diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000..bf8ada5
Binary files /dev/null and b/.DS_Store differ
diff --git a/._.DS_Store b/._.DS_Store
new file mode 100644
index 0000000..28c42fb
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diff --git a/.gitignore b/.gitignore
index b6e4761..7cd481f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -127,3 +127,9 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# Optimization outputs
+out_*/
+out_s*/
+out_s*
+threed1.*
diff --git a/AGENTS.md b/AGENTS.md
new file mode 100644
index 0000000..e02d7ec
--- /dev/null
+++ b/AGENTS.md
@@ -0,0 +1,50 @@
+# Repository Guidelines
+
+## Project Structure & Module Organization
+
+- `main.py`: primary EP + equilibrium optimization driver (MPI-aware); produces
+  output folders like `out_s*_NFP*` and CSV logs `output_*.csv`.
+- `initial_configs/`: VMEC input files used as starting points (e.g.
+  `initial_configs/input.nfp2_QA`).
+- `Alan_objectives.py`: objective/penalty utilities (mirror ratio, elongation).
+- `plot_opt.py`, `vmecPlot2.py`: post-processing and plotting helpers.
+- `regression_test.py`, `test_search_global_minimum.py`: standalone scripts for
+  robustness checks / optimization experiments.
+
+## Build, Test, and Development Commands
+
+This repo is script-driven (no package build step). Use a Python environment
+that has the scientific stack plus VMEC + NEAT installed.
+
+- Install dependencies (examples):
+  - `python3 -m pip install numpy scipy pandas matplotlib mpi4py simsopt booz_xform`
+  - VMEC extension (required by `simsopt.mhd.Vmec`): `python3 -m pip install git+ssh://git@github.com/hiddenSymmetries/VMEC2000.git`
+  - NEAT (required by `from neat...`): `python3 -m pip install -e ../NEAT`
+- If VMEC fails to build due to hardcoded compiler/library paths, edit the
+  VMEC2000 `cmake_config_file.json` to point at your `mpicc`/`mpifort` and
+  NetCDF include/lib directories (e.g. `/usr/include`, `/usr/lib`).
+- Run optimization: `mpirun -n 4 python3 main.py` (or `python3 main.py` for
+  serial experiments).
+- Plot results (after an optimization run): `python3 plot_opt.py`.
+
+## Coding Style & Naming Conventions
+
+- Python, 4-space indentation, keep lines reasonably short.
+- Prefer `pathlib.Path` over manual string path joins in new code.
+- Keep scripts runnable from the repository root (assume `initial_configs/` is
+  available via relative paths).
+
+## Testing Guidelines
+
+There is no pytest suite. Use quick smoke checks before larger runs:
+
+- VMEC + SIMSOPT sanity run (writes to `/tmp`): `python3 -c "from simsopt.mhd import Vmec; import os; os.chdir('/tmp'); Vmec('path/to/initial_configs/input.nfp2_QA', verbose=False).run()"`
+- Import sanity: `python3 -c "from neat.fields import Simple; from simsopt.mhd import Vmec"`
+
+## Commit & Pull Request Guidelines
+
+- Commit messages in this repo are short, imperative, and capitalized (e.g.
+  Added ..., Create ..., Initial commit); follow that style.
+- PRs should describe the physics intent, list runtime/environment assumptions
+  (MPI size, key parameters), and include plots/CSV excerpts when they help
+  reviewers reproduce results.
diff --git a/Alan_objectives.py b/Alan_objectives.py
index 62b8c7e..ccbb4ac 100644
--- a/Alan_objectives.py
+++ b/Alan_objectives.py
@@ -225,9 +225,9 @@ def FindBoundary(theta,phi):
         # Fit an ellipse to this cross-section shape
         perim_resid = lambda a : perim - (4*a*ellipe(1 - ( A / (np.pi * a**2 ) )**2))
         if iphi == 0:
-            a1 = fsolve(perim_resid, 1)
+            a1 = float(np.asarray(fsolve(perim_resid, 1)).item())
         else:
-            a1 = fsolve(perim_resid, a1)
+            a1 = float(np.asarray(fsolve(perim_resid, a1)).item())
         a2 = A / (np.pi * a1)
         if a1 > a2:
             maj = a1
@@ -275,4 +275,4 @@ def MirrorRatioPen(v, mirror_threshold=0.20, output_mirror=False):
     # print("Mirror =",m)
     pen = np.max([0,m-mirror_threshold])
     if output_mirror: return m
-    else: return pen
\ No newline at end of file
+    else: return pen
diff --git a/README.md b/README.md
index 62cf13f..f5bb3ab 100644
--- a/README.md
+++ b/README.md
@@ -1,2 +1,16 @@
 # EPoptimization
-Energetic Particle Stellarator Optimization
+
+This branch runs a direct collisionless alpha-loss study. It minimizes the
+measured 100 ms loss fraction for 256 deterministic 3.5 MeV alpha particles
+born at `s = 0.25`. Mirror ratio and maximum elongation are broad feasibility
+constraints; proxy, classifier, Gamma-c, and effective-ripple quantities do
+not enter the objective.
+
+`main.py` primes constrained TuRBO/SCBO from completed direct observations.
+`generate_scbo_candidates.py` maps requests through the bounded ALPES-centered
+eight-dimensional chart, and `run_direct_scbo_candidate.sh` evaluates VMEC,
+geometry feasibility, and the pinned SIMPLE direct metric.
+
+The campaign contract, exact executable hashes, provenance, and cluster
+orchestration live in the companion `alpha-loss-optimization-data` repository
+under `runs/alpha_direct_turbo_v1/`.
diff --git a/advance_alpha_scbo.py b/advance_alpha_scbo.py
new file mode 100644
index 0000000..53f9cfc
--- /dev/null
+++ b/advance_alpha_scbo.py
@@ -0,0 +1,51 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+
+def advance(args: argparse.Namespace) -> None:
+    from simsopt_dfo.scbo_checkpoint import (
+        complete_candidates,
+        issue_candidates,
+        write_checkpoint,
+    )
+
+    state = json.loads(args.state.read_text())
+    responses = pending_responses(state, args.responses)
+    state = complete_candidates(state, responses)
+    state, requests = issue_candidates(state)
+    write_checkpoint(args.state, state)
+    args.requests.write_text(
+        json.dumps({"requests": requests}, indent=2, sort_keys=True) + "\n"
+    )
+
+
+def pending_responses(state: dict, root: Path) -> list[dict]:
+    pending = {row["candidate_id"] for row in state["pending"]}
+    rows = [json.loads(path.read_text()) for path in Path(root).glob("*/response.json")]
+    selected = sorted(
+        (row for row in rows if row["candidate_id"] in pending),
+        key=lambda row: row["candidate_id"],
+    )
+    if {row["candidate_id"] for row in selected} != pending:
+        raise ValueError("SCBO response wave does not cover every pending candidate")
+    return selected
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--state", type=Path, required=True)
+    root.add_argument("--responses", type=Path, required=True)
+    root.add_argument("--requests", type=Path, required=True)
+    return root
+
+
+def main() -> None:
+    advance(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/barrier_overlap.py b/barrier_overlap.py
new file mode 100644
index 0000000..ce9c1ed
--- /dev/null
+++ b/barrier_overlap.py
@@ -0,0 +1,715 @@
+"""Continuous radial-barrier proxy from SIMPLE fast orbit classification.
+
+Production uses only the raw J_parallel variation and tip-map rotation-drift
+scores.  It reconstructs each score on fixed magnetic-moment nodes over several
+radial surfaces, takes a soft minimum along the escape path, and integrates the
+result against deterministic alpha-birth quadrature weights. Lower is better.
+
+Three corrections against the 2026-07 campaign, which concluded the fast
+classifier was slower than direct loss tracing:
+
+1. ``class_plot`` stays ``.False.``. The early exit in SIMPLE's
+   classification.f90 requires ``.not. class_plot``; with it set, no orbit ever
+   exits early and every trace runs to ``trace_time``. The old namelist had it
+   ``.True.`` in every commit of its history.
+2. ``tcut = -1d0`` with ``fast_class = .True.``. This needs SIMPLE with the
+   standalone-dispatch fix (PR #512): before it, that combination silently
+   disabled the classifier and wrote no ``class_parts.dat``. It is the only
+   configuration that classifies without the Minkowski fractal cut, which
+   fires at ``kt == ntcut``.
+3. ``notrace_passing = 1`` on *both* surfaces. The overlap masks everything by
+   the trapped flag, so passing particles at the birth surface were traced for
+   nothing and cost three quarters of the old budget. ``trap_par`` is computed
+   before the skip and written for every particle, so the trapped mask is
+   unaffected.
+
+Starting points are a deterministic product grid rather than random draws, so
+the same phase-space points are compared across candidate designs.
+
+The old two-surface integer overlap helpers remain below only to read archived
+campaigns.  :func:`barrier_metrics` never reads an integer class or invokes the
+Minkowski classifier.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import os
+import shutil
+import subprocess
+import tempfile
+import time
+from pathlib import Path
+from typing import Sequence
+
+import numpy as np
+
+CLASS_COLUMN = {"jpar": 3, "topology": 4}
+
+A_TARGET = 1.704
+B_TARGET = 5.865
+
+#: Boozer field, midpoint symplectic integrator. Pinned for every run.
+ISW_FIELD_TYPE_BOOZER = 2
+INTEGMODE_MIDPOINT = 3
+
+CLASSIFY_NAMELIST = """&config
+  netcdffile = 'wout.nc'
+  startmode = 2
+  num_surf = {num_surf}
+  notrace_passing = 1
+  ntestpart = {n}
+  trace_time = {ttime}
+  sbeg = {sbeg}
+  contr_pp = -1.0d10
+  n_e = 2
+  n_d = 4
+  facE_al = 1.0d0
+  npoiper = 100
+  npoiper2 = 256
+  ns_s = 5
+  ns_tp = 5
+  multharm = 5
+  isw_field_type = {field_type}
+  integmode = {integmode}
+  relerr = 1d-13
+  nturns = {nturns}
+  tcut = -1d0
+  vmec_RZ_scale = {rz}
+  vmec_B_scale = {b}
+  class_plot = .False.
+  fast_class = .True.
+  swcoll = .False.
+  deterministic = .True.
+  ran_seed = {seed}
+/
+"""
+
+
+def find_simple_x(explicit: str | os.PathLike | None = None) -> Path:
+    if explicit is not None:
+        path = Path(explicit)
+        if not path.exists():
+            raise FileNotFoundError(path)
+        return path
+    environment = os.environ.get("SIMPLE_X") or os.environ.get("SIMPLE_EXE")
+    if environment:
+        path = Path(environment)
+        if not path.exists():
+            raise FileNotFoundError(path)
+        return path
+    for candidate in (
+        Path.home() / "code" / "SIMPLE" / "build" / "simple.x",
+        Path.home() / "bin" / "simple.x",
+    ):
+        if candidate.exists():
+            return candidate
+    installed = shutil.which("simple.x")
+    if installed:
+        return Path(installed)
+    raise FileNotFoundError("Could not locate SIMPLE executable")
+
+
+def file_sha256(path: str | os.PathLike) -> str:
+    digest = hashlib.sha256()
+    with Path(path).open("rb") as handle:
+        for block in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def reactor_scale(wout_path: str | os.PathLike) -> tuple[float, float]:
+    """Return scales that put a VMEC equilibrium at the ARIES-CS point."""
+    from scipy.io import netcdf_file
+
+    with netcdf_file(str(wout_path), "r", mmap=False) as dataset:
+        minor_radius = float(dataset.variables["Aminor_p"][()])
+        mean_field = float(dataset.variables["volavgB"][()])
+    return A_TARGET / minor_radius, B_TARGET / abs(mean_field)
+
+
+def pitch_quadrature(
+    count: int, *, pitch_max: float = 1.0
+) -> tuple[np.ndarray, np.ndarray]:
+    """Gauss-Legendre nodes and normalized weights for isotropic pitch.
+
+    Fusion alpha birth is uniform in ``v_parallel / v``.  Fixed quadrature
+    nodes therefore represent that distribution without random sampling and
+    without deriving a grid from the candidate geometry.
+    """
+    if count <= 0:
+        raise ValueError("pitch count must be positive")
+    if not 0.0 < pitch_max <= 1.0:
+        raise ValueError("pitch bound must lie in (0, 1]")
+    nodes, weights = np.polynomial.legendre.leggauss(count)
+    nodes = pitch_max * nodes
+    weights = pitch_max * weights
+    return nodes, weights / weights.sum()
+
+
+def pitch_grid(count: int, *, pitch_max: float = 1.0) -> np.ndarray:
+    """Pitch nodes from :func:`pitch_quadrature`."""
+    return pitch_quadrature(count, pitch_max=pitch_max)[0]
+
+
+def starting_grid(
+    surface: float,
+    *,
+    ntheta: int,
+    nzeta: int,
+    npitch: int,
+    nfp: int,
+    pitch_max: float = 1.0,
+) -> np.ndarray:
+    """Deterministic (theta, zeta, pitch) product grid in VMEC coordinates.
+
+    Columns match SIMPLE's ``start.dat``: s, theta, varphi, v/v0, v_par/v.
+    Angles are cell-centred so no point sits on a symmetry plane, and zeta
+    spans one field period since the equilibrium repeats.
+    """
+    if not 0.0 < surface < 1.0:
+        raise ValueError("birth surface must lie inside the plasma")
+    if min(ntheta, nzeta, npitch) <= 0 or nfp <= 0:
+        raise ValueError("grid counts and field-period number must be positive")
+    theta = 2.0 * np.pi * (np.arange(ntheta) + 0.5) / ntheta
+    zeta = 2.0 * np.pi * (np.arange(nzeta) + 0.5) / (nfp * nzeta)
+    pitch = pitch_grid(npitch, pitch_max=pitch_max)
+    mesh = np.stack(np.meshgrid(theta, zeta, pitch, indexing="ij"), axis=-1).reshape(
+        -1, 3
+    )
+    rows = np.empty((mesh.shape[0], 5), dtype=float)
+    rows[:, 0] = surface
+    rows[:, 1] = mesh[:, 0]
+    rows[:, 2] = mesh[:, 1]
+    rows[:, 3] = 1.0
+    rows[:, 4] = mesh[:, 2]
+    return rows
+
+
+def starting_weights(ntheta: int, nzeta: int, npitch: int) -> np.ndarray:
+    """Normalized alpha-birth weights in ``starting_grid`` row order."""
+    if min(ntheta, nzeta, npitch) <= 0:
+        raise ValueError("grid counts must be positive")
+    _, pitch_weights = pitch_quadrature(npitch)
+    weights = np.tile(pitch_weights, ntheta * nzeta)
+    return weights / (ntheta * nzeta)
+
+
+#: SIMPLE splines the equilibrium with ns_s = ns_tp = 5, so a wout with too
+#: few flux surfaces overruns the spline construction and aborts the process
+#: inside spline_vmec_data rather than returning an error.
+MINIMUM_FLUX_SURFACES = 2 * 5 + 1
+
+
+def field_periods(wout_path: str | os.PathLike) -> int:
+    from scipy.io import netcdf_file
+
+    with netcdf_file(str(wout_path), "r", mmap=False) as dataset:
+        return int(dataset.variables["nfp"][()])
+
+
+def flux_surface_count(wout_path: str | os.PathLike) -> int:
+    from scipy.io import netcdf_file
+
+    with netcdf_file(str(wout_path), "r", mmap=False) as dataset:
+        return int(dataset.variables["ns"][()])
+
+
+def check_radial_resolution(wout_path: str | os.PathLike) -> int:
+    """Reject equilibria too coarse for SIMPLE's radial splines."""
+    surfaces = flux_surface_count(wout_path)
+    if surfaces < MINIMUM_FLUX_SURFACES:
+        raise ValueError(
+            f"{wout_path} has ns={surfaces}, below the {MINIMUM_FLUX_SURFACES} "
+            "flux surfaces SIMPLE needs for ns_s = ns_tp = 5; raise NS_ARRAY "
+            "in the VMEC input"
+        )
+    return surfaces
+
+
+def load_classification(
+    run: Path, column: int
+) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
+    """Return (perp_inv, class code, trapped mask) for one classification run.
+
+    ``trap_par`` is column 3 of ``times_lost.dat`` and is written for every
+    particle, including the passing ones skipped by ``notrace_passing``.
+    """
+    classes = np.loadtxt(run / "class_parts.dat", ndmin=2)
+    particles = np.loadtxt(run / "times_lost.dat", ndmin=2)
+    if classes.shape[0] != particles.shape[0]:
+        raise ValueError(f"classification particle count mismatch in {run}")
+    if not np.array_equal(classes[:, 0].astype(int), particles[:, 0].astype(int)):
+        raise ValueError(f"classification particle indices mismatch in {run}")
+    if classes.shape[1] <= column or particles.shape[1] < 3:
+        raise ValueError(f"classification output is missing columns in {run}")
+    return classes[:, 2], classes[:, column].astype(int), particles[:, 2] > 0.0
+
+
+def barrier_overlap_samples(
+    mu_inner: np.ndarray,
+    class_inner: np.ndarray,
+    trapped_inner: np.ndarray,
+    mu_outer: np.ndarray,
+    class_outer: np.ndarray,
+    trapped_outer: np.ndarray,
+    *,
+    edges: np.ndarray,
+) -> float:
+    """Sum over mu bins of P(chaotic at birth) * F(chaotic at barrier).
+
+    ``edges`` is supplied by the caller rather than derived from the samples.
+    Deriving them from the common mu range, as the 2026-07 version did, moves
+    the bin boundaries with the candidate geometry and makes the metric
+    discontinuous in the design variables.
+    """
+    edges = np.asarray(edges, dtype=float)
+    if edges.ndim != 1 or edges.size < 2 or not np.all(np.diff(edges) > 0.0):
+        raise ValueError("mu bin edges must be increasing and at least two")
+    if trapped_inner.sum() == 0 or trapped_outer.sum() == 0:
+        return float("nan")
+    inner_total = int(trapped_inner.sum())
+    nbins = edges.size - 1
+    overlap = 0.0
+    for index in range(nbins):
+        low, high = edges[index], edges[index + 1]
+        last = index == nbins - 1
+        in_inner = (mu_inner >= low) & (mu_inner <= high if last else mu_inner < high)
+        in_outer = (mu_outer >= low) & (mu_outer <= high if last else mu_outer < high)
+        inner = trapped_inner & in_inner
+        outer = trapped_outer & in_outer
+        if inner.sum() == 0 or outer.sum() == 0:
+            continue
+        birth_chaotic = float((class_inner[inner] == 2).sum()) / inner_total
+        barrier_breach = float((class_outer[outer] == 2).sum()) / int(outer.sum())
+        overlap += birth_chaotic * barrier_breach
+    return float(overlap)
+
+
+#: SIMPLE carries the field in Gauss, so ``perp_inv = v_perp**2 / B`` for a
+#: normalised speed sits near ``1 / (B[T] * 1e4)`` — of order 1e-5 at reactor
+#: field, not of order 0.1.
+GAUSS_PER_TESLA = 1.0e4
+
+#: Fraction of the reference mu the bin band spans on either side. Trapped
+#: particles occupy roughly ``1/B_max`` to ``1/B_min``, a factor set by the
+#: mirror ratio; +-30% covers a mirror ratio of 0.2 with margin.
+MU_BAND_FRACTION = 0.3
+
+
+def reference_mu() -> float:
+    """Perpendicular invariant of a trapped particle at the reactor field."""
+    return 1.0 / (B_TARGET * GAUSS_PER_TESLA)
+
+
+def fixed_mu_edges(b_scale: float, *, nbins: int) -> np.ndarray:
+    """Design-independent mu bin edges.
+
+    ``perp_inv`` is ``v_perp**2 / B`` in SIMPLE's units, so for a normalised
+    speed of one it is of order ``1 / B_min`` with B in Gauss. Anchoring the
+    edges to the reactor field rather than to the sample range keeps the bins
+    identical across candidates, which is what the optimizer needs.
+
+    The band is centred on the reference mu rather than starting at zero.
+    Trapped particles occupy a narrow band set by the mirror ratio, so bins
+    running from zero put every one of them in the first bin and throw away
+    all the mu resolution the metric is built on.
+    """
+    if nbins <= 0 or not np.isfinite(b_scale) or b_scale <= 0.0:
+        raise ValueError("bin count and field scale must be positive")
+    centre = reference_mu()
+    return np.linspace(
+        centre * (1.0 - MU_BAND_FRACTION), centre * (1.0 + MU_BAND_FRACTION), nbins + 1
+    )
+
+
+def fixed_mu_nodes(count: int) -> np.ndarray:
+    """Design-independent quadrature nodes for continuous ``mu`` fields."""
+    if count < 3:
+        raise ValueError("at least three mu nodes are required")
+    centre = reference_mu()
+    return np.linspace(
+        centre * (1.0 - MU_BAND_FRACTION),
+        centre * (1.0 + MU_BAND_FRACTION),
+        count,
+    )
+
+
+def radial_quadrature_weights(surfaces: Sequence[float]) -> np.ndarray:
+    """Normalized trapezoid weights on an increasing radial path."""
+    surfaces = np.asarray(surfaces, dtype=float)
+    if surfaces.ndim != 1 or surfaces.size < 2:
+        raise ValueError("at least two radial surfaces are required")
+    if not np.all(np.diff(surfaces) > 0.0):
+        raise ValueError("radial surfaces must be strictly increasing")
+    weights = np.empty_like(surfaces)
+    weights[0] = 0.5 * (surfaces[1] - surfaces[0])
+    weights[-1] = 0.5 * (surfaces[-1] - surfaces[-2])
+    weights[1:-1] = 0.5 * (surfaces[2:] - surfaces[:-2])
+    return weights / weights.sum()
+
+
+def classification_loss_metrics(
+    run: Path,
+    *,
+    prompt_time: float,
+    trace_time: float,
+    sample_weights: np.ndarray | None = None,
+    rows: slice | None = None,
+) -> dict[str, float | int]:
+    """Loss fractions from a classification run.
+
+    Passing particles are skipped and recorded with ``times_lost = -1``, so
+    they count as confined. That is a bias only to the extent that passing
+    particles are actually lost, which is negligible at reactor scale on this
+    time scale, and it is what makes the run cheap.
+    """
+    particles = np.loadtxt(run / "times_lost.dat", ndmin=2)
+    if particles.ndim != 2 or particles.shape[1] < 2:
+        raise ValueError(f"invalid times_lost.dat in {run}")
+    if not 0.0 < prompt_time < trace_time:
+        raise ValueError("loss windows require 0 < prompt < trace")
+    if rows is not None:
+        particles = particles[rows]
+    times = particles[:, 1]
+    prompt = (times > 0.0) & (times <= prompt_time)
+    late = (times > prompt_time) & (times < trace_time)
+    count = times.size
+    weights = (
+        np.ones(count, dtype=float)
+        if sample_weights is None
+        else np.asarray(sample_weights, dtype=float)
+    )
+    if weights.shape != (count,) or np.any(weights < 0.0):
+        raise ValueError("loss sample weights are invalid")
+    if not np.all(np.isfinite(weights)) or weights.sum() <= 0.0:
+        raise ValueError("loss sample weights must be finite with positive mass")
+    return {
+        "particles": int(count),
+        "prompt_count": int(prompt.sum()),
+        "late_count": int(late.sum()),
+        "prompt_loss": float(np.average(prompt, weights=weights)),
+        "late_loss": float(np.average(late, weights=weights)),
+        "total_loss": float(np.average(prompt | late, weights=weights)),
+    }
+
+
+def run_classification(
+    wout_path: str | os.PathLike,
+    *,
+    surface: float,
+    starts: np.ndarray,
+    rz_scale: float,
+    b_scale: float,
+    trace_time: float,
+    nturns: int,
+    seed: int,
+    workdir: Path,
+    surface_bounds: Sequence[float] | None = None,
+    simple_executable: str | os.PathLike | None = None,
+    timeout_s: float = 3600.0,
+) -> Path:
+    starts = np.asarray(starts, dtype=float)
+    if starts.ndim != 2 or starts.shape[1] != 5:
+        raise ValueError("starting points must have five columns")
+    simple_x = find_simple_x(simple_executable)
+    workdir.mkdir(parents=True, exist_ok=True)
+    shutil.copyfile(wout_path, workdir / "wout.nc")
+    np.savetxt(workdir / "start.dat", starts, fmt="%.17e")
+    bounds = [surface] if surface_bounds is None else list(surface_bounds)
+    if not bounds:
+        raise ValueError("at least one classifier surface is required")
+    namelist_surfaces = [bounds[0]] if len(bounds) == 1 else [bounds[0], bounds[-1]]
+    sbeg = ", ".join(
+        f"{float(value):.16e}".replace("e", "d") for value in namelist_surfaces
+    )
+    (workdir / "simple.in").write_text(
+        CLASSIFY_NAMELIST.format(
+            n=starts.shape[0],
+            ttime=_fortran_d(trace_time),
+            num_surf=len(namelist_surfaces),
+            sbeg=sbeg,
+            field_type=ISW_FIELD_TYPE_BOOZER,
+            integmode=INTEGMODE_MIDPOINT,
+            nturns=int(nturns),
+            rz=_fortran_d(rz_scale),
+            b=_fortran_d(b_scale),
+            seed=int(seed),
+        )
+    )
+    log_path = workdir / "simple_stdout.txt"
+    with log_path.open("w") as log:
+        completed = subprocess.run(
+            [str(simple_x)],
+            cwd=str(workdir),
+            stdout=log,
+            stderr=subprocess.STDOUT,
+            text=True,
+            timeout=timeout_s,
+            check=False,
+        )
+    if completed.returncode != 0:
+        raise RuntimeError(
+            f"SIMPLE failed with exit code {completed.returncode}; see {log_path}"
+        )
+    if not (workdir / "class_parts.dat").exists():
+        raise FileNotFoundError(
+            f"{workdir / 'class_parts.dat'} is missing; SIMPLE must carry the "
+            "fast_class standalone dispatch fix"
+        )
+    return workdir
+
+
+DEFAULT_CONTINUOUS_SETTINGS = {
+    "trapped_width": 0.15,
+    "mu_width_factor": 0.75,
+    "temperature_jpar": 0.1,
+    "temperature_rotation": 0.02,
+}
+
+
+def load_perp_invariant(run: Path) -> np.ndarray:
+    """Read magnetic moment without consulting any integer class column."""
+    table = np.loadtxt(run / "class_parts.dat", ndmin=2)
+    if table.shape[1] < 3:
+        raise ValueError(f"class_parts.dat is missing magnetic moment in {run}")
+    expected = np.arange(1, table.shape[0] + 1)
+    if not np.array_equal(table[:, 0].astype(int), expected):
+        raise ValueError(
+            f"class_parts.dat particle indices are not sequential in {run}"
+        )
+    return table[:, 2]
+
+
+def barrier_metrics(
+    wout_path: str | os.PathLike,
+    *,
+    expected_simple_sha256: str,
+    surfaces: Sequence[float],
+    ntheta: int,
+    nzeta: int,
+    npitch: int,
+    pitch_max: float,
+    nmu: int,
+    trace_time: float,
+    prompt_time: float,
+    nturns: int,
+    seed: int,
+    continuous_settings: dict | None = None,
+    simple_executable: str | os.PathLike | None = None,
+    work_root: str | os.PathLike | None = None,
+    keep_workdir: bool = False,
+    timeout_s: float = 3600.0,
+) -> dict:
+    """Run raw fast classifiers and form continuous radial-barrier fields."""
+    surfaces = np.asarray(surfaces, dtype=float)
+    radial_weights = radial_quadrature_weights(surfaces)
+    if surfaces[0] <= 0.0 or surfaces[-1] >= 1.0:
+        raise ValueError("barrier surfaces must lie strictly inside the plasma")
+    simple_x = find_simple_x(simple_executable)
+    binary_hash = file_sha256(simple_x)
+    if binary_hash != expected_simple_sha256:
+        raise ValueError("unexpected SIMPLE executable hash")
+    check_radial_resolution(wout_path)
+    rz_scale, b_scale = reactor_scale(wout_path)
+    nfp = field_periods(wout_path)
+    nodes = fixed_mu_nodes(nmu)
+    particle_weights = starting_weights(ntheta, nzeta, npitch)
+    work_parent = None if work_root is None else Path(work_root)
+    if work_parent is not None:
+        work_parent.mkdir(parents=True, exist_ok=True)
+    base = Path(tempfile.mkdtemp(prefix="continuous_barrier_", dir=work_parent))
+    total_started = time.monotonic()
+    try:
+        particles_per_surface = ntheta * nzeta * npitch
+        starts = np.concatenate(
+            [
+                starting_grid(
+                    float(surface),
+                    ntheta=ntheta,
+                    nzeta=nzeta,
+                    npitch=npitch,
+                    nfp=nfp,
+                    pitch_max=pitch_max,
+                )
+                for surface in surfaces
+            ]
+        )
+        surface_slices = [
+            slice(index * particles_per_surface, (index + 1) * particles_per_surface)
+            for index in range(len(surfaces))
+        ]
+        started = time.monotonic()
+        run = run_classification(
+            wout_path,
+            surface=float(surfaces[0]),
+            surface_bounds=(float(surfaces[0]), float(surfaces[-1])),
+            starts=starts,
+            rz_scale=rz_scale,
+            b_scale=b_scale,
+            trace_time=trace_time,
+            nturns=nturns,
+            seed=seed,
+            workdir=base / "all_surfaces",
+            simple_executable=simple_x,
+            timeout_s=timeout_s,
+        )
+        classification_seconds = time.monotonic() - started
+        continuous = _continuous_metrics(
+            [run],
+            particle_weights,
+            nodes=nodes,
+            radial_weights=radial_weights,
+            settings=continuous_settings,
+            surface_slices=surface_slices,
+        )
+        losses = classification_loss_metrics(
+            run,
+            prompt_time=prompt_time,
+            trace_time=trace_time,
+            sample_weights=particle_weights,
+            rows=surface_slices[0],
+        )
+        return {
+            "continuous": continuous,
+            "classifiers": ["jpar", "rotation"],
+            "prompt_loss_birth": losses["prompt_loss"],
+            "short_loss_birth": losses["total_loss"],
+            "loss_metrics_birth": losses,
+            "trapped_count_by_surface": continuous["trapped_count_by_surface"],
+            "soft_trapped_mass_by_surface": continuous["soft_trapped_mass_by_surface"],
+            "particles_per_surface": particles_per_surface,
+            "pitch_max": float(pitch_max),
+            "sample_distribution": "isotropic-pitch-gauss-legendre-equal-angle",
+            "mu_nodes": nodes.tolist(),
+            "surfaces": surfaces.tolist(),
+            "radial_weights": radial_weights.tolist(),
+            "s_inner": float(surfaces[0]),
+            "s_outer": float(surfaces[-1]),
+            "nfp": nfp,
+            "trace_time": float(trace_time),
+            "nturns": int(nturns),
+            "seed": int(seed),
+            "integmode": INTEGMODE_MIDPOINT,
+            "isw_field_type": ISW_FIELD_TYPE_BOOZER,
+            "vmec_RZ_scale": float(rz_scale),
+            "vmec_B_scale": float(b_scale),
+            "classification_mode": "batched-surfaces",
+            "classification_seconds": classification_seconds,
+            "seconds_total": time.monotonic() - total_started,
+            "simple_sha256": binary_hash,
+            "wout_sha256": file_sha256(wout_path),
+            "workdir": str(base) if keep_workdir else "",
+        }
+    finally:
+        if not keep_workdir:
+            shutil.rmtree(base, ignore_errors=True)
+
+
+def _continuous_metrics(
+    runs: Sequence[Path],
+    particle_weights: np.ndarray,
+    *,
+    nodes: np.ndarray,
+    radial_weights: np.ndarray,
+    settings: dict | None,
+    surface_slices: Sequence[slice] | None = None,
+) -> dict:
+    """Aggregate only raw J_parallel and rotation-drift score fields."""
+    from smooth_barrier import (
+        birth_weighted_integral,
+        continuous_barrier_metric,
+        load_class_scores,
+        resolved_fraction,
+        trapped_weight,
+    )
+
+    configured = dict(DEFAULT_CONTINUOUS_SETTINGS)
+    if settings:
+        unknown = set(settings) - set(configured)
+        if unknown:
+            raise ValueError(f"unknown continuous settings: {sorted(unknown)}")
+        configured.update(settings)
+    if any(not np.isfinite(value) or value <= 0.0 for value in configured.values()):
+        raise ValueError("continuous settings must be finite and positive")
+
+    if surface_slices is None:
+        score_runs = [load_class_scores(run) for run in runs]
+        mu_runs = [load_perp_invariant(run) for run in runs]
+    else:
+        if len(runs) != 1:
+            raise ValueError("batched surface slices require exactly one SIMPLE run")
+        all_scores = load_class_scores(runs[0])
+        all_mu = load_perp_invariant(runs[0])
+        score_runs = [all_scores.subset(rows) for rows in surface_slices]
+        mu_runs = [all_mu[rows] for rows in surface_slices]
+    if any(len(scores) != particle_weights.size for scores in score_runs):
+        raise ValueError("particle quadrature and classifier output sizes differ")
+    spacing = float(nodes[1] - nodes[0])
+    mu_width = configured["mu_width_factor"] * spacing
+    result = {}
+    for classifier in ("jpar", "rotation"):
+        metric = continuous_barrier_metric(
+            score_runs,
+            mu_runs,
+            nodes,
+            classifier=classifier,
+            temperature=configured[f"temperature_{classifier}"],
+            trapped_width=configured["trapped_width"],
+            mu_width=mu_width,
+            sample_weights_by_surface=[particle_weights] * len(score_runs),
+            surface_weights=radial_weights,
+        )
+        birth_mean = birth_weighted_integral(
+            nodes,
+            metric.surface_fields[0].values,
+            metric.birth_density,
+        )
+        result[classifier] = {
+            "birth_mean": _finite_or_none(birth_mean),
+            "barrier_defect": _finite_or_none(metric.value),
+            "resolved_coverage": _finite_or_none(metric.resolved_coverage),
+            "resolved_fraction_by_surface": [
+                resolved_fraction(scores, classifier=classifier)
+                for scores in score_runs
+            ],
+            "barrier_field": _array_for_json(metric.barrier_field),
+            "birth_density": _array_for_json(metric.birth_density),
+            "surface_fields": [
+                {
+                    "values": _array_for_json(field.values),
+                    "resolved_coverage": _array_for_json(field.resolved_coverage),
+                }
+                for field in metric.surface_fields
+            ],
+        }
+    soft_trapped = [
+        float(
+            np.sum(
+                particle_weights
+                * trapped_weight(scores.trap_par, width=configured["trapped_width"])
+            )
+        )
+        for scores in score_runs
+    ]
+    return {
+        "settings": {**configured, "mu_width": mu_width},
+        "jpar": result["jpar"],
+        "rotation": result["rotation"],
+        "trapped_count_by_surface": [
+            int(np.sum(scores.trap_par > 0.0)) for scores in score_runs
+        ],
+        "soft_trapped_mass_by_surface": soft_trapped,
+    }
+
+
+def _finite_or_none(value: float) -> float | None:
+    return float(value) if np.isfinite(value) else None
+
+
+def _array_for_json(values: np.ndarray) -> list[float | None]:
+    return [_finite_or_none(value) for value in np.asarray(values, dtype=float)]
+
+
+def _fortran_d(value: float) -> str:
+    return f"{float(value):.16g}".replace("e", "d").replace("E", "d")
diff --git a/build_barrier_scbo_response.py b/build_barrier_scbo_response.py
new file mode 100644
index 0000000..d92e23d
--- /dev/null
+++ b/build_barrier_scbo_response.py
@@ -0,0 +1,159 @@
+#!/usr/bin/env python3
+"""Turn continuous fast-classifier fields into an optimizer response.
+
+Constraints are mirror ratio, maximum elongation, and prompt loss, all in the
+``value / limit - 1 <= 0`` convention the geometry evaluator already uses.
+Prompt loss remains a constraint because an orbit lost before three banana
+tips cannot carry either raw finite-time score.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+
+def base_response(request: dict, status: str, failure_kind: str | None) -> dict:
+    return {
+        "candidate_id": int(request["candidate_id"]),
+        "unit_x": [float(value) for value in request["unit_x"]],
+        "observation": None,
+        "status": status,
+        "failure_kind": failure_kind,
+    }
+
+
+OBJECTIVES = (
+    "jpar",
+    "rotation",
+    "barrier-jpar",
+    "barrier-rotation",
+)
+
+
+def select_objective(barrier: dict, objective: str) -> float:
+    if objective not in OBJECTIVES:
+        raise ValueError(f"unknown objective {objective}")
+    classifier = objective.removeprefix("barrier-")
+    key = "barrier_defect" if objective.startswith("barrier-") else "birth_mean"
+    continuous = barrier.get("continuous") or {}
+    score = continuous.get(classifier) or {}
+    value = score.get(key)
+    if value is None:
+        resolved = score.get("resolved_fraction_by_surface")
+        raise ValueError(
+            f"{objective} has no value on this candidate; resolved fractions "
+            f"were {resolved}"
+        )
+    return float(value)
+
+
+def successful_response(
+    request: dict,
+    result: dict,
+    geometry: dict,
+    *,
+    objective: str,
+    inner_surface: float,
+    outer_surface: float,
+    particles_per_surface: int,
+    prompt_limit: float,
+) -> dict:
+    if result.get("schema_name") != "alpha-loss.continuous-fast-classifier-result":
+        raise ValueError("barrier result has an unexpected schema")
+    if geometry.get("schema_name") != "alpha-loss.direct-geometry":
+        raise ValueError("geometry document has an unexpected schema")
+    if not 0.0 < prompt_limit <= 1.0:
+        raise ValueError("prompt loss limit must lie in (0, 1]")
+
+    barrier = result["barrier"]
+    expected = {
+        "s_inner": inner_surface,
+        "s_outer": outer_surface,
+        "particles_per_surface": particles_per_surface,
+    }
+    for key, value in expected.items():
+        if key not in barrier or not np.isclose(barrier[key], value):
+            raise ValueError(f"barrier result has unexpected {key}")
+
+    overlap = float(select_objective(barrier, objective))
+    if not np.isfinite(overlap):
+        raise ValueError(f"objective {objective} is not finite")
+    trapped = barrier["trapped_count_by_surface"]
+    if not trapped or min(trapped) <= 0:
+        raise ValueError("barrier surfaces carry no trapped particles")
+
+    prompt_loss = float(barrier["prompt_loss_birth"])
+    geometry_constraints = [float(value) for value in geometry["constraints"]]
+    if len(geometry_constraints) != 2:
+        raise ValueError("geometry constraints are incomplete")
+    constraints = geometry_constraints + [prompt_loss / prompt_limit - 1.0]
+    if not np.isfinite(constraints).all():
+        raise ValueError("constraints must be finite")
+
+    response = base_response(request, "ok", None)
+    response["observation"] = {
+        "value": overlap,
+        "constraints": constraints,
+        "constraint_variances": [0.0, 0.0, 0.0],
+    }
+    response["metrics"] = {
+        "objective_name": (
+            f"{objective}_continuous_fast_classifier"
+            f"_s{inner_surface:g}_to_s{outer_surface:g}"
+        ),
+        "objective_kind": objective,
+        "continuous_fast_classifier": barrier["continuous"],
+        "constraint_names": list(geometry["constraint_names"]) + ["prompt_loss"],
+        "constraint_limits": list(geometry["constraint_limits"]) + [prompt_limit],
+        "barrier": barrier,
+        "geometry": geometry["metrics"],
+        "geometry_feasible": bool(geometry["feasible"]),
+        "wout_sha256": result["wout_sha256"],
+    }
+    return response
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--request", type=Path, required=True)
+    root.add_argument("--result", type=Path)
+    root.add_argument("--geometry", type=Path)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--failure-kind")
+    root.add_argument("--inner-surface", type=float, default=0.25)
+    root.add_argument("--outer-surface", type=float, default=0.6)
+    root.add_argument("--particles-per-surface", type=int, default=1024)
+    root.add_argument("--prompt-limit", type=float, default=0.05)
+    root.add_argument("--objective", choices=OBJECTIVES, default="barrier-jpar")
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    request = json.loads(args.request.read_text())
+    if args.failure_kind:
+        response = base_response(request, "failed", args.failure_kind)
+    else:
+        if args.result is None or args.geometry is None:
+            raise ValueError("successful response requires barrier and geometry results")
+        response = successful_response(
+            request,
+            json.loads(args.result.read_text()),
+            json.loads(args.geometry.read_text()),
+            objective=args.objective,
+            inner_surface=args.inner_surface,
+            outer_surface=args.outer_surface,
+            particles_per_surface=args.particles_per_surface,
+            prompt_limit=args.prompt_limit,
+        )
+    args.out.write_text(
+        json.dumps(response, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/build_direct_scbo_response.py b/build_direct_scbo_response.py
new file mode 100755
index 0000000..ccbfb77
--- /dev/null
+++ b/build_direct_scbo_response.py
@@ -0,0 +1,120 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+
+def jeffreys_variance(losses: int, particles: int) -> float:
+    if particles < 1 or not 0 <= losses <= particles:
+        raise ValueError("binomial counts are inconsistent")
+    alpha = losses + 0.5
+    beta = particles - losses + 0.5
+    total = alpha + beta
+    return float(alpha * beta / (total * total * (total + 1.0)))
+
+
+def base_response(request: dict, status: str, failure_kind: str | None) -> dict:
+    return {
+        "candidate_id": int(request["candidate_id"]),
+        "unit_x": [float(value) for value in request["unit_x"]],
+        "observation": None,
+        "status": status,
+        "failure_kind": failure_kind,
+    }
+
+
+def successful_response(
+    request: dict,
+    result: dict,
+    geometry: dict,
+    *,
+    particles: int,
+    seed: int,
+    birth_surface: float,
+    trace_time: float,
+) -> dict:
+    direct = result.get("direct", {})
+    expected = {
+        "particles": particles,
+        "seed": seed,
+        "birth_surface": birth_surface,
+        "trace_time": trace_time,
+    }
+    for key, value in expected.items():
+        if key not in result or not np.isclose(result[key], value):
+            raise ValueError(f"direct result has unexpected {key}")
+    total_count = int(direct["total_count"])
+    prompt_count = int(direct["prompt_count"])
+    late_count = int(direct["late_count"])
+    if total_count != prompt_count + late_count:
+        raise ValueError("direct loss windows do not partition total loss")
+    total_loss = float(direct["total_loss"])
+    if not np.isclose(total_loss, total_count / particles):
+        raise ValueError("direct total loss differs from the particle count")
+    constraints = [float(value) for value in geometry["constraints"]]
+    if geometry.get("schema_name") != "alpha-loss.direct-geometry":
+        raise ValueError("geometry document has an unexpected schema")
+    if len(constraints) != 2 or not np.isfinite(constraints).all():
+        raise ValueError("geometry constraints are incomplete")
+
+    response = base_response(request, "ok", None)
+    response["observation"] = {
+        "value": total_loss,
+        "variance": jeffreys_variance(total_count, particles),
+        "constraints": constraints,
+        "constraint_variances": [0.0, 0.0],
+    }
+    response["metrics"] = {
+        "objective_name": "direct_total_loss_fraction_100ms_s025",
+        "constraint_names": geometry["constraint_names"],
+        "constraint_limits": geometry["constraint_limits"],
+        "direct": direct,
+        "geometry": geometry["metrics"],
+        "geometry_feasible": bool(geometry["feasible"]),
+        "wout_sha256": result["wout_sha256"],
+    }
+    return response
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--request", type=Path, required=True)
+    root.add_argument("--result", type=Path)
+    root.add_argument("--geometry", type=Path)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--failure-kind")
+    root.add_argument("--particles", type=int, default=256)
+    root.add_argument("--seed", type=int, default=12345)
+    root.add_argument("--birth-surface", type=float, default=0.25)
+    root.add_argument("--trace-time", type=float, default=0.1)
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    request = json.loads(args.request.read_text())
+    if args.failure_kind:
+        response = base_response(request, "failed", args.failure_kind)
+    else:
+        if args.result is None or args.geometry is None:
+            raise ValueError("successful response requires direct and geometry results")
+        response = successful_response(
+            request,
+            json.loads(args.result.read_text()),
+            json.loads(args.geometry.read_text()),
+            particles=args.particles,
+            seed=args.seed,
+            birth_surface=args.birth_surface,
+            trace_time=args.trace_time,
+        )
+    args.out.write_text(
+        json.dumps(response, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/convert_boozer_chartmap.py b/convert_boozer_chartmap.py
new file mode 100644
index 0000000..1ea5120
--- /dev/null
+++ b/convert_boozer_chartmap.py
@@ -0,0 +1,17 @@
+#!/usr/bin/env python3
+import argparse
+from pathlib import Path
+
+from spatial_grid import write_compatible_chartmap
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--source", type=Path, required=True)
+    root.add_argument("--out", type=Path, required=True)
+    return root
+
+
+if __name__ == "__main__":
+    args = parser().parse_args()
+    write_compatible_chartmap(args.source.resolve(), args.out.resolve())
diff --git a/data_informed_surface.py b/data_informed_surface.py
new file mode 100644
index 0000000..7bdcb43
--- /dev/null
+++ b/data_informed_surface.py
@@ -0,0 +1,322 @@
+from __future__ import annotations
+
+import hashlib
+from dataclasses import dataclass
+from pathlib import Path
+
+import h5py
+import numpy as np
+from scipy import optimize
+from weightedpca import WeightedPCA, WeightedQuantileTransformer
+
+
+@dataclass(frozen=True, slots=True)
+class WeightedSurfaceTransform:
+    n_theta: int
+    n_phi: int
+    mean: np.ndarray
+    components: np.ndarray
+    references: np.ndarray
+    quantiles: np.ndarray
+    explained_variance: np.ndarray
+    source_sha256: str
+
+    @property
+    def dimension(self) -> int:
+        return len(self.components)
+
+    def decode(self, unit: np.ndarray, margin: float = 0.0) -> np.ndarray:
+        values = _unit_values(unit, self.dimension, margin)
+        probabilities = margin + (1.0 - 2.0 * margin) * values
+        scores = np.array(
+            [
+                np.interp(probabilities[index], self.references, self.quantiles[:, index])
+                for index in range(self.dimension)
+            ]
+        )
+        return self.mean + scores @ self.components
+
+    def encode(self, real_space: np.ndarray, margin: float = 0.0) -> np.ndarray:
+        values = np.asarray(real_space, dtype=float)
+        if values.shape != self.mean.shape or not np.isfinite(values).all():
+            raise ValueError("real-space surface vector has the wrong shape")
+        scores = (values - self.mean) @ self.components.T
+        probabilities = np.array(
+            [
+                np.interp(scores[index], self.quantiles[:, index], self.references)
+                for index in range(self.dimension)
+            ]
+        )
+        unit = (probabilities - margin) / (1.0 - 2.0 * margin)
+        if np.any((unit < 0.0) | (unit > 1.0)):
+            raise ValueError("surface lies outside the quantile margin")
+        return unit
+
+    def decode_anchored(
+        self, unit: np.ndarray, anchor: np.ndarray, margin: float = 0.0
+    ) -> np.ndarray:
+        values = _unit_values(unit, self.dimension, margin)
+        base = _real_space_values(anchor, self.mean.shape)
+        probabilities = margin + (1.0 - 2.0 * margin) * values
+        scores = _interpolate_columns(probabilities, self.references, self.quantiles)
+        medians = _interpolate_columns(
+            np.full(self.dimension, 0.5), self.references, self.quantiles
+        )
+        return base + (scores - medians) @ self.components
+
+    def encode_anchored(
+        self, real_space: np.ndarray, anchor: np.ndarray, margin: float = 0.0
+    ) -> np.ndarray:
+        values = _real_space_values(real_space, self.mean.shape)
+        base = _real_space_values(anchor, self.mean.shape)
+        delta_scores = (values - base) @ self.components.T
+        medians = _interpolate_columns(
+            np.full(self.dimension, 0.5), self.references, self.quantiles
+        )
+        probabilities = np.array(
+            [
+                np.interp(
+                    medians[index] + delta_scores[index],
+                    self.quantiles[:, index],
+                    self.references,
+                )
+                for index in range(self.dimension)
+            ]
+        )
+        unit = (probabilities - margin) / (1.0 - 2.0 * margin)
+        if np.any((unit < 0.0) | (unit > 1.0)):
+            raise ValueError("surface lies outside the anchored quantile margin")
+        return unit
+
+    def save(self, path: Path) -> None:
+        np.savez_compressed(
+            path,
+            n_theta=np.array(self.n_theta),
+            n_phi=np.array(self.n_phi),
+            mean=self.mean,
+            components=self.components,
+            references=self.references,
+            quantiles=self.quantiles,
+            explained_variance=self.explained_variance,
+            source_sha256=np.array(self.source_sha256),
+        )
+
+
+def fit_weighted_surface_transform(path: Path, dimension: int) -> WeightedSurfaceTransform:
+    source = Path(path)
+    with h5py.File(source, "r") as archive:
+        if not {"data", "weights", "n_theta", "n_phi"} <= set(archive):
+            raise ValueError("weighted surface data inventory is incomplete")
+        data = np.asarray(archive["data"], dtype=float)
+        weights = np.asarray(archive["weights"], dtype=float)
+        n_theta = int(archive["n_theta"][()])
+        n_phi = int(archive["n_phi"][()])
+    _validate_training_data(data, weights, n_theta, n_phi, dimension)
+    pca = WeightedPCA(dimension).fit(data, sample_weight=weights)
+    components = np.asarray(pca.components_, dtype=float).copy()
+    scores = (data - pca.mean_) @ components.T
+    quantile = WeightedQuantileTransformer(subsample=None).fit(
+        scores, sample_weight=weights
+    )
+    transform = WeightedSurfaceTransform(
+        n_theta,
+        n_phi,
+        np.asarray(pca.mean_, dtype=float),
+        components,
+        np.asarray(quantile.references_, dtype=float),
+        np.asarray(quantile.quantiles_, dtype=float),
+        np.asarray(pca.explained_variance_ratio_, dtype=float),
+        _file_sha256(source),
+    )
+    validate_transform(transform)
+    return transform
+
+
+def load_weighted_surface_transform(path: Path) -> WeightedSurfaceTransform:
+    with np.load(path, allow_pickle=False) as archive:
+        expected = {
+            "n_theta",
+            "n_phi",
+            "mean",
+            "components",
+            "references",
+            "quantiles",
+            "explained_variance",
+            "source_sha256",
+        }
+        if set(archive.files) != expected:
+            raise ValueError("weighted surface transform inventory differs")
+        transform = WeightedSurfaceTransform(
+            int(archive["n_theta"]),
+            int(archive["n_phi"]),
+            np.asarray(archive["mean"]),
+            np.asarray(archive["components"]),
+            np.asarray(archive["references"]),
+            np.asarray(archive["quantiles"]),
+            np.asarray(archive["explained_variance"]),
+            str(archive["source_sha256"]),
+        )
+    validate_transform(transform)
+    return transform
+
+
+def surface_from_unit(
+    transform: WeightedSurfaceTransform,
+    unit: np.ndarray,
+    *,
+    nfp: int,
+    major_radius: float,
+    minor_radius: float,
+    mpol: int = 6,
+    ntor: int = 6,
+    margin: float = 0.0,
+    exact_radii: bool = True,
+    anchor: np.ndarray | None = None,
+):
+    from simsopt.geo import SurfaceRZFourier
+
+    surface = SurfaceRZFourier.from_nphi_ntheta(
+        nfp=nfp,
+        mpol=mpol,
+        ntor=ntor,
+        range="half period",
+        ntheta=transform.n_theta,
+        nphi=transform.n_phi,
+    )
+    normalized = (
+        transform.decode(unit, margin)
+        if anchor is None
+        else transform.decode_anchored(unit, anchor, margin)
+    )
+    surface.least_squares_fit(_cartesian_grid(surface, normalized, major_radius, minor_radius))
+    if exact_radii:
+        _enforce_radii(surface, major_radius, minor_radius)
+    return surface
+
+
+def normalized_surface_grid(surface, transform: WeightedSurfaceTransform) -> np.ndarray:
+    from simsopt.geo import SurfaceRZFourier
+
+    grid = SurfaceRZFourier.from_nphi_ntheta(
+        nfp=surface.nfp,
+        mpol=surface.mpol,
+        ntor=surface.ntor,
+        range="half period",
+        ntheta=transform.n_theta,
+        nphi=transform.n_phi,
+    )
+    sampled = SurfaceRZFourier(
+        nfp=surface.nfp,
+        stellsym=surface.stellsym,
+        mpol=surface.mpol,
+        ntor=surface.ntor,
+        quadpoints_phi=grid.quadpoints_phi,
+        quadpoints_theta=grid.quadpoints_theta,
+        dofs=surface.dofs,
+    )
+    gamma = sampled.gamma()
+    radius = np.hypot(gamma[:, :, 0], gamma[:, :, 1])
+    major = surface.major_radius()
+    minor = surface.minor_radius()
+    return np.concatenate(
+        (((radius - major) / minor).ravel(), (gamma[:, :, 2] / minor).ravel())
+    )
+
+
+def validate_transform(transform: WeightedSurfaceTransform) -> None:
+    size = 2 * transform.n_theta * transform.n_phi
+    if (
+        min(transform.n_theta, transform.n_phi, transform.dimension) < 1
+        or transform.mean.shape != (size,)
+        or transform.components.shape != (transform.dimension, size)
+        or transform.quantiles.shape != (len(transform.references), transform.dimension)
+        or transform.explained_variance.shape != (transform.dimension,)
+        or len(transform.source_sha256) != 64
+    ):
+        raise ValueError("weighted surface transform shapes differ")
+    arrays = (
+        transform.mean,
+        transform.components,
+        transform.references,
+        transform.quantiles,
+        transform.explained_variance,
+    )
+    if not all(np.isfinite(value).all() for value in arrays):
+        raise ValueError("weighted surface transform contains nonfinite values")
+    if np.any(np.diff(transform.references) <= 0.0) or np.any(
+        np.diff(transform.quantiles, axis=0) < 0.0
+    ):
+        raise ValueError("weighted surface quantiles are not monotone")
+    np.testing.assert_allclose(
+        transform.components @ transform.components.T,
+        np.eye(transform.dimension),
+        rtol=0.0,
+        atol=1.0e-12,
+    )
+
+
+def _validate_training_data(data, weights, n_theta, n_phi, dimension) -> None:
+    if (
+        data.ndim != 2
+        or data.shape[1] != 2 * n_theta * n_phi
+        or weights.shape != (len(data),)
+        or not np.isfinite(data).all()
+        or not np.isfinite(weights).all()
+        or np.any(weights <= 0.0)
+        or not 1 <= dimension <= min(data.shape)
+    ):
+        raise ValueError("weighted surface training data are invalid")
+
+
+def _unit_values(unit, dimension, margin) -> np.ndarray:
+    values = np.asarray(unit, dtype=float)
+    if (
+        values.shape != (dimension,)
+        or not np.isfinite(values).all()
+        or np.any((values < 0.0) | (values > 1.0))
+        or not 0.0 <= margin < 0.5
+    ):
+        raise ValueError("surface coordinates or quantile margin are invalid")
+    return values
+
+
+def _real_space_values(values, shape) -> np.ndarray:
+    array = np.asarray(values, dtype=float)
+    if array.shape != shape or not np.isfinite(array).all():
+        raise ValueError("real-space surface vector has the wrong shape")
+    return array
+
+
+def _interpolate_columns(values, references, quantiles) -> np.ndarray:
+    return np.array(
+        [
+            np.interp(values[index], references, quantiles[:, index])
+            for index in range(len(values))
+        ]
+    )
+
+
+def _cartesian_grid(surface, normalized, major, minor) -> np.ndarray:
+    count = surface.quadpoints_phi.size * surface.quadpoints_theta.size
+    radius = normalized[:count].reshape((surface.quadpoints_phi.size, -1)) * minor + major
+    vertical = normalized[count:].reshape((surface.quadpoints_phi.size, -1)) * minor
+    angle = 2.0 * np.pi * surface.quadpoints_phi[:, None]
+    return np.stack((radius * np.cos(angle), radius * np.sin(angle), vertical), axis=2)
+
+
+def _enforce_radii(surface, major_radius: float, minor_radius: float) -> None:
+    target_aspect = major_radius / minor_radius
+
+    def residual(value):
+        dofs = surface.x.copy()
+        dofs[0] = value
+        surface.x = dofs
+        return surface.aspect_ratio() - target_aspect
+
+    root = optimize.newton(residual, x0=major_radius)
+    residual(root)
+    surface.x = surface.x * (minor_radius / surface.minor_radius())
+
+
+def _file_sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
diff --git a/evaluate_barrier_overlap.py b/evaluate_barrier_overlap.py
new file mode 100644
index 0000000..7bc9e4c
--- /dev/null
+++ b/evaluate_barrier_overlap.py
@@ -0,0 +1,82 @@
+#!/usr/bin/env python3
+"""Evaluate continuous fast-classifier metrics for one equilibrium."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+from barrier_overlap import barrier_metrics, file_sha256
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--wout", type=Path, required=True)
+    root.add_argument("--wout-sha256", required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--simple-executable", type=Path, required=True)
+    root.add_argument("--simple-sha256", required=True)
+    root.add_argument("--work-root", type=Path)
+    root.add_argument("--surfaces", default="0.25,0.4,0.55,0.7")
+    root.add_argument("--ntheta", type=int, default=8)
+    root.add_argument("--nzeta", type=int, default=8)
+    root.add_argument("--npitch", type=int, default=16)
+    root.add_argument("--pitch-max", type=float, default=1.0)
+    root.add_argument("--mu-nodes", type=int, default=24)
+    root.add_argument("--trace-time", type=float, default=0.02)
+    root.add_argument("--prompt-time", type=float, default=0.001)
+    root.add_argument("--nturns", type=int, default=8)
+    root.add_argument("--seed", type=int, default=12345)
+    root.add_argument("--trapped-width", type=float, default=0.15)
+    root.add_argument("--mu-width-factor", type=float, default=0.75)
+    root.add_argument("--jpar-temperature", type=float, default=0.1)
+    root.add_argument("--rotation-temperature", type=float, default=0.02)
+    root.add_argument("--timeout", type=float, default=3600.0)
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    surfaces = [float(value) for value in args.surfaces.split(",") if value.strip()]
+    wout = args.wout.resolve()
+    observed = file_sha256(wout)
+    if observed != args.wout_sha256:
+        raise ValueError("wout hash does not match the scheduled candidate")
+    metrics = barrier_metrics(
+        wout,
+        expected_simple_sha256=args.simple_sha256,
+        surfaces=surfaces,
+        ntheta=args.ntheta,
+        nzeta=args.nzeta,
+        npitch=args.npitch,
+        pitch_max=args.pitch_max,
+        nmu=args.mu_nodes,
+        trace_time=args.trace_time,
+        prompt_time=args.prompt_time,
+        nturns=args.nturns,
+        seed=args.seed,
+        continuous_settings={
+            "trapped_width": args.trapped_width,
+            "mu_width_factor": args.mu_width_factor,
+            "temperature_jpar": args.jpar_temperature,
+            "temperature_rotation": args.rotation_temperature,
+        },
+        simple_executable=args.simple_executable,
+        work_root=args.work_root,
+        timeout_s=args.timeout,
+    )
+    args.out.mkdir(parents=True, exist_ok=True)
+    document = {
+        "schema_name": "alpha-loss.continuous-fast-classifier-result",
+        "schema_version": 2,
+        "barrier": metrics,
+        "wout_sha256": observed,
+    }
+    (args.out / "result.json").write_text(
+        json.dumps(document, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evaluate_direct_loss.py b/evaluate_direct_loss.py
new file mode 100644
index 0000000..761c43e
--- /dev/null
+++ b/evaluate_direct_loss.py
@@ -0,0 +1,83 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+import shutil
+from pathlib import Path
+
+import simple_direct
+from execution_record import write_execution_record
+
+
+def evaluate(args: argparse.Namespace) -> None:
+    if args.particles <= 0:
+        raise ValueError("particles must be positive")
+    if not 0.0 < args.birth_surface < 1.0:
+        raise ValueError("birth surface must satisfy 0 < s < 1")
+    if not 0.0 < args.prompt_time < args.trace_time:
+        raise ValueError("loss windows must satisfy 0 < prompt < trace")
+    executable = args.simple_executable.resolve()
+    executable_hash = simple_direct.file_sha256(executable)
+    if executable_hash != args.simple_sha256:
+        raise ValueError(f"unexpected SIMPLE executable hash {executable_hash}")
+    wout = args.wout.resolve()
+    wout_hash = simple_direct.file_sha256(wout)
+    if wout_hash != args.wout_sha256:
+        raise ValueError(f"unexpected equilibrium hash {wout_hash}")
+    output = args.out.resolve()
+    output.mkdir(parents=True, exist_ok=False)
+    metrics = simple_direct.direct_loss_metrics(
+        wout,
+        ntestpart=args.particles,
+        expected_simple_sha256=executable_hash,
+        trace_time=args.trace_time,
+        prompt_time=args.prompt_time,
+        sbeg=args.birth_surface,
+        seed=args.seed,
+        simple_executable=executable,
+        keep_workdir=True,
+        timeout_s=args.timeout,
+    )
+    workdir = Path(str(metrics.pop("workdir")))
+    direct = output / "direct"
+    shutil.move(str(workdir), direct)
+    write_execution_record(direct, executable, executable_hash, wout_hash, args.seed)
+    result = {
+        "status": "ok",
+        "wout_sha256": wout_hash,
+        "simple_sha256": executable_hash,
+        "particles": args.particles,
+        "seed": args.seed,
+        "birth_surface": args.birth_surface,
+        "prompt_time": args.prompt_time,
+        "trace_time": args.trace_time,
+        "direct": metrics,
+    }
+    (output / "result.json").write_text(
+        json.dumps(result, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--wout", type=Path, required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--simple-executable", type=Path, required=True)
+    root.add_argument("--simple-sha256", required=True)
+    root.add_argument("--wout-sha256", required=True)
+    root.add_argument("--particles", type=int, default=256)
+    root.add_argument("--seed", type=int, default=12345)
+    root.add_argument("--birth-surface", type=float, default=0.25)
+    root.add_argument("--prompt-time", type=float, default=1.0e-3)
+    root.add_argument("--trace-time", type=float, default=1.0e-1)
+    root.add_argument("--timeout", type=float, default=900.0)
+    return root
+
+
+def main() -> None:
+    evaluate(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/evaluate_vmec_geometry.py b/evaluate_vmec_geometry.py
new file mode 100755
index 0000000..1646da6
--- /dev/null
+++ b/evaluate_vmec_geometry.py
@@ -0,0 +1,71 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+from Alan_objectives import MaxElongationPen, MirrorRatioPen
+
+
+def evaluate(
+    wout: Path,
+    *,
+    mirror_limit: float = 0.20,
+    elongation_limit: float = 6.0,
+) -> dict:
+    from simsopt.mhd import Vmec
+
+    if not 0.0 < mirror_limit < 1.0 or elongation_limit <= 1.0:
+        raise ValueError("geometry limits are outside their physical ranges")
+    vmec = Vmec(str(wout.resolve()), verbose=False)
+    metrics = {
+        "aspect": float(vmec.aspect()),
+        "mean_iota": float(vmec.mean_iota()),
+        "vacuum_well": float(vmec.vacuum_well()),
+        "mirror_ratio": float(MirrorRatioPen(v=vmec, output_mirror=True)),
+        "max_elongation": float(MaxElongationPen(vmec=vmec, return_elongation=True)),
+    }
+    if not np.isfinite(list(metrics.values())).all():
+        raise ValueError("VMEC geometry metrics must be finite")
+    constraints = [
+        metrics["mirror_ratio"] / mirror_limit - 1.0,
+        metrics["max_elongation"] / elongation_limit - 1.0,
+    ]
+    return {
+        "schema_name": "alpha-loss.direct-geometry",
+        "schema_version": 1,
+        "wout": str(wout.resolve()),
+        "metrics": metrics,
+        "constraint_names": ["mirror_ratio", "max_elongation"],
+        "constraint_limits": [mirror_limit, elongation_limit],
+        "constraints": constraints,
+        "feasible": bool(max(constraints) <= 0.0),
+    }
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--wout", type=Path, required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--mirror-limit", type=float, default=0.20)
+    root.add_argument("--elongation-limit", type=float, default=6.0)
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    document = evaluate(
+        args.wout,
+        mirror_limit=args.mirror_limit,
+        elongation_limit=args.elongation_limit,
+    )
+    args.out.write_text(
+        json.dumps(document, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/execution_record.py b/execution_record.py
new file mode 100644
index 0000000..ee2decd
--- /dev/null
+++ b/execution_record.py
@@ -0,0 +1,30 @@
+from __future__ import annotations
+
+import os
+import socket
+from datetime import datetime, timezone
+from pathlib import Path
+
+from simple_direct import file_sha256
+
+
+def write_execution_record(
+    run: Path,
+    executable: Path,
+    executable_hash: str,
+    wout_hash: str,
+    seed: int,
+) -> None:
+    input_hash = file_sha256(run / "simple.in")
+    (run / "output_checksums.txt").write_text(
+        f"{executable_hash}  {executable}\n"
+        f"{wout_hash}  wout.nc\n"
+        f"{input_hash}  simple.in\n"
+    )
+    (run / "execution.txt").write_text(
+        f"simple_bin={executable}\n"
+        f"host={socket.gethostname()}\n"
+        f"slurm_job={os.environ.get('SLURM_JOB_ID', '')}\n"
+        f"seed={seed}\n"
+        f"completed={datetime.now(timezone.utc).astimezone().isoformat()}\n"
+    )
diff --git a/fit_data_informed_charts.py b/fit_data_informed_charts.py
new file mode 100644
index 0000000..0603715
--- /dev/null
+++ b/fit_data_informed_charts.py
@@ -0,0 +1,176 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+from pathlib import Path
+
+import h5py
+import numpy as np
+from scipy.stats import qmc
+
+from data_informed_surface import (
+    fit_weighted_surface_transform,
+    normalized_surface_grid,
+    surface_from_unit,
+)
+
+WEIGHTEDPCA_COMMIT = "6c7b83dd6b245f14dbdbb8abeff70f62f75ec8d8"
+
+
+def fit(args: argparse.Namespace) -> None:
+    from simsopt.mhd import Vmec
+
+    output = args.out.resolve()
+    output.mkdir(parents=True, exist_ok=False)
+    base = Vmec(str(args.base_input.resolve()), verbose=False).boundary
+    source_inventory = _source_inventory(args.source)
+    charts = []
+    for dimension in args.dimensions:
+        transform = fit_weighted_surface_transform(args.source, dimension)
+        anchor = normalized_surface_grid(base, transform)
+        sidecar = output / f"weighted-pca-d{dimension}.npz"
+        transform.save(sidecar)
+        audit = _audit(transform, anchor, base, args, dimension)
+        charts.append(
+            {
+                "dimension": dimension,
+                "explained_variance_fraction": float(
+                    np.sum(transform.explained_variance)
+                ),
+                "sidecar": sidecar.name,
+                "sidecar_sha256": _file_sha256(sidecar),
+                **audit,
+            }
+        )
+    manifest = {
+        "schema_name": "alpha-loss.data-informed-charts",
+        "schema_version": 1,
+        "method": "Landreman weighted real-space PCA and inverse marginal quantiles",
+        "adaptation": "quantile displacements anchored at the ALPES reference",
+        "weightedpca_commit": WEIGHTEDPCA_COMMIT,
+        "source": source_inventory,
+        "base_input_sha256": _file_sha256(args.base_input),
+        "nfp": base.nfp,
+        "stellarator_symmetry": base.stellsym,
+        "major_radius": base.major_radius(),
+        "minor_radius": base.minor_radius(),
+        "mpol": args.mpol,
+        "ntor": args.ntor,
+        "quantile_margin": args.margin,
+        "sobol_seed": args.seed,
+        "sobol_points": 2**args.audit_power,
+        "charts": charts,
+    }
+    (output / "manifest.json").write_text(
+        json.dumps(manifest, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+def _audit(transform, anchor, base, args, dimension) -> dict[str, float | int]:
+    center = surface_from_unit(
+        transform,
+        np.full(dimension, 0.5),
+        nfp=base.nfp,
+        major_radius=base.major_radius(),
+        minor_radius=base.minor_radius(),
+        mpol=args.mpol,
+        ntor=args.ntor,
+        margin=args.margin,
+        anchor=anchor,
+    )
+    error = _surface_error(center, base) / base.minor_radius()
+    points = qmc.Sobol(dimension, scramble=True, seed=args.seed).random_base2(
+        args.audit_power
+    )
+    usable = sum(_usable(transform, anchor, base, point, args) for point in points)
+    return {
+        "reference_max_point_error_over_a": error,
+        "analytic_usable": usable,
+        "analytic_usable_fraction": usable / len(points),
+    }
+
+
+def _usable(transform, anchor, base, point, args) -> int:
+    try:
+        surface = surface_from_unit(
+            transform,
+            point,
+            nfp=base.nfp,
+            major_radius=base.major_radius(),
+            minor_radius=base.minor_radius(),
+            mpol=args.mpol,
+            ntor=args.ntor,
+            margin=args.margin,
+            anchor=anchor,
+        )
+        return int(not surface.is_self_intersecting())
+    except (RuntimeError, ValueError):
+        return 0
+
+
+def _surface_error(first, second) -> float:
+    from simsopt.geo import SurfaceRZFourier
+
+    grid = SurfaceRZFourier.from_nphi_ntheta(
+        nfp=first.nfp,
+        mpol=max(first.mpol, second.mpol),
+        ntor=max(first.ntor, second.ntor),
+        range="half period",
+        nphi=64,
+        ntheta=128,
+    )
+    values = []
+    for surface in (first, second):
+        sampled = SurfaceRZFourier(
+            nfp=surface.nfp,
+            stellsym=surface.stellsym,
+            mpol=surface.mpol,
+            ntor=surface.ntor,
+            quadpoints_phi=grid.quadpoints_phi,
+            quadpoints_theta=grid.quadpoints_theta,
+            dofs=surface.dofs,
+        )
+        values.append(sampled.gamma())
+    return float(np.max(np.linalg.norm(values[0] - values[1], axis=2)))
+
+
+def _source_inventory(path: Path) -> dict[str, object]:
+    with h5py.File(path, "r") as archive:
+        return {
+            "file": path.name,
+            "sha256": _file_sha256(path),
+            "rows": int(archive["data"].shape[0]),
+            "real_space_dimension": int(archive["data"].shape[1]),
+            "n_kappel": int(archive["n_Kappel"][()]),
+            "n_quasr": int(archive["n_QUASR"][()]),
+            "n_constellaration": int(archive["n_constellaration"][()]),
+            "weight_sum": float(np.sum(archive["weights"][()])),
+        }
+
+
+def _file_sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--source", type=Path, required=True)
+    root.add_argument("--base-input", type=Path, required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--dimensions", type=int, nargs="+", default=(8, 12, 16))
+    root.add_argument("--margin", type=float, default=0.1)
+    root.add_argument("--mpol", type=int, default=9)
+    root.add_argument("--ntor", type=int, default=6)
+    root.add_argument("--audit-power", type=int, default=8)
+    root.add_argument("--seed", type=int, default=20260713)
+    return root
+
+
+def main() -> None:
+    fit(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/generate_scbo_candidates.py b/generate_scbo_candidates.py
new file mode 100644
index 0000000..515aa9c
--- /dev/null
+++ b/generate_scbo_candidates.py
@@ -0,0 +1,130 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+from data_informed_surface import (
+    load_weighted_surface_transform,
+    normalized_surface_grid,
+    surface_from_unit,
+)
+from generate_vmec_audit_inputs import file_sha256, normalize_vmec_input
+
+
+def generate(args: argparse.Namespace) -> None:
+    from simsopt.mhd import Vmec
+
+    output = args.out.resolve()
+    output.mkdir(parents=True, exist_ok=False)
+    transform = load_weighted_surface_transform(args.transform.resolve())
+    requests = load_requests(args.requests, transform.dimension)
+    vmec = Vmec(str(args.base_input.resolve()), verbose=False)
+    base = vmec.boundary
+    anchor = normalized_surface_grid(base, transform)
+    major_radius = base.major_radius()
+    minor_radius = base.minor_radius()
+    fixed = (base.nfp, major_radius, minor_radius)
+    cases = [
+        generate_case(vmec, transform, anchor, request, args, output, fixed)
+        for request in requests
+    ]
+    manifest = {
+        "schema_name": "alpha-loss.scbo-candidate-wave",
+        "schema_version": 1,
+        "base_input_sha256": file_sha256(args.base_input),
+        "transform_sha256": file_sha256(args.transform),
+        "quantile_margin": args.margin,
+        "mpol": args.mpol,
+        "ntor": args.ntor,
+        "cases": cases,
+    }
+    (output / "manifest.json").write_text(
+        json.dumps(manifest, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+def generate_case(vmec, transform, anchor, request, args, output, fixed):
+    candidate_id = request["candidate_id"]
+    name = f"candidate-{candidate_id:08d}"
+    unit = np.asarray(request["unit_x"], dtype=float)
+    nfp, major_radius, minor_radius = fixed
+    surface = surface_from_unit(
+        transform,
+        unit,
+        nfp=nfp,
+        major_radius=major_radius,
+        minor_radius=minor_radius,
+        mpol=args.mpol,
+        ntor=args.ntor,
+        margin=args.margin,
+        anchor=anchor,
+    )
+    case = output / name
+    case.mkdir()
+    record = {"candidate_id": candidate_id, "unit_x": unit.tolist(), "case": name}
+    if "generation" in request:
+        record["generation"] = int(request["generation"])
+    (case / "request.json").write_text(
+        json.dumps(record, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+    if surface.is_self_intersecting():
+        record.update({"status": "failed", "failure_kind": "self_intersection"})
+        return record
+    vmec.boundary.x = surface.x
+    input_path = case / f"input.{name}"
+    vmec.write_input(str(input_path))
+    normalize_vmec_input(input_path)
+    record.update(
+        {
+            "status": "ready",
+            "input": str(input_path.relative_to(output)),
+            "input_sha256": file_sha256(input_path),
+        }
+    )
+    return record
+
+
+def load_requests(path: Path, dimension: int) -> list[dict]:
+    document = json.loads(Path(path).read_text())
+    rows = document["requests"] if isinstance(document, dict) else document
+    ids = [int(row["candidate_id"]) for row in rows]
+    if len(set(ids)) != len(ids) or ids != sorted(ids):
+        raise ValueError("SCBO request candidate IDs must be unique and ordered")
+    requests = []
+    for candidate_id, row in zip(ids, rows, strict=True):
+        unit = np.asarray(row["unit_x"], dtype=float)
+        if (
+            unit.shape != (dimension,)
+            or not np.isfinite(unit).all()
+            or np.any((unit < 0.0) | (unit > 1.0))
+        ):
+            raise ValueError("SCBO request coordinates differ from the chart")
+        request = {"candidate_id": candidate_id, "unit_x": unit.tolist()}
+        if "generation" in row:
+            request["generation"] = int(row["generation"])
+        requests.append(request)
+    return requests
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--base-input", type=Path, required=True)
+    root.add_argument("--transform", type=Path, required=True)
+    root.add_argument("--requests", type=Path, required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--margin", type=float, default=0.35)
+    root.add_argument("--mpol", type=int, default=9)
+    root.add_argument("--ntor", type=int, default=6)
+    return root
+
+
+def main() -> None:
+    generate(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/generate_vmec_audit_inputs.py b/generate_vmec_audit_inputs.py
new file mode 100644
index 0000000..3402baa
--- /dev/null
+++ b/generate_vmec_audit_inputs.py
@@ -0,0 +1,133 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+from pathlib import Path
+
+import numpy as np
+from scipy.stats import qmc
+
+from data_informed_surface import (
+    load_weighted_surface_transform,
+    normalized_surface_grid,
+    surface_from_unit,
+)
+
+
+def generate(args: argparse.Namespace) -> None:
+    from simsopt.mhd import Vmec
+
+    output = args.out.resolve()
+    output.mkdir(parents=True, exist_ok=False)
+    base_input = args.base_input.resolve()
+    vmec = Vmec(str(base_input), verbose=False)
+    base = vmec.boundary
+    base_dofs = base.x.copy()
+    nfp = base.nfp
+    major_radius = base.major_radius()
+    minor_radius = base.minor_radius()
+    cases = []
+    for sidecar in args.transforms:
+        transform = load_weighted_surface_transform(sidecar.resolve())
+        base.x = base_dofs
+        anchor = normalized_surface_grid(base, transform)
+        for name, dimension, index, unit in case_specs(
+            transform.dimension, args.audit_power, args.seed
+        ):
+            surface = surface_from_unit(
+                transform,
+                unit,
+                nfp=nfp,
+                major_radius=major_radius,
+                minor_radius=minor_radius,
+                mpol=args.mpol,
+                ntor=args.ntor,
+                margin=args.margin,
+                anchor=anchor,
+            )
+            if surface.is_self_intersecting():
+                raise RuntimeError(f"analytic audit changed for {name}")
+            vmec.boundary.x = surface.x
+            case = output / relative_case_path(dimension, index, name)
+            case.mkdir(parents=True)
+            input_path = case / f"input.{name}"
+            vmec.write_input(str(input_path))
+            normalize_vmec_input(input_path)
+            cases.append(
+                {
+                    "case": name,
+                    "dimension": dimension,
+                    "index": index,
+                    "unit": unit.tolist(),
+                    "input": str(input_path.relative_to(output)),
+                    "input_sha256": file_sha256(input_path),
+                    "transform": sidecar.name,
+                    "transform_sha256": file_sha256(sidecar),
+                }
+            )
+    manifest = {
+        "schema_name": "alpha-loss.vmec-chart-audit",
+        "schema_version": 1,
+        "base_input_sha256": file_sha256(base_input),
+        "sobol_seed": args.seed,
+        "sobol_points_per_chart": 2**args.audit_power,
+        "quantile_margin": args.margin,
+        "mpol": args.mpol,
+        "ntor": args.ntor,
+        "cases": cases,
+    }
+    (output / "manifest.json").write_text(
+        json.dumps(manifest, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+def case_specs(
+    dimension: int, audit_power: int, seed: int
+) -> list[tuple[str, int, int, np.ndarray]]:
+    if dimension < 1 or audit_power < 0:
+        raise ValueError("dimension and audit power are outside their ranges")
+    points = qmc.Sobol(dimension, scramble=True, seed=seed).random_base2(audit_power)
+    return [
+        (f"d{dimension:02d}_{index:03d}", dimension, index, point)
+        for index, point in enumerate(points)
+    ]
+
+
+def relative_case_path(dimension: int, index: int, name: str) -> Path:
+    return Path(f"d{dimension:02d}") / f"b{index // 32:02d}" / name
+
+
+def file_sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with Path(path).open("rb") as stream:
+        for block in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def normalize_vmec_input(path: Path) -> None:
+    lines = [line.rstrip() for line in Path(path).read_text().splitlines()]
+    Path(path).write_text("\n".join(lines).rstrip() + "\n")
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--base-input", type=Path, required=True)
+    root.add_argument("--transforms", type=Path, nargs="+", required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--margin", type=float, default=0.1)
+    root.add_argument("--mpol", type=int, default=9)
+    root.add_argument("--ntor", type=int, default=6)
+    root.add_argument("--audit-power", type=int, default=8)
+    root.add_argument("--seed", type=int, default=20260713)
+    return root
+
+
+def main() -> None:
+    generate(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/initial_configs/LICENSE.ALPES b/initial_configs/LICENSE.ALPES
new file mode 100644
index 0000000..cdfdc6f
--- /dev/null
+++ b/initial_configs/LICENSE.ALPES
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 The ALPES Team
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/initial_configs/LICENSE.QUASR b/initial_configs/LICENSE.QUASR
new file mode 100644
index 0000000..683f511
--- /dev/null
+++ b/initial_configs/LICENSE.QUASR
@@ -0,0 +1,28 @@
+MIT License
+
+Copyright (c) 2024 Andrew Giuliani
+
+This repository includes a VMEC input file derived from the QUASR dataset:
+
+- QUASR model: 0021326
+- Dataset: QUASR: the QUAsisymmetric Stellarator Repository
+- DOI: 10.5281/zenodo.10944430
+- License (Zenodo metadata): MIT
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/initial_configs/LICENSE.simsopt b/initial_configs/LICENSE.simsopt
new file mode 100644
index 0000000..9c839b9
--- /dev/null
+++ b/initial_configs/LICENSE.simsopt
@@ -0,0 +1,22 @@
+MIT License
+
+Copyright (c) 2023 Simsopt contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+
diff --git a/initial_configs/NOTICE.ALPES_QUASR_0021326 b/initial_configs/NOTICE.ALPES_QUASR_0021326
new file mode 100644
index 0000000..1646208
--- /dev/null
+++ b/initial_configs/NOTICE.ALPES_QUASR_0021326
@@ -0,0 +1,7 @@
+This directory includes `input.ALPES_QUASR_0021326_1`, a VMEC input file used
+in the ALPES project and originating from the QUASR database model 0021326.
+
+Sources:
+- ALPES repo: /home/ert/code/ALPES (MIT licensed, see LICENSE.ALPES)
+- QUASR model page: https://quasr.flatironinstitute.org/model/0021326
+- QUASR dataset DOI: 10.5281/zenodo.10944430 (MIT licensed, see LICENSE.QUASR)
diff --git a/initial_configs/input.ALPES_QUASR_0021326_1 b/initial_configs/input.ALPES_QUASR_0021326_1
new file mode 100644
index 0000000..646ec85
--- /dev/null
+++ b/initial_configs/input.ALPES_QUASR_0021326_1
@@ -0,0 +1,161 @@
+&INDATA
+! This file created by simsopt on July 05 2024, 12:36:45
+
+! ---- Geometric parameters ----
+NFP = 2
+LASYM = F
+
+! ---- Resolution parameters ----
+MPOL = 9
+NTOR = 6
+NTHETA = 24
+NZETA = 18
+NS_ARRAY    =     3
+NITER_ARRAY =  10000  10000  10000
+FTOL_ARRAY  =  2e-10
+
+! ---- Boundary toroidal flux ----
+PHIEDGE = 1.0
+
+! ---- Pressure profile specification ----
+PMASS_TYPE = "power_series"
+AM = 0.0 
+PRES_SCALE = 1.0
+
+! ---- Profile specification of iota or current ----
+NCURR = 1
+CURTOR = 0.0
+PCURR_TYPE = "power_series"
+AC = 0.0 
+
+! ---- Other numerical parameters ----
+DELT = 0.9
+NSTEP = 200
+
+! ---- Boundary shape. Array index order is (n, m) ----
+RBC(   0,   0) =  1.037482275701635e+00,    ZBS(   0,   0) =  0.000000000000000e+00
+RBC(   1,   0) =  9.339693406918478e-02,    ZBS(   1,   0) =  1.069486882814592e-01
+RBC(   2,   0) =  5.509584053807044e-03,    ZBS(   2,   0) =  5.958378221101873e-03
+RBC(   3,   0) =  5.403840802194012e-04,    ZBS(   3,   0) =  3.909731871350326e-04
+RBC(   4,   0) =  4.286336049475691e-04,    ZBS(   4,   0) =  1.836273432603913e-04
+RBC(   5,   0) =  5.135928586887884e-04,    ZBS(   5,   0) = -2.210132103377411e-04
+RBC(   6,   0) =  1.406773113755671e-03,    ZBS(   6,   0) = -2.349746833339385e-04
+RBC(  -6,   1) = -6.637042462103116e-04,    ZBS(  -6,   1) =  2.496545495837565e-04
+RBC(  -5,   1) =  9.120740506180424e-04,    ZBS(  -5,   1) =  1.042873602963963e-03
+RBC(  -4,   1) =  5.994487051061747e-04,    ZBS(  -4,   1) =  8.170446669257006e-04
+RBC(  -3,   1) =  4.141747404217256e-04,    ZBS(  -3,   1) =  7.527716068322473e-04
+RBC(  -2,   1) = -1.508370195330564e-03,    ZBS(  -2,   1) =  2.264661119326507e-03
+RBC(  -1,   1) = -2.179730462757535e-02,    ZBS(  -1,   1) =  2.022522748373621e-02
+RBC(   0,   1) = -2.829820432639614e-01,    ZBS(   0,   1) =  2.445230714555625e-01
+RBC(   1,   1) =  9.766553383675308e-02,    ZBS(   1,   1) =  6.200772022022946e-02
+RBC(   2,   1) =  1.398834499950336e-02,    ZBS(   2,   1) =  1.308029896994436e-02
+RBC(   3,   1) =  1.417983940738847e-03,    ZBS(   3,   1) =  1.462448347128497e-03
+RBC(   4,   1) = -6.378023658286113e-05,    ZBS(   4,   1) =  1.244101982355371e-04
+RBC(   5,   1) =  7.535874600360025e-06,    ZBS(   5,   1) = -1.683114299846660e-05
+RBC(   6,   1) = -4.740071147219712e-04,    ZBS(   6,   1) =  4.383907677715318e-04
+RBC(  -6,   2) =  2.633328262211147e-04,    ZBS(  -6,   2) = -2.773557356441214e-04
+RBC(  -5,   2) =  6.144575796877927e-05,    ZBS(  -5,   2) =  1.296634652237609e-04
+RBC(  -4,   2) =  1.844038433158538e-04,    ZBS(  -4,   2) =  1.822812338316488e-04
+RBC(  -3,   2) =  3.770907230560651e-04,    ZBS(  -3,   2) =  4.970336413033421e-04
+RBC(  -2,   2) = -7.458647344724807e-05,    ZBS(  -2,   2) =  1.061389377796316e-03
+RBC(  -1,   2) = -4.434998189227216e-03,    ZBS(  -1,   2) =  5.318547129057076e-03
+RBC(   0,   2) = -5.673500379888089e-02,    ZBS(   0,   2) =  3.634067864772867e-02
+RBC(   1,   2) =  4.706523409326446e-02,    ZBS(   1,   2) =  3.395638824280155e-02
+RBC(   2,   2) =  1.442606385375100e-02,    ZBS(   2,   2) =  1.282655785310807e-02
+RBC(   3,   2) =  2.774669479569761e-03,    ZBS(   3,   2) =  2.701238358797072e-03
+RBC(   4,   2) =  4.002554910364133e-04,    ZBS(   4,   2) =  4.169697161773624e-04
+RBC(   5,   2) =  2.527020285792371e-05,    ZBS(   5,   2) =  3.189412760277275e-05
+RBC(   6,   2) = -1.042253828412319e-04,    ZBS(   6,   2) = -2.439235617789694e-05
+RBC(  -6,   3) =  1.004716772161850e-04,    ZBS(  -6,   3) =  1.567325141978609e-05
+RBC(  -5,   3) =  1.771152992406636e-04,    ZBS(  -5,   3) = -1.622321603232918e-04
+RBC(  -4,   3) = -3.870324961766302e-04,    ZBS(  -4,   3) = -6.275067892263844e-04
+RBC(  -3,   3) = -2.912333474326158e-04,    ZBS(  -3,   3) = -4.468472951307841e-04
+RBC(  -2,   3) = -4.027490043353972e-04,    ZBS(  -2,   3) = -9.817379698945697e-05
+RBC(  -1,   3) = -1.960415417197040e-03,    ZBS(  -1,   3) =  1.388945900887780e-03
+RBC(   0,   3) = -1.516325604648303e-02,    ZBS(   0,   3) =  7.568834538602634e-03
+RBC(   1,   3) =  1.985438821855766e-02,    ZBS(   1,   3) =  1.699205891974218e-02
+RBC(   2,   3) =  9.750456442663466e-03,    ZBS(   2,   3) =  8.639922921450591e-03
+RBC(   3,   3) =  2.282439879103958e-03,    ZBS(   3,   3) =  2.242182458273002e-03
+RBC(   4,   3) =  4.537267649331738e-04,    ZBS(   4,   3) =  5.210534011552982e-04
+RBC(   5,   3) =  4.951832688858445e-05,    ZBS(   5,   3) =  9.339883731926644e-05
+RBC(   6,   3) = -1.160518421007308e-04,    ZBS(   6,   3) =  8.053611007900234e-05
+RBC(  -6,   4) =  4.362913485189504e-05,    ZBS(  -6,   4) =  4.517237422141926e-05
+RBC(  -5,   4) =  7.192336291306456e-05,    ZBS(  -5,   4) = -5.286102364207326e-05
+RBC(  -4,   4) = -4.675178580161597e-04,    ZBS(  -4,   4) = -5.424911346438898e-04
+RBC(  -3,   4) = -3.451755808527939e-04,    ZBS(  -3,   4) = -4.242815388371704e-04
+RBC(  -2,   4) = -3.522868015368525e-04,    ZBS(  -2,   4) = -2.587699493069896e-04
+RBC(  -1,   4) = -9.220559505361694e-04,    ZBS(  -1,   4) =  2.031556596781286e-04
+RBC(   0,   4) = -4.540157214266849e-03,    ZBS(   0,   4) =  1.345686660848236e-03
+RBC(   1,   4) =  7.819065364125560e-03,    ZBS(   1,   4) =  8.119374355771099e-03
+RBC(   2,   4) =  6.124012080131434e-03,    ZBS(   2,   4) =  5.523763739133167e-03
+RBC(   3,   4) =  1.671343017348709e-03,    ZBS(   3,   4) =  1.633828268354721e-03
+RBC(   4,   4) =  3.607141333552154e-04,    ZBS(   4,   4) =  3.993158654058775e-04
+RBC(   5,   4) =  5.938618848565332e-05,    ZBS(   5,   4) =  9.162550496808641e-05
+RBC(   6,   4) = -8.315736903611775e-05,    ZBS(   6,   4) =  9.530648681118248e-05
+RBC(  -6,   5) =  2.921915646010230e-05,    ZBS(  -6,   5) =  2.496658576584582e-05
+RBC(  -5,   5) =  2.858984479452007e-07,    ZBS(  -5,   5) = -7.903589487148170e-06
+RBC(  -4,   5) = -3.923707419189745e-04,    ZBS(  -4,   5) = -2.769905569336035e-04
+RBC(  -3,   5) = -1.936883381052368e-04,    ZBS(  -3,   5) = -1.540988603033603e-04
+RBC(  -2,   5) = -1.913229641014767e-04,    ZBS(  -2,   5) = -1.176043666508126e-04
+RBC(  -1,   5) = -4.144481613721851e-04,    ZBS(  -1,   5) = -2.107711292097974e-05
+RBC(   0,   5) = -1.493873855139403e-03,    ZBS(   0,   5) =  2.626336603599044e-05
+RBC(   1,   5) =  2.836874619832460e-03,    ZBS(   1,   5) =  3.704359033776406e-03
+RBC(   2,   5) =  3.607975982202313e-03,    ZBS(   2,   5) =  3.405003362402597e-03
+RBC(   3,   5) =  1.159891416140262e-03,    ZBS(   3,   5) =  1.144398974286070e-03
+RBC(   4,   5) =  2.359218806741565e-04,    ZBS(   4,   5) =  2.555133344923649e-04
+RBC(   5,   5) =  4.211570851279061e-05,    ZBS(   5,   5) =  5.895410044913843e-05
+RBC(   6,   5) = -4.795443968158398e-05,    ZBS(   6,   5) =  6.487299076315962e-05
+RBC(  -6,   6) =  1.866483782197583e-05,    ZBS(  -6,   6) =  1.060825234019053e-05
+RBC(  -5,   6) = -2.541689440665489e-05,    ZBS(  -5,   6) = -3.218430461088993e-06
+RBC(  -4,   6) = -2.680533181562642e-04,    ZBS(  -4,   6) = -1.080373049714992e-04
+RBC(  -3,   6) = -4.075735043307147e-05,    ZBS(  -3,   6) =  1.139939566806561e-05
+RBC(  -2,   6) = -6.375189434905038e-05,    ZBS(  -2,   6) = -9.083298012568898e-06
+RBC(  -1,   6) = -1.669288973125443e-04,    ZBS(  -1,   6) = -1.577355508505889e-05
+RBC(   0,   6) = -5.740947496624452e-04,    ZBS(   0,   6) = -1.468401390178271e-04
+RBC(   1,   6) =  9.797399171320143e-04,    ZBS(   1,   6) =  1.660974255542010e-03
+RBC(   2,   6) =  2.005552908326592e-03,    ZBS(   2,   6) =  2.024014755917893e-03
+RBC(   3,   6) =  7.895751058684376e-04,    ZBS(   3,   6) =  7.949978507802499e-04
+RBC(   4,   6) =  1.430026322574913e-04,    ZBS(   4,   6) =  1.578777627406422e-04
+RBC(   5,   6) =  1.632711480728213e-05,    ZBS(   5,   6) =  2.527001077500360e-05
+RBC(   6,   6) = -3.017528371174111e-05,    ZBS(   6,   6) =  3.261562870194376e-05
+RBC(  -6,   7) =  8.843555887433268e-06,    ZBS(  -6,   7) =  2.254450604786848e-06
+RBC(  -5,   7) = -2.566387988171289e-05,    ZBS(  -5,   7) = -4.050153539059534e-06
+RBC(  -4,   7) = -1.570232999808248e-04,    ZBS(  -4,   7) = -3.233318253199152e-05
+RBC(  -3,   7) =  4.667452607786889e-05,    ZBS(  -3,   7) =  5.906176034675469e-05
+RBC(  -2,   7) =  7.375112031781281e-07,    ZBS(  -2,   7) =  2.612554507553553e-05
+RBC(  -1,   7) = -5.561588382186081e-05,    ZBS(  -1,   7) =  4.560354645558982e-06
+RBC(   0,   7) = -2.544396106653482e-04,    ZBS(   0,   7) = -1.054799178639967e-04
+RBC(   1,   7) =  4.801560282529168e-04,    ZBS(   1,   7) =  7.261087165171264e-04
+RBC(   2,   7) =  1.033228707871272e-03,    ZBS(   2,   7) =  1.134840201352543e-03
+RBC(   3,   7) =  5.242568176479419e-04,    ZBS(   3,   7) =  5.410073694766236e-04
+RBC(   4,   7) =  8.935945632050070e-05,    ZBS(   4,   7) =  1.044107267490790e-04
+RBC(   5,   7) = -3.185864510932317e-06,    ZBS(   5,   7) =  4.090528140114576e-06
+RBC(   6,   7) = -2.438960600864805e-05,    ZBS(   6,   7) =  1.146662761512652e-05
+RBC(  -6,   8) =  4.386907587164293e-06,    ZBS(  -6,   8) = -1.158797131476164e-06
+RBC(  -5,   8) = -2.408938661765834e-05,    ZBS(  -5,   8) = -4.533100400365035e-06
+RBC(  -4,   8) = -7.881905208795266e-05,    ZBS(  -4,   8) = -3.913106990398991e-06
+RBC(  -3,   8) =  7.477768771097089e-05,    ZBS(  -3,   8) =  5.304242572923369e-05
+RBC(  -2,   8) =  1.910732289810221e-05,    ZBS(  -2,   8) =  2.560109273519888e-05
+RBC(  -1,   8) = -9.623565442064731e-06,    ZBS(  -1,   8) =  1.024550531123320e-05
+RBC(   0,   8) = -9.390121113938230e-05,    ZBS(   0,   8) = -7.071965325837792e-05
+RBC(   1,   8) = -1.738692985508703e-04,    ZBS(   1,   8) =  5.094610801626467e-04
+RBC(   2,   8) =  5.981878383042165e-04,    ZBS(   2,   8) =  7.022582314932573e-04
+RBC(   3,   8) =  3.588450116417199e-04,    ZBS(   3,   8) =  3.799398311072145e-04
+RBC(   4,   8) =  6.211128567024899e-05,    ZBS(   4,   8) =  7.845148386562932e-05
+RBC(   5,   8) = -1.233123228084070e-05,    ZBS(   5,   8) = -4.495754207362030e-06
+RBC(   6,   8) = -2.134989466723940e-05,    ZBS(   6,   8) = -6.472484674411366e-07
+RBC(  -6,   9) =  2.126021144344328e-07,    ZBS(  -6,   9) = -9.408113700709743e-07
+RBC(  -5,   9) = -1.308385171918917e-05,    ZBS(  -5,   9) = -5.527185463969529e-06
+RBC(  -4,   9) = -3.493230755826244e-05,    ZBS(  -4,   9) =  1.251757432670082e-06
+RBC(  -3,   9) =  6.925828459579091e-05,    ZBS(  -3,   9) =  3.181573038529729e-05
+RBC(  -2,   9) =  1.683550196473891e-05,    ZBS(  -2,   9) =  1.466874053254625e-05
+RBC(  -1,   9) =  1.304354634187420e-06,    ZBS(  -1,   9) =  1.295469035472810e-05
+RBC(   0,   9) = -4.400578573357121e-05,    ZBS(   0,   9) = -3.387123599162059e-05
+RBC(   1,   9) = -8.251368218891716e-05,    ZBS(   1,   9) =  1.978709893774306e-04
+RBC(   2,   9) =  3.269835024957091e-04,    ZBS(   2,   9) =  4.350067117603741e-04
+RBC(   3,   9) =  2.518538471987470e-04,    ZBS(   3,   9) =  2.771534104490756e-04
+RBC(   4,   9) =  4.926947018807496e-05,    ZBS(   4,   9) =  6.839271007676722e-05
+RBC(   5,   9) = -1.111458317545673e-05,    ZBS(   5,   9) = -3.125604302938337e-06
+RBC(   6,   9) = -1.733098465656395e-05,    ZBS(   6,   9) = -5.306421732939473e-06
+/
+
diff --git a/initial_configs/input.ALPES_QUASR_0021326_1_geo6_ns16 b/initial_configs/input.ALPES_QUASR_0021326_1_geo6_ns16
new file mode 100644
index 0000000..45eb2da
--- /dev/null
+++ b/initial_configs/input.ALPES_QUASR_0021326_1_geo6_ns16
@@ -0,0 +1,155 @@
+&INDATA
+! Scaled from input.ALPES_QUASR_0021326_1 with geo_scale=6.
+! Boundary Fourier coefficients (RBC/RBS/ZBC/ZBS) were scaled.
+! License and provenance: see initial_configs/NOTICE.ALPES_QUASR_0021326.
+
+NFP = 2
+LASYM = F
+
+MPOL = 9
+NTOR = 6
+NTHETA = 24
+NZETA = 18
+  NS_ARRAY = 16
+NITER_ARRAY =  10000  10000  10000
+FTOL_ARRAY  =  2e-10
+
+PHIEDGE = 1.0
+
+PMASS_TYPE = "power_series"
+AM = 0.0 
+PRES_SCALE = 1.0
+
+NCURR = 1
+CURTOR = 0.0
+PCURR_TYPE = "power_series"
+AC = 0.0 
+
+DELT = 0.9
+NSTEP = 200
+
+RBC(0,0) = 6.224893654209811E+00,    ZBS(0,0) = 0.000000000000000E+00
+RBC(1,0) = 5.603816044151086E-01,    ZBS(1,0) = 6.416921296887552E-01
+RBC(2,0) = 3.305750432284227E-02,    ZBS(2,0) = 3.575026932661124E-02
+RBC(3,0) = 3.242304481316407E-03,    ZBS(3,0) = 2.345839122810196E-03
+RBC(4,0) = 2.571801629685414E-03,    ZBS(4,0) = 1.101764059562348E-03
+RBC(5,0) = 3.081557152132730E-03,    ZBS(5,0) = -1.326079262026447E-03
+RBC(6,0) = 8.440638682534026E-03,    ZBS(6,0) = -1.409848100003631E-03
+RBC(-6,1) = -3.982225477261870E-03,    ZBS(-6,1) = 1.497927297502539E-03
+RBC(-5,1) = 5.472444303708255E-03,    ZBS(-5,1) = 6.257241617783777E-03
+RBC(-4,1) = 3.596692230637048E-03,    ZBS(-4,1) = 4.902268001554203E-03
+RBC(-3,1) = 2.485048442530354E-03,    ZBS(-3,1) = 4.516629640993483E-03
+RBC(-2,1) = -9.050221171983383E-03,    ZBS(-2,1) = 1.358796671595904E-02
+RBC(-1,1) = -1.307838277654521E-01,    ZBS(-1,1) = 1.213513649024173E-01
+RBC(0,1) = -1.697892259583769E+00,    ZBS(0,1) = 1.467138428733375E+00
+RBC(1,1) = 5.859932030205185E-01,    ZBS(1,1) = 3.720463213213768E-01
+RBC(2,1) = 8.393006999702016E-02,    ZBS(2,1) = 7.848179381966616E-02
+RBC(3,1) = 8.507903644433081E-03,    ZBS(3,1) = 8.774690082770983E-03
+RBC(4,1) = -3.826814194971668E-04,    ZBS(4,1) = 7.464611894132226E-04
+RBC(5,1) = 4.521524760216015E-05,    ZBS(5,1) = -1.009868579907996E-04
+RBC(6,1) = -2.844042688331827E-03,    ZBS(6,1) = 2.630344606629191E-03
+RBC(-6,2) = 1.579996957326688E-03,    ZBS(-6,2) = -1.664134413864728E-03
+RBC(-5,2) = 3.686745478126756E-04,    ZBS(-5,2) = 7.779807913425654E-04
+RBC(-4,2) = 1.106423059895123E-03,    ZBS(-4,2) = 1.093687402989893E-03
+RBC(-3,2) = 2.262544338336391E-03,    ZBS(-3,2) = 2.982201847820052E-03
+RBC(-2,2) = -4.475188406834885E-04,    ZBS(-2,2) = 6.368336266777895E-03
+RBC(-1,2) = -2.660998913536330E-02,    ZBS(-1,2) = 3.191128277434245E-02
+RBC(0,2) = -3.404100227932854E-01,    ZBS(0,2) = 2.180440718863720E-01
+RBC(1,2) = 2.823914045595868E-01,    ZBS(1,2) = 2.037383294568093E-01
+RBC(2,2) = 8.655638312250599E-02,    ZBS(2,2) = 7.695934711864841E-02
+RBC(3,2) = 1.664801687741857E-02,    ZBS(3,2) = 1.620743015278243E-02
+RBC(4,2) = 2.401532946218480E-03,    ZBS(4,2) = 2.501818297064175E-03
+RBC(5,2) = 1.516212171475422E-04,    ZBS(5,2) = 1.913647656166365E-04
+RBC(6,2) = -6.253522970473914E-04,    ZBS(6,2) = -1.463541370673816E-04
+RBC(-6,3) = 6.028300632971100E-04,    ZBS(-6,3) = 9.403950851871654E-05
+RBC(-5,3) = 1.062691795443982E-03,    ZBS(-5,3) = -9.733929619397508E-04
+RBC(-4,3) = -2.322194977059781E-03,    ZBS(-4,3) = -3.765040735358307E-03
+RBC(-3,3) = -1.747400084595695E-03,    ZBS(-3,3) = -2.681083770784705E-03
+RBC(-2,3) = -2.416494026012383E-03,    ZBS(-2,3) = -5.890427819367418E-04
+RBC(-1,3) = -1.176249250318224E-02,    ZBS(-1,3) = 8.333675405326679E-03
+RBC(0,3) = -9.097953627889818E-02,    ZBS(0,3) = 4.541300723161580E-02
+RBC(1,3) = 1.191263293113460E-01,    ZBS(1,3) = 1.019523535184531E-01
+RBC(2,3) = 5.850273865598080E-02,    ZBS(2,3) = 5.183953752870354E-02
+RBC(3,3) = 1.369463927462375E-02,    ZBS(3,3) = 1.345309474963801E-02
+RBC(4,3) = 2.722360589599043E-03,    ZBS(4,3) = 3.126320406931789E-03
+RBC(5,3) = 2.971099613315067E-04,    ZBS(5,3) = 5.603930239155986E-04
+RBC(6,3) = -6.963110526043848E-04,    ZBS(6,3) = 4.832166604740140E-04
+RBC(-6,4) = 2.617748091113702E-04,    ZBS(-6,4) = 2.710342453285156E-04
+RBC(-5,4) = 4.315401774783874E-04,    ZBS(-5,4) = -3.171661418524395E-04
+RBC(-4,4) = -2.805107148096959E-03,    ZBS(-4,4) = -3.254946807863339E-03
+RBC(-3,4) = -2.071053485116763E-03,    ZBS(-3,4) = -2.545689233023022E-03
+RBC(-2,4) = -2.113720809221115E-03,    ZBS(-2,4) = -1.552619695841937E-03
+RBC(-1,4) = -5.532335703217016E-03,    ZBS(-1,4) = 1.218933958068772E-03
+RBC(0,4) = -2.724094328560109E-02,    ZBS(0,4) = 8.074119965089416E-03
+RBC(1,4) = 4.691439218475336E-02,    ZBS(1,4) = 4.871624613462659E-02
+RBC(2,4) = 3.674407248078861E-02,    ZBS(2,4) = 3.314258243479901E-02
+RBC(3,4) = 1.002805810409226E-02,    ZBS(3,4) = 9.802969610128326E-03
+RBC(4,4) = 2.164284800131293E-03,    ZBS(4,4) = 2.395895192435265E-03
+RBC(5,4) = 3.563171309139199E-04,    ZBS(5,4) = 5.497530298085184E-04
+RBC(6,4) = -4.989442142167065E-04,    ZBS(6,4) = 5.718389208670949E-04
+RBC(-6,5) = 1.753149387606138E-04,    ZBS(-6,5) = 1.497995145950749E-04
+RBC(-5,5) = 1.715390687671204E-06,    ZBS(-5,5) = -4.742153692288902E-05
+RBC(-4,5) = -2.354224451513847E-03,    ZBS(-4,5) = -1.661943341601621E-03
+RBC(-3,5) = -1.162130028631421E-03,    ZBS(-3,5) = -9.245931618201617E-04
+RBC(-2,5) = -1.147937784608860E-03,    ZBS(-2,5) = -7.056261999048756E-04
+RBC(-1,5) = -2.486688968233110E-03,    ZBS(-1,5) = -1.264626775258785E-04
+RBC(0,5) = -8.963243130836417E-03,    ZBS(0,5) = 1.575801962159426E-04
+RBC(1,5) = 1.702124771899476E-02,    ZBS(1,5) = 2.222615420265844E-02
+RBC(2,5) = 2.164785589321388E-02,    ZBS(2,5) = 2.043002017441558E-02
+RBC(3,5) = 6.959348496841572E-03,    ZBS(3,5) = 6.866393845716421E-03
+RBC(4,5) = 1.415531284044939E-03,    ZBS(4,5) = 1.533080006954189E-03
+RBC(5,5) = 2.526942510767437E-04,    ZBS(5,5) = 3.537246026948306E-04
+RBC(6,5) = -2.877266380895039E-04,    ZBS(6,5) = 3.892379445789578E-04
+RBC(-6,6) = 1.119890269318550E-04,    ZBS(-6,6) = 6.364951404114319E-05
+RBC(-5,6) = -1.525013664399294E-04,    ZBS(-5,6) = -1.931058276653396E-05
+RBC(-4,6) = -1.608319908937585E-03,    ZBS(-4,6) = -6.482238298289952E-04
+RBC(-3,6) = -2.445441025984289E-04,    ZBS(-3,6) = 6.839637400839366E-05
+RBC(-2,6) = -3.825113660943023E-04,    ZBS(-2,6) = -5.449978807541339E-05
+RBC(-1,6) = -1.001573383875266E-03,    ZBS(-1,6) = -9.464133051035334E-05
+RBC(0,6) = -3.444568497974671E-03,    ZBS(0,6) = -8.810408341069627E-04
+RBC(1,6) = 5.878439502792086E-03,    ZBS(1,6) = 9.965845533252060E-03
+RBC(2,6) = 1.203331744995955E-02,    ZBS(2,6) = 1.214408853550736E-02
+RBC(3,6) = 4.737450635210626E-03,    ZBS(3,6) = 4.769987104681499E-03
+RBC(4,6) = 8.580157935449478E-04,    ZBS(4,6) = 9.472665764438531E-04
+RBC(5,6) = 9.796268884369279E-05,    ZBS(5,6) = 1.516200646500216E-04
+RBC(6,6) = -1.810517022704467E-04,    ZBS(6,6) = 1.956937722116626E-04
+RBC(-6,7) = 5.306133532459960E-05,    ZBS(-6,7) = 1.352670362872109E-05
+RBC(-5,7) = -1.539832792902774E-04,    ZBS(-5,7) = -2.430092123435720E-05
+RBC(-4,7) = -9.421397998849488E-04,    ZBS(-4,7) = -1.939990951919491E-04
+RBC(-3,7) = 2.800471564672133E-04,    ZBS(-3,7) = 3.543705620805281E-04
+RBC(-2,7) = 4.425067219068769E-06,    ZBS(-2,7) = 1.567532704532132E-04
+RBC(-1,7) = -3.336953029311649E-04,    ZBS(-1,7) = 2.736212787335389E-05
+RBC(0,7) = -1.526637663992089E-03,    ZBS(0,7) = -6.328795071839802E-04
+RBC(1,7) = 2.880936169517501E-03,    ZBS(1,7) = 4.356652299102758E-03
+RBC(2,7) = 6.199372247227632E-03,    ZBS(2,7) = 6.809041208115258E-03
+RBC(3,7) = 3.145540905887652E-03,    ZBS(3,7) = 3.246044216859742E-03
+RBC(4,7) = 5.361567379230041E-04,    ZBS(4,7) = 6.264643604944741E-04
+RBC(5,7) = -1.911518706559390E-05,    ZBS(5,7) = 2.454316884068746E-05
+RBC(6,7) = -1.463376360518883E-04,    ZBS(6,7) = 6.879976569075912E-05
+RBC(-6,8) = 2.632144552298576E-05,    ZBS(-6,8) = -6.952782788856983E-06
+RBC(-5,8) = -1.445363197059500E-04,    ZBS(-5,8) = -2.719860240219021E-05
+RBC(-4,8) = -4.729143125277160E-04,    ZBS(-4,8) = -2.347864194239394E-05
+RBC(-3,8) = 4.486661262658253E-04,    ZBS(-3,8) = 3.182545543754022E-04
+RBC(-2,8) = 1.146439373886133E-04,    ZBS(-2,8) = 1.536065564111933E-04
+RBC(-1,8) = -5.774139265238839E-05,    ZBS(-1,8) = 6.147303186739921E-05
+RBC(0,8) = -5.634072668362938E-04,    ZBS(0,8) = -4.243179195502675E-04
+RBC(1,8) = -1.043215791305222E-03,    ZBS(1,8) = 3.056766480975880E-03
+RBC(2,8) = 3.589127029825299E-03,    ZBS(2,8) = 4.213549388959544E-03
+RBC(3,8) = 2.153070069850320E-03,    ZBS(3,8) = 2.279638986643287E-03
+RBC(4,8) = 3.726677140214939E-04,    ZBS(4,8) = 4.707089031937760E-04
+RBC(5,8) = -7.398739368504419E-05,    ZBS(5,8) = -2.697452524417218E-05
+RBC(6,8) = -1.280993680034364E-04,    ZBS(6,8) = -3.883490804646820E-06
+RBC(-6,9) = 1.275612686606597E-06,    ZBS(-6,9) = -5.644868220425845E-06
+RBC(-5,9) = -7.850311031513501E-05,    ZBS(-5,9) = -3.316311278381717E-05
+RBC(-4,9) = -2.095938453495746E-04,    ZBS(-4,9) = 7.510544596020492E-06
+RBC(-3,9) = 4.155497075747455E-04,    ZBS(-3,9) = 1.908943823117838E-04
+RBC(-2,9) = 1.010130117884335E-04,    ZBS(-2,9) = 8.801244319527750E-05
+RBC(-1,9) = 7.826127805124520E-06,    ZBS(-1,9) = 7.772814212836860E-05
+RBC(0,9) = -2.640347144014272E-04,    ZBS(0,9) = -2.032274159497235E-04
+RBC(1,9) = -4.950820931335030E-04,    ZBS(1,9) = 1.187225936264584E-03
+RBC(2,9) = 1.961901014974255E-03,    ZBS(2,9) = 2.610040270562245E-03
+RBC(3,9) = 1.511123083192482E-03,    ZBS(3,9) = 1.662920462694454E-03
+RBC(4,9) = 2.956168211284498E-04,    ZBS(4,9) = 4.103562604606033E-04
+RBC(5,9) = -6.668749905274038E-05,    ZBS(5,9) = -1.875362581763002E-05
+RBC(6,9) = -1.039859079393837E-04,    ZBS(6,9) = -3.183853039763684E-05
+/
diff --git a/initial_configs/input.ALPES_QUASR_0021326_1_ns16 b/initial_configs/input.ALPES_QUASR_0021326_1_ns16
new file mode 100644
index 0000000..067357e
--- /dev/null
+++ b/initial_configs/input.ALPES_QUASR_0021326_1_ns16
@@ -0,0 +1,155 @@
+&INDATA
+! Scaled from input.ALPES_QUASR_0021326_1 with geo_scale=1.
+! Boundary Fourier coefficients (RBC/RBS/ZBC/ZBS) were scaled.
+! License and provenance: see initial_configs/NOTICE.ALPES_QUASR_0021326.
+
+NFP = 2
+LASYM = F
+
+MPOL = 9
+NTOR = 6
+NTHETA = 24
+NZETA = 18
+  NS_ARRAY = 16
+NITER_ARRAY =  10000  10000  10000
+FTOL_ARRAY  =  2e-10
+
+PHIEDGE = 1.0
+
+PMASS_TYPE = "power_series"
+AM = 0.0 
+PRES_SCALE = 1.0
+
+NCURR = 1
+CURTOR = 0.0
+PCURR_TYPE = "power_series"
+AC = 0.0 
+
+DELT = 0.9
+NSTEP = 200
+
+RBC(0,0) = 1.037482275701635E+00,    ZBS(0,0) = 0.000000000000000E+00
+RBC(1,0) = 9.339693406918478E-02,    ZBS(1,0) = 1.069486882814592E-01
+RBC(2,0) = 5.509584053807044E-03,    ZBS(2,0) = 5.958378221101873E-03
+RBC(3,0) = 5.403840802194012E-04,    ZBS(3,0) = 3.909731871350326E-04
+RBC(4,0) = 4.286336049475691E-04,    ZBS(4,0) = 1.836273432603913E-04
+RBC(5,0) = 5.135928586887884E-04,    ZBS(5,0) = -2.210132103377411E-04
+RBC(6,0) = 1.406773113755671E-03,    ZBS(6,0) = -2.349746833339385E-04
+RBC(-6,1) = -6.637042462103116E-04,    ZBS(-6,1) = 2.496545495837565E-04
+RBC(-5,1) = 9.120740506180424E-04,    ZBS(-5,1) = 1.042873602963963E-03
+RBC(-4,1) = 5.994487051061747E-04,    ZBS(-4,1) = 8.170446669257006E-04
+RBC(-3,1) = 4.141747404217256E-04,    ZBS(-3,1) = 7.527716068322473E-04
+RBC(-2,1) = -1.508370195330564E-03,    ZBS(-2,1) = 2.264661119326507E-03
+RBC(-1,1) = -2.179730462757535E-02,    ZBS(-1,1) = 2.022522748373621E-02
+RBC(0,1) = -2.829820432639614E-01,    ZBS(0,1) = 2.445230714555625E-01
+RBC(1,1) = 9.766553383675308E-02,    ZBS(1,1) = 6.200772022022946E-02
+RBC(2,1) = 1.398834499950336E-02,    ZBS(2,1) = 1.308029896994436E-02
+RBC(3,1) = 1.417983940738847E-03,    ZBS(3,1) = 1.462448347128497E-03
+RBC(4,1) = -6.378023658286113E-05,    ZBS(4,1) = 1.244101982355371E-04
+RBC(5,1) = 7.535874600360025E-06,    ZBS(5,1) = -1.683114299846660E-05
+RBC(6,1) = -4.740071147219712E-04,    ZBS(6,1) = 4.383907677715318E-04
+RBC(-6,2) = 2.633328262211147E-04,    ZBS(-6,2) = -2.773557356441214E-04
+RBC(-5,2) = 6.144575796877927E-05,    ZBS(-5,2) = 1.296634652237609E-04
+RBC(-4,2) = 1.844038433158538E-04,    ZBS(-4,2) = 1.822812338316488E-04
+RBC(-3,2) = 3.770907230560651E-04,    ZBS(-3,2) = 4.970336413033421E-04
+RBC(-2,2) = -7.458647344724807E-05,    ZBS(-2,2) = 1.061389377796316E-03
+RBC(-1,2) = -4.434998189227216E-03,    ZBS(-1,2) = 5.318547129057076E-03
+RBC(0,2) = -5.673500379888089E-02,    ZBS(0,2) = 3.634067864772867E-02
+RBC(1,2) = 4.706523409326446E-02,    ZBS(1,2) = 3.395638824280155E-02
+RBC(2,2) = 1.442606385375100E-02,    ZBS(2,2) = 1.282655785310807E-02
+RBC(3,2) = 2.774669479569761E-03,    ZBS(3,2) = 2.701238358797072E-03
+RBC(4,2) = 4.002554910364133E-04,    ZBS(4,2) = 4.169697161773624E-04
+RBC(5,2) = 2.527020285792371E-05,    ZBS(5,2) = 3.189412760277275E-05
+RBC(6,2) = -1.042253828412319E-04,    ZBS(6,2) = -2.439235617789694E-05
+RBC(-6,3) = 1.004716772161850E-04,    ZBS(-6,3) = 1.567325141978609E-05
+RBC(-5,3) = 1.771152992406636E-04,    ZBS(-5,3) = -1.622321603232918E-04
+RBC(-4,3) = -3.870324961766302E-04,    ZBS(-4,3) = -6.275067892263844E-04
+RBC(-3,3) = -2.912333474326158E-04,    ZBS(-3,3) = -4.468472951307841E-04
+RBC(-2,3) = -4.027490043353972E-04,    ZBS(-2,3) = -9.817379698945697E-05
+RBC(-1,3) = -1.960415417197040E-03,    ZBS(-1,3) = 1.388945900887780E-03
+RBC(0,3) = -1.516325604648303E-02,    ZBS(0,3) = 7.568834538602634E-03
+RBC(1,3) = 1.985438821855766E-02,    ZBS(1,3) = 1.699205891974218E-02
+RBC(2,3) = 9.750456442663466E-03,    ZBS(2,3) = 8.639922921450591E-03
+RBC(3,3) = 2.282439879103958E-03,    ZBS(3,3) = 2.242182458273002E-03
+RBC(4,3) = 4.537267649331738E-04,    ZBS(4,3) = 5.210534011552982E-04
+RBC(5,3) = 4.951832688858445E-05,    ZBS(5,3) = 9.339883731926644E-05
+RBC(6,3) = -1.160518421007308E-04,    ZBS(6,3) = 8.053611007900234E-05
+RBC(-6,4) = 4.362913485189504E-05,    ZBS(-6,4) = 4.517237422141926E-05
+RBC(-5,4) = 7.192336291306456E-05,    ZBS(-5,4) = -5.286102364207326E-05
+RBC(-4,4) = -4.675178580161597E-04,    ZBS(-4,4) = -5.424911346438898E-04
+RBC(-3,4) = -3.451755808527939E-04,    ZBS(-3,4) = -4.242815388371704E-04
+RBC(-2,4) = -3.522868015368525E-04,    ZBS(-2,4) = -2.587699493069896E-04
+RBC(-1,4) = -9.220559505361694E-04,    ZBS(-1,4) = 2.031556596781286E-04
+RBC(0,4) = -4.540157214266849E-03,    ZBS(0,4) = 1.345686660848236E-03
+RBC(1,4) = 7.819065364125560E-03,    ZBS(1,4) = 8.119374355771099E-03
+RBC(2,4) = 6.124012080131434E-03,    ZBS(2,4) = 5.523763739133167E-03
+RBC(3,4) = 1.671343017348709E-03,    ZBS(3,4) = 1.633828268354721E-03
+RBC(4,4) = 3.607141333552154E-04,    ZBS(4,4) = 3.993158654058775E-04
+RBC(5,4) = 5.938618848565332E-05,    ZBS(5,4) = 9.162550496808641E-05
+RBC(6,4) = -8.315736903611775E-05,    ZBS(6,4) = 9.530648681118248E-05
+RBC(-6,5) = 2.921915646010230E-05,    ZBS(-6,5) = 2.496658576584582E-05
+RBC(-5,5) = 2.858984479452007E-07,    ZBS(-5,5) = -7.903589487148170E-06
+RBC(-4,5) = -3.923707419189745E-04,    ZBS(-4,5) = -2.769905569336035E-04
+RBC(-3,5) = -1.936883381052368E-04,    ZBS(-3,5) = -1.540988603033603E-04
+RBC(-2,5) = -1.913229641014767E-04,    ZBS(-2,5) = -1.176043666508126E-04
+RBC(-1,5) = -4.144481613721851E-04,    ZBS(-1,5) = -2.107711292097974E-05
+RBC(0,5) = -1.493873855139403E-03,    ZBS(0,5) = 2.626336603599044E-05
+RBC(1,5) = 2.836874619832460E-03,    ZBS(1,5) = 3.704359033776406E-03
+RBC(2,5) = 3.607975982202313E-03,    ZBS(2,5) = 3.405003362402597E-03
+RBC(3,5) = 1.159891416140262E-03,    ZBS(3,5) = 1.144398974286070E-03
+RBC(4,5) = 2.359218806741565E-04,    ZBS(4,5) = 2.555133344923649E-04
+RBC(5,5) = 4.211570851279061E-05,    ZBS(5,5) = 5.895410044913843E-05
+RBC(6,5) = -4.795443968158398E-05,    ZBS(6,5) = 6.487299076315962E-05
+RBC(-6,6) = 1.866483782197583E-05,    ZBS(-6,6) = 1.060825234019053E-05
+RBC(-5,6) = -2.541689440665489E-05,    ZBS(-5,6) = -3.218430461088993E-06
+RBC(-4,6) = -2.680533181562642E-04,    ZBS(-4,6) = -1.080373049714992E-04
+RBC(-3,6) = -4.075735043307147E-05,    ZBS(-3,6) = 1.139939566806561E-05
+RBC(-2,6) = -6.375189434905038E-05,    ZBS(-2,6) = -9.083298012568898E-06
+RBC(-1,6) = -1.669288973125443E-04,    ZBS(-1,6) = -1.577355508505889E-05
+RBC(0,6) = -5.740947496624452E-04,    ZBS(0,6) = -1.468401390178271E-04
+RBC(1,6) = 9.797399171320143E-04,    ZBS(1,6) = 1.660974255542010E-03
+RBC(2,6) = 2.005552908326592E-03,    ZBS(2,6) = 2.024014755917893E-03
+RBC(3,6) = 7.895751058684376E-04,    ZBS(3,6) = 7.949978507802499E-04
+RBC(4,6) = 1.430026322574913E-04,    ZBS(4,6) = 1.578777627406422E-04
+RBC(5,6) = 1.632711480728213E-05,    ZBS(5,6) = 2.527001077500360E-05
+RBC(6,6) = -3.017528371174111E-05,    ZBS(6,6) = 3.261562870194376E-05
+RBC(-6,7) = 8.843555887433268E-06,    ZBS(-6,7) = 2.254450604786848E-06
+RBC(-5,7) = -2.566387988171289E-05,    ZBS(-5,7) = -4.050153539059534E-06
+RBC(-4,7) = -1.570232999808248E-04,    ZBS(-4,7) = -3.233318253199152E-05
+RBC(-3,7) = 4.667452607786889E-05,    ZBS(-3,7) = 5.906176034675469E-05
+RBC(-2,7) = 7.375112031781281E-07,    ZBS(-2,7) = 2.612554507553553E-05
+RBC(-1,7) = -5.561588382186081E-05,    ZBS(-1,7) = 4.560354645558982E-06
+RBC(0,7) = -2.544396106653482E-04,    ZBS(0,7) = -1.054799178639967E-04
+RBC(1,7) = 4.801560282529168E-04,    ZBS(1,7) = 7.261087165171264E-04
+RBC(2,7) = 1.033228707871272E-03,    ZBS(2,7) = 1.134840201352543E-03
+RBC(3,7) = 5.242568176479419E-04,    ZBS(3,7) = 5.410073694766236E-04
+RBC(4,7) = 8.935945632050070E-05,    ZBS(4,7) = 1.044107267490790E-04
+RBC(5,7) = -3.185864510932317E-06,    ZBS(5,7) = 4.090528140114576E-06
+RBC(6,7) = -2.438960600864805E-05,    ZBS(6,7) = 1.146662761512652E-05
+RBC(-6,8) = 4.386907587164293E-06,    ZBS(-6,8) = -1.158797131476164E-06
+RBC(-5,8) = -2.408938661765834E-05,    ZBS(-5,8) = -4.533100400365035E-06
+RBC(-4,8) = -7.881905208795266E-05,    ZBS(-4,8) = -3.913106990398991E-06
+RBC(-3,8) = 7.477768771097089E-05,    ZBS(-3,8) = 5.304242572923369E-05
+RBC(-2,8) = 1.910732289810221E-05,    ZBS(-2,8) = 2.560109273519888E-05
+RBC(-1,8) = -9.623565442064731E-06,    ZBS(-1,8) = 1.024550531123320E-05
+RBC(0,8) = -9.390121113938230E-05,    ZBS(0,8) = -7.071965325837792E-05
+RBC(1,8) = -1.738692985508703E-04,    ZBS(1,8) = 5.094610801626467E-04
+RBC(2,8) = 5.981878383042165E-04,    ZBS(2,8) = 7.022582314932573E-04
+RBC(3,8) = 3.588450116417199E-04,    ZBS(3,8) = 3.799398311072145E-04
+RBC(4,8) = 6.211128567024899E-05,    ZBS(4,8) = 7.845148386562932E-05
+RBC(5,8) = -1.233123228084070E-05,    ZBS(5,8) = -4.495754207362030E-06
+RBC(6,8) = -2.134989466723940E-05,    ZBS(6,8) = -6.472484674411366E-07
+RBC(-6,9) = 2.126021144344328E-07,    ZBS(-6,9) = -9.408113700709743E-07
+RBC(-5,9) = -1.308385171918917E-05,    ZBS(-5,9) = -5.527185463969529E-06
+RBC(-4,9) = -3.493230755826244E-05,    ZBS(-4,9) = 1.251757432670082E-06
+RBC(-3,9) = 6.925828459579091E-05,    ZBS(-3,9) = 3.181573038529729E-05
+RBC(-2,9) = 1.683550196473891E-05,    ZBS(-2,9) = 1.466874053254625E-05
+RBC(-1,9) = 1.304354634187420E-06,    ZBS(-1,9) = 1.295469035472810E-05
+RBC(0,9) = -4.400578573357121E-05,    ZBS(0,9) = -3.387123599162059E-05
+RBC(1,9) = -8.251368218891716E-05,    ZBS(1,9) = 1.978709893774306E-04
+RBC(2,9) = 3.269835024957091E-04,    ZBS(2,9) = 4.350067117603741E-04
+RBC(3,9) = 2.518538471987470E-04,    ZBS(3,9) = 2.771534104490756E-04
+RBC(4,9) = 4.926947018807496E-05,    ZBS(4,9) = 6.839271007676722E-05
+RBC(5,9) = -1.111458317545673E-05,    ZBS(5,9) = -3.125604302938337E-06
+RBC(6,9) = -1.733098465656395E-05,    ZBS(6,9) = -5.306421732939473E-06
+/
diff --git a/initial_configs/input.LandremanPaul2021_QA_lowres_simsopt b/initial_configs/input.LandremanPaul2021_QA_lowres_simsopt
new file mode 100644
index 0000000..d7a441b
--- /dev/null
+++ b/initial_configs/input.LandremanPaul2021_QA_lowres_simsopt
@@ -0,0 +1,106 @@
+&INDATA
+!----- Runtime Parameters -----
+  DELT =   9.00E-01
+  NITER = 10000
+  NSTEP =  200
+  TCON0 =   2.00E+00
+  NS_ARRAY    =      16       50 75
+  NITER_ARRAY =     600     3000 3000
+  FTOL_ARRAY  = 1.0E-16  1.0E-11 1.0E-13
+
+!  NS_ARRAY    =      12      25      50      75     100     150     201
+!  NITER_ARRAY =    1200    2000    3000    4000    5000    6000   20000
+!  FTOL_ARRAY  = 1.0E-17 1.0e-17 1.0e-17 1.0e-17 1.0e-17 1.0e-17 2.0e-17
+
+  PRECON_TYPE = 'none'
+  PREC2D_THRESHOLD =   1.000000E-19
+!----- Grid Parameters -----
+  LASYM = F
+  NFP = 0002
+  MPOL = 8
+  NTOR = 8
+!  MPOL = 00016
+!  NTOR = 00012
+  PHIEDGE =    0.08385727554
+!----- Free Boundary Parameters -----
+  LFREEB = F
+  NVACSKIP =    6
+!----- Pressure Parameters -----
+  GAMMA =    0.000000000000E+000
+  BLOAT =    1.000000000000E+000
+  SPRES_PED =    1.000000000000E+000
+  PRES_SCALE =    1.000000000000E+000
+  PMASS_TYPE = 'power_series'
+  AM =   000000000E+00
+!----- Current/Iota Parameters -----
+  CURTOR =  0
+  NCURR = 1
+  PIOTA_TYPE = 'power_series'
+  PCURR_TYPE = 'power_series'
+!----- Axis Parameters ----- 
+  RAXIS_CC = 0
+  ZAXIS_CS = 0
+!----- Boundary Parameters -----
+! n comes before m!
+RBC(   0,   0) =    1.000000000000000e+00,      ZBS(   0,   0) =   -0.000000000000000e+00
+RBC(   1,   0) =    1.635736469509085e-01,      ZBS(   1,   0) =   -1.253658594586452e-01
+RBC(   2,   0) =    1.153464403265224e-02,      ZBS(   2,   0) =   -1.143100828466809e-02
+RBC(   3,   0) =    1.660825542716507e-04,      ZBS(   3,   0) =   -1.836705489992535e-04
+RBC(   4,   0) =   -4.289839778893124e-05,      ZBS(   4,   0) =    6.379980554947428e-05
+RBC(   5,   0) =   -7.088365208037713e-06,      ZBS(   5,   0) =    6.424749751809887e-06
+RBC(  -5,   1) =   -1.234892163278594e-06,      ZBS(  -5,   1) =    1.650698547431063e-06
+RBC(  -4,   1) =    5.885906939720765e-05,      ZBS(  -4,   1) =    7.747703517376636e-05
+RBC(  -3,   1) =    1.177705088726893e-03,      ZBS(  -3,   1) =    8.768242973159689e-04
+RBC(  -2,   1) =    6.117449935928349e-03,      ZBS(  -2,   1) =    6.917463886154144e-03
+RBC(  -1,   1) =    3.695998128952078e-02,      ZBS(  -1,   1) =    3.357703036173842e-02
+RBC(   0,   1) =    1.658776713857751e-01,      ZBS(   0,   1) =    2.153938070783234e-01
+RBC(   1,   1) =   -1.088789497913388e-01,      ZBS(   1,   1) =    8.004202421496563e-02
+RBC(   2,   1) =   -2.128857374166514e-02,      ZBS(   2,   1) =    1.941805377930779e-02
+RBC(   3,   1) =   -2.300157572693968e-03,      ZBS(   3,   1) =    2.043310207615721e-03
+RBC(   4,   1) =   -2.627971451624495e-05,      ZBS(   4,   1) =    9.515817827817248e-05
+RBC(   5,   1) =   -3.624748429446710e-06,      ZBS(   5,   1) =    2.237608189340047e-06
+RBC(  -5,   2) =    3.429971812740527e-07,      ZBS(  -5,   2) =    3.653065246955757e-06
+RBC(  -4,   2) =    4.850684989433037e-05,      ZBS(  -4,   2) =    2.581277522578798e-05
+RBC(  -3,   2) =   -1.629464724791329e-05,      ZBS(  -3,   2) =    9.255771223110816e-05
+RBC(  -2,   2) =    6.490349497379012e-04,      ZBS(  -2,   2) =    3.952687065376200e-04
+RBC(  -1,   2) =    3.445618605450382e-05,      ZBS(  -1,   2) =   -1.331440902105533e-03
+RBC(   0,   2) =    1.582563423506581e-02,      ZBS(   0,   2) =    1.561378330710932e-02
+RBC(   1,   2) =    2.546788563643479e-02,      ZBS(   1,   2) =    8.409380325679782e-05
+RBC(   2,   2) =    3.589988783905243e-03,      ZBS(   2,   2) =   -7.162905352448011e-03
+RBC(   3,   2) =    2.023292416997494e-03,      ZBS(   3,   2) =   -1.623525685575538e-03
+RBC(   4,   2) =    1.334125199187403e-04,      ZBS(   4,   2) =   -2.144823958959020e-04
+RBC(   5,   2) =    7.495835691917963e-06,      ZBS(   5,   2) =   -3.041995113869397e-06
+RBC(  -5,   3) =    2.595971377554895e-06,      ZBS(  -5,   3) =    7.546398657171724e-07
+RBC(  -4,   3) =   -2.752586825793088e-05,      ZBS(  -4,   3) =   -1.293908425979845e-05
+RBC(  -3,   3) =   -6.881215658169502e-05,      ZBS(  -3,   3) =   -1.146639773380277e-04
+RBC(  -2,   3) =    1.851061354443457e-04,      ZBS(  -2,   3) =    2.034757712275398e-04
+RBC(  -1,   3) =   -9.499158045035575e-04,      ZBS(  -1,   3) =   -1.194121521590374e-03
+RBC(   0,   3) =    6.789213877319417e-04,      ZBS(   0,   3) =    2.074912419441758e-03
+RBC(   1,   3) =    1.278256592588691e-04,      ZBS(   1,   3) =    1.453779212226518e-03
+RBC(   2,   3) =    1.216640222421739e-04,      ZBS(   2,   3) =    1.751939663468610e-03
+RBC(   3,   3) =   -8.824623427313230e-04,      ZBS(   3,   3) =    4.283901601890926e-04
+RBC(   4,   3) =   -8.290455528140711e-05,      ZBS(   4,   3) =    1.361192934036727e-04
+RBC(   5,   3) =   -7.724473257867983e-06,      ZBS(   5,   3) =    8.518581946796281e-06
+RBC(  -5,   4) =   -4.525265993447933e-07,      ZBS(  -5,   4) =   -4.025242836970244e-07
+RBC(  -4,   4) =   -3.765525591663771e-06,      ZBS(  -4,   4) =   -5.091039705513993e-06
+RBC(  -3,   4) =    1.302918803102485e-05,      ZBS(  -3,   4) =    2.938909520741841e-06
+RBC(  -2,   4) =   -9.479666265169178e-05,      ZBS(  -2,   4) =   -2.244078515714136e-05
+RBC(  -1,   4) =    2.264194360369701e-04,      ZBS(  -1,   4) =   -2.520850733246328e-05
+RBC(   0,   4) =   -3.151153789937265e-04,      ZBS(   0,   4) =    9.320140252262431e-05
+RBC(   1,   4) =    3.296873412220537e-04,      ZBS(   1,   4) =   -2.042044185495455e-05
+RBC(   2,   4) =    3.702513915656681e-04,      ZBS(   2,   4) =    4.064784880640345e-05
+RBC(   3,   4) =    1.391783522713434e-04,      ZBS(   3,   4) =   -1.361278177512208e-05
+RBC(   4,   4) =    6.688738405012066e-06,      ZBS(   4,   4) =   -6.608364805280040e-05
+RBC(   5,   4) =    1.339256039281701e-05,      ZBS(   5,   4) =   -4.386750839649032e-06
+RBC(  -5,   5) =   -4.605122542160908e-07,      ZBS(  -5,   5) =   -1.918844832075774e-07
+RBC(  -4,   5) =    4.705334806798627e-06,      ZBS(  -4,   5) =    4.045952798129327e-06
+RBC(  -3,   5) =   -3.907227055013670e-06,      ZBS(  -3,   5) =    1.473135558324792e-06
+RBC(  -2,   5) =    1.564971051544039e-06,      ZBS(  -2,   5) =   -4.697232422054022e-06
+RBC(  -1,   5) =    1.512725785055272e-05,      ZBS(  -1,   5) =    2.716682965888606e-05
+RBC(   0,   5) =    2.685611719517791e-05,      ZBS(   0,   5) =    4.010578314605041e-05
+RBC(   1,   5) =   -6.524317753178391e-05,      ZBS(   1,   5) =    1.623461963012973e-05
+RBC(   2,   5) =   -3.537817812851590e-05,      ZBS(   2,   5) =   -3.511150206275442e-05
+RBC(   3,   5) =    3.342938698620821e-05,      ZBS(   3,   5) =    2.352419744940536e-05
+RBC(   4,   5) =   -9.745754270559217e-06,      ZBS(   4,   5) =    1.637637084327691e-06
+RBC(   5,   5) =   -1.976517490730610e-06,      ZBS(   5,   5) =    4.498757881413679e-08
+/
diff --git a/main.py b/main.py
index 04e4e20..97e5381 100644
--- a/main.py
+++ b/main.py
@@ -1,294 +1,8 @@
-#!/usr/bin/env python
-import os
-import glob
-import time
-import shutil
-import vmecPlot2
-import numpy as np
-import pandas as pd
-from mpi4py import MPI
-import booz_xform as bx
-from pathlib import Path
-import matplotlib.pyplot as plt
-from simsopt import make_optimizable
-from simsopt.mhd import Vmec, Boozer
-from simsopt.util import MpiPartition
-from simsopt.solve import least_squares_mpi_solve, least_squares_serial_solve
-from simsopt.mhd import QuasisymmetryRatioResidual
-from simsopt.objectives import LeastSquaresProblem
-from neat.fields import Simple
-from neat.tracing import ChargedParticleEnsemble, ParticleEnsembleOrbit_Simple
-from scipy.optimize import minimize, basinhopping, differential_evolution, dual_annealing
-from Alan_objectives import MaxElongationPen, MirrorRatioPen
-mpi = MpiPartition()
-this_path = Path(__file__).parent.resolve()
-def pprint(*args, **kwargs):
-    if MPI.COMM_WORLD.rank == 0:
-        print(*args, **kwargs)
-############################################################################
-#### Input Parameters
-############################################################################
-MAXITER = 500
-max_modes = [1, 2]
-QA_or_QH_or_QI = 'QA'
-opt_quasisymmetry = False
-opt_EP = True
-opt_well = False
-opt_iota = False
-opt_Mirror = True
-opt_Elongation = True
-plot_result = True
-optimizer = 'dual_annealing' # least_squares_diff, least_squares, basinhopping, differential_evolution, dual_annealing
-use_previous_results_if_available = False
+#!/usr/bin/env python3
+"""Prime the direct 100 ms constrained-TuRBO alpha-loss study."""
 
-weight_optEP = 100.0
-weight_opt_Mirror = 100.0
-weight_opt_Elongation = 10.0
-weight_opt_well = 0.1
-redux_B = 1.5 # Use ARIES-CS magnetic field reduced by this factor
-redux_Aminor = 1.5 # Use ARIES-CS minor radius reduced by this factor
-if QA_or_QH_or_QI == 'QA': aspect_ratio_target = 6
-elif QA_or_QH_or_QI == 'QH': aspect_ratio_target = 7
-elif QA_or_QH_or_QI == 'QI': aspect_ratio_target = 8
+from prime_direct_scbo import main
 
-s_initial = 0.3  # initial normalized toroidal magnetic flux (radial VMEC coordinate)
-nparticles = 600  # number of particles
-tfinal = 6e-5  # total time of tracing in seconds
-nsamples = 1500 # number of time steps
-multharm = 3 # angular grid factor
-ns_s = 3 # spline order over s
-ns_tp = 3 # spline order over theta and phi
-nper = 400 # number of periods for initial field line
-npoiper = 150 # number of points per period on this field line
-npoiper2 = 120 # points per period for integrator step
-notrace_passing = 0 # if 1 skips tracing of passing particles, else traces them
 
-nruns_opt_average = 1 # number of particle tracing runs to average over in cost function
-iota_target = -0.42
-well_target = 0.1
-
-diff_rel_step = 1e-1
-diff_abs_step = 1e-2
-
-output_path_parameters=f'output_{optimizer}_{QA_or_QH_or_QI}.csv'
-######################################
-######################################
-if QA_or_QH_or_QI == 'QA': nfp=2
-elif QA_or_QH_or_QI == 'QH': nfp=4
-elif QA_or_QH_or_QI == 'QI': nfp=3 # Change it later to vmec.indata.nfp
-OUT_DIR_APPENDIX=f'out_s{s_initial}_NFP{nfp}'
-if opt_quasisymmetry: OUT_DIR_APPENDIX+=f'_{QA_or_QH_or_QI}'
-if opt_well: OUT_DIR_APPENDIX+=f'_well'
-OUT_DIR = os.path.join(this_path, OUT_DIR_APPENDIX)
-os.makedirs(OUT_DIR, exist_ok=True)
-######################################
-dest = os.path.join(OUT_DIR,OUT_DIR_APPENDIX+'_previous')
-if use_previous_results_if_available and (os.path.isfile(os.path.join(OUT_DIR,'input.final')) or os.path.isfile(os.path.join(dest,'input.final'))):
-    if MPI.COMM_WORLD.rank == 0:
-        os.makedirs(dest, exist_ok=True)
-        if os.path.isfile(os.path.join(OUT_DIR, 'input.final')) and not os.path.isfile(os.path.join(dest, 'input.final')):
-            files = os.listdir(OUT_DIR)
-            for f in files:
-                shutil.move(os.path.join(OUT_DIR, f), dest)
-    else:
-        time.sleep(0.5)
-    filename = os.path.join(dest, 'input.final')
-else:
-    if QA_or_QH_or_QI == 'QA': filename = os.path.join(this_path, 'initial_configs', 'input.nfp2_QA')
-    elif QA_or_QH_or_QI == 'QH': filename = os.path.join(this_path, 'initial_configs', 'input.nfp4_QH')
-    elif QA_or_QH_or_QI == 'QI': filename = os.path.join(this_path, 'initial_configs', 'input.QI')
-os.chdir(OUT_DIR)
-vmec = Vmec(filename, mpi=mpi, verbose=False)
-vmec.keep_all_files = True
-surf = vmec.boundary
-g_particle = ChargedParticleEnsemble(r_initial=s_initial)
-######################################
-def output_dofs_to_csv(dofs,mean_iota,aspect,loss_fraction,eff_time,mirror_ratio,max_elongation):
-    keys=np.concatenate([[f'x({i})' for i, dof in enumerate(dofs)],['mean_iota'],['aspect'],['loss_fraction'],['eff_time'],['mirror_ratio'],['max_elongation']])
-    values=np.concatenate([dofs,[mean_iota],[aspect],[loss_fraction],[eff_time],[mirror_ratio],[max_elongation]])
-    dictionary = dict(zip(keys, values))
-    df = pd.DataFrame(data=[dictionary])
-    if not os.path.exists(output_path_parameters): pd.DataFrame(columns=df.columns).to_csv(output_path_parameters, index=False)
-    df.to_csv(output_path_parameters, mode='a', header=False, index=False)
-######################################
-optElongation = make_optimizable(MaxElongationPen, vmec)
-optMirror = make_optimizable(MirrorRatioPen, vmec)
-######################################
-def EPcostFunction(v: Vmec):
-    start_time = time.time()
-    try: v.run()
-    except Exception as e:
-        print(e)
-        return 1e3
-    B_scale = 5.7/v.wout.b0/redux_B  # Scale the magnetic field by a factor
-    Aminor_scale = 1.7/v.wout.Aminor_p/redux_Aminor  # Scale the machine size by a factor
-    g_field_temp = Simple(wout_filename=v.output_file, B_scale=B_scale, Aminor_scale=Aminor_scale, multharm=multharm,ns_s=ns_s,ns_tp=ns_tp)
-    final_loss_fraction_array = []
-    effective_time_array = []
-    for i in range(nruns_opt_average): # Average over a given number of runs
-        for j in range(0,3): # Try three times the same orbits, if not able continue
-            while True:
-                try:
-                    g_orbits_temp = ParticleEnsembleOrbit_Simple(g_particle,g_field_temp,tfinal=tfinal,nparticles=nparticles,nsamples=nsamples,notrace_passing=notrace_passing,nper=nper,npoiper=npoiper,npoiper2=npoiper2)
-                    final_loss_fraction_array.append(g_orbits_temp.total_particles_lost)
-                    lost_times_array = tfinal-g_field_temp.params.times_lost
-                    lost_times_array = lost_times_array[lost_times_array!=0.0]
-                    if np.asarray(lost_times_array).size==0: lost_times_array=[tfinal]
-                    effective_time_array.append(np.mean(lost_times_array)/(np.max(lost_times_array)+1e-9))
-                except ValueError as error_print:
-                    print(f'Try {j} of ParticleEnsembleOrbit_Simple gave error:',error_print)
-                    continue
-                break
-    final_loss_fraction = np.mean(final_loss_fraction_array)
-    final_effective_time = np.min([np.max([np.mean(effective_time_array),0]),10])
-    g_field_temp.simple_main.finalize()
-    mirror_ratio = MirrorRatioPen(v=v, output_mirror=True)
-    max_elongation = MaxElongationPen(vmec=v, return_elongation=True)
-    print(f'Loss = {(100*final_loss_fraction):1f}% with '
-    # + f'eff time = {final_effective_time:1f} (J={(final_effective_time*final_loss_fraction):1f}) and '
-    # + 'dofs = {v.x}, mean_iota={v.mean_iota()} and '
-    + f'mirror ratio={mirror_ratio:1f}, max elongation={max_elongation:1f} and '
-    + f'aspect ratio={v.aspect():1f} took {(time.time()-start_time):1f}s')
-    output_dofs_to_csv(v.x,v.mean_iota(),v.aspect(),final_loss_fraction,final_effective_time,mirror_ratio,max_elongation)
-    return final_loss_fraction
-    # return final_effective_time*final_loss_fraction
-optEP = make_optimizable(EPcostFunction, vmec)
-######################################
-try:
-    pprint("Initial aspect ratio:", vmec.aspect())
-    pprint("Initial mean iota:", vmec.mean_iota())
-    pprint("Initial magnetic well:", vmec.vacuum_well())
-    pprint("Initial mirror ratio:", MirrorRatioPen(v=vmec, output_mirror=True))
-    pprint("Initial max elongation:", MaxElongationPen(vmec=vmec, return_elongation=True))
-except Exception as e: pprint(e)
-if MPI.COMM_WORLD.rank == 0:
-    B_scale = 5.7/vmec.wout.b0/redux_B  # Scale the magnetic field by a factor
-    Aminor_scale = 1.7/vmec.wout.Aminor_p/redux_Aminor  # Scale the machine size by a factor
-    g_field = Simple(wout_filename=vmec.output_file, B_scale=B_scale, Aminor_scale=Aminor_scale, multharm=multharm,ns_s=ns_s,ns_tp=ns_tp)
-    g_orbits = ParticleEnsembleOrbit_Simple(g_particle,g_field,tfinal=tfinal,nparticles=nparticles,notrace_passing=notrace_passing,nper=nper,npoiper=npoiper,npoiper2=npoiper2)
-    pprint("Initial loss fraction:", g_orbits.total_particles_lost)
-######################################
-if QA_or_QH_or_QI == 'QA': qs = QuasisymmetryRatioResidual(vmec, np.arange(0, 1.01, 0.1), helicity_m=1, helicity_n=0)
-else: qs = QuasisymmetryRatioResidual(vmec, np.arange(0, 1.01, 0.1), helicity_m=1, helicity_n=-1)    
-opt_tuple = [(vmec.aspect, aspect_ratio_target, 1)]
-if opt_well: opt_tuple.append((vmec.vacuum_well, well_target, weight_opt_well))
-if opt_iota: opt_tuple.append((vmec.mean_iota, iota_target, 1))
-if opt_EP: opt_tuple.append((optEP.J, 0, weight_optEP))
-if opt_quasisymmetry: opt_tuple.append((qs.residuals, 0, 1))
-if opt_Mirror: opt_tuple.append((optMirror.J, 0, weight_opt_Mirror))
-if opt_Elongation: opt_tuple.append((optElongation.J, 0, weight_opt_Elongation))
-try: pprint("Quasisymmetry objective before optimization:", qs.total())
-except Exception as e: pprint(e)
-######################################
-initial_dofs=np.copy(surf.x)
-def fun(dofss):
-    # prob.x = initial_dofs
-    prob.x = dofss
-    return prob.objective()
-for max_mode in max_modes:
-    output_path_parameters=f'output_{optimizer}_{QA_or_QH_or_QI}_maxmode{max_mode}.csv'
-    surf.fix_all()
-    surf.fixed_range(mmin=0, mmax=max_mode, nmin=-max_mode, nmax=max_mode, fixed=False)
-    surf.fix("rc(0,0)")
-    initial_dofs=np.copy(surf.x)
-    dofs=surf.x
-    ######################################
-    prob = LeastSquaresProblem.from_tuples(opt_tuple)
-    if MPI.COMM_WORLD.rank == 0: pprint("Total objective before optimization:", prob.objective())
-    pprint('-------------------------')
-    pprint(f'Optimizing with max_mode = {max_mode}')
-    pprint('-------------------------')
-    if optimizer == 'minimize':
-        res = minimize(fun, dofs, method='BFGS', options={'maxiter': MAXITER}, tol=1e-9)
-    elif optimizer == 'dual_annealing':
-        initial_temp = 1000
-        visit = 2.0
-        no_local_search = False
-        # bounds = [(np.max([-10*np.abs(dof),-0.21]),np.min([0.21,10*np.abs(dof)])) for dof in dofs]
-        bounds = [(-0.25,0.25) for _ in dofs]
-        res = dual_annealing(fun, bounds=bounds, maxiter=MAXITER, initial_temp=initial_temp,visit=visit, no_local_search=no_local_search, x0=dofs)
-    elif optimizer == 'basinhopping':
-        stepsize_minimizer = 0.5
-        T_minimizer = 1.0
-        res = basinhopping(fun, dofs, niter=MAXITER, stepsize=stepsize_minimizer, T=T_minimizer, disp=True, minimizer_kwargs={"method": "BFGS"})
-    elif optimizer =='differential_evolution':
-        bounds = [(-0.25,0.25) for _ in dofs]
-        # bounds = [(np.max([-10*np.abs(dof),-0.21]),np.min([0.21,10*np.abs(dof)])) for dof in dofs]
-        res = differential_evolution(fun, bounds, maxiter=MAXITER, disp=True, x0=dofs)
-    elif optimizer == 'least_squares_diff':
-        least_squares_mpi_solve(prob, mpi, grad=True, rel_step=diff_rel_step, abs_step=diff_abs_step, max_nfev=MAXITER)
-    elif optimizer == 'least_squares':
-        least_squares_serial_solve(prob, rel_step=diff_rel_step, abs_step=diff_abs_step, max_nfev=MAXITER)
-    if optimizer in ['dual_annealing','minimize','basinhopping','differential_evolution']:
-        pprint(f"global minimum: x = {res.x}, f(x) = {res.fun}")
-        vmec.x = res.x
-    ######################################
-    if MPI.COMM_WORLD.rank == 0:
-        try: 
-            pprint("Final aspect ratio:", vmec.aspect())
-            pprint("Final mean iota:", vmec.mean_iota())
-            pprint("Final magnetic well:", vmec.vacuum_well())
-            pprint("Final mirror ratio:", MirrorRatioPen(v=vmec, output_mirror=True))
-            pprint("Final max elongation:", MaxElongationPen(vmec=vmec, return_elongation=True))
-            pprint("Quasisymmetry objective after optimization:", qs.total())
-            B_scale = 5.7/vmec.wout.b0/redux_B  # Scale the magnetic field by a factor
-            Aminor_scale = 1.7/vmec.wout.Aminor_p/redux_Aminor  # Scale the machine size by a factor
-            g_field = Simple(wout_filename=vmec.output_file, B_scale=B_scale, Aminor_scale=Aminor_scale,multharm=multharm,ns_s=ns_s,ns_tp=ns_tp)
-            g_orbits = ParticleEnsembleOrbit_Simple(g_particle,g_field,tfinal=tfinal,nparticles=nparticles,notrace_passing=notrace_passing,nper=nper,npoiper=npoiper,npoiper2=npoiper2)
-            pprint("Final loss fraction:", g_orbits.total_particles_lost)
-            pprint("Total objective after optimization:", prob.objective())
-        except Exception as e: pprint(e)
-    ######################################
-if MPI.COMM_WORLD.rank == 0:
-    try:
-        for objective_file in glob.glob("objective_*"):
-            os.remove(objective_file)
-        for residuals_file in glob.glob("residuals_*"):
-            os.remove(residuals_file)
-        for jac_file in glob.glob("jac_log_*"):
-            os.remove(jac_file)
-        for threed_file in glob.glob("threed1.*"):
-            os.remove(threed_file)
-        for threed_file in glob.glob("wout_*"):
-            os.remove(threed_file)
-        for threed_file in glob.glob("input.*"):
-            os.remove(threed_file)
-        os.remove('fort.6601')
-    except Exception as e:
-        pprint(e)
-    ##################################################
-    vmec.write_input(os.path.join(OUT_DIR, f'input.final'))
-######################################
-if plot_result and MPI.COMM_WORLD.rank==0:
-    vmec_final = Vmec(os.path.join(OUT_DIR, f'input.final'), mpi=mpi)
-    vmec_final.indata.ns_array[:3]    = [  16,    51,    101]#,   151,   201]
-    vmec_final.indata.niter_array[:3] = [ 4000, 10000,  4000]#,  5000, 10000]
-    vmec_final.indata.ftol_array[:3]  = [1e-12, 1e-13, 1e-14]#, 1e-15, 1e-15]
-    vmec_final.run()
-    shutil.move(os.path.join(OUT_DIR, f"wout_final_000_000000.nc"), os.path.join(OUT_DIR, f"wout_final.nc"))
-    os.remove(os.path.join(OUT_DIR, f'input.final_000_000000'))
-    try: vmecPlot2.main(file=os.path.join(OUT_DIR, f"wout_final.nc"), name='EP_opt', figures_folder=OUT_DIR)
-    except Exception as e: print(e)
-    pprint('Creating Boozer class for vmec_final')
-    b1 = Boozer(vmec_final, mpol=64, ntor=64)
-    boozxform_nsurfaces=10
-    pprint('Defining surfaces where to compute Boozer coordinates')
-    booz_surfaces = np.linspace(0,1,boozxform_nsurfaces,endpoint=False)
-    pprint(f' booz_surfaces={booz_surfaces}')
-    b1.register(booz_surfaces)
-    pprint('Running BOOZ_XFORM')
-    b1.run()
-    b1.bx.write_boozmn(os.path.join(OUT_DIR,"boozmn_single_stage.nc"))
-    pprint("Plot BOOZ_XFORM")
-    fig = plt.figure(); bx.surfplot(b1.bx, js=1,  fill=False, ncontours=35)
-    plt.savefig(os.path.join(OUT_DIR, "Boozxform_surfplot_1_single_stage.pdf"), bbox_inches = 'tight', pad_inches = 0); plt.close()
-    fig = plt.figure(); bx.surfplot(b1.bx, js=int(boozxform_nsurfaces/2), fill=False, ncontours=35)
-    plt.savefig(os.path.join(OUT_DIR, "Boozxform_surfplot_2_single_stage.pdf"), bbox_inches = 'tight', pad_inches = 0); plt.close()
-    fig = plt.figure(); bx.surfplot(b1.bx, js=boozxform_nsurfaces-1, fill=False, ncontours=35)
-    plt.savefig(os.path.join(OUT_DIR, "Boozxform_surfplot_3_single_stage.pdf"), bbox_inches = 'tight', pad_inches = 0); plt.close()
-    fig = plt.figure(); bx.symplot(b1.bx, helical_detail = True, sqrts=True)
-    plt.savefig(os.path.join(OUT_DIR, "Boozxform_symplot_single_stage.pdf"), bbox_inches = 'tight', pad_inches = 0); plt.close()
-    fig = plt.figure(); bx.modeplot(b1.bx, sqrts=True); plt.xlabel(r'$s=\psi/\psi_b$')
-    plt.savefig(os.path.join(OUT_DIR, "Boozxform_modeplot_single_stage.pdf"), bbox_inches = 'tight', pad_inches = 0); plt.close()
-############################################################################
-############################################################################
\ No newline at end of file
+if __name__ == "__main__":
+    main()
diff --git a/opt_parameters.csv b/opt_parameters.csv
new file mode 100644
index 0000000..7e5d680
--- /dev/null
+++ b/opt_parameters.csv
@@ -0,0 +1,21 @@
+QA_or_QH,s_initial,nparticles,tfinal,nsamples,multharm,ns_s,ns_tp,nper,npoiper,npoiper2,notrace_passing,nruns,duration_per_run,std_J,mean_J,coeff_variation
+QH,0.3,500,0.0005,3000,3,3,3,300,200,120,0,10,4.3166299104690555,0.0,0.31599999999999995,0.0
+QH,0.3,1500,0.0005,3000,3,3,3,300,200,120,0,10,7.704722118377686,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0015,3000,3,3,3,300,200,120,0,10,7.078237009048462,0.0,0.33199999999999996,0.0
+QH,0.3,500.0,0.0005,3000,3,3,3,900,200,120,0,10,11.012152767181396,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,600,120,0,10,12.169547772407531,5.551115123125783e-17,0.308,1.8023101049109684e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,200.0,360,0,10,7.485076951980591,0.0,0.31599999999999995,0.0
+QH,0.3,500,0.0005,3000,3,3,3,300,200,120,0,10,2.5855441331863402,0.0,0.31599999999999995,0.0
+QH,0.3,1500,0.0005,3000,3,3,3,300,200,120,0,10,4.096217155456543,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0015,3000,3,3,3,300,200,120,0,10,4.532854390144348,0.0,0.33199999999999996,0.0
+QH,0.3,500.0,0.0005,3000,3,3,3,900,200,120,0,10,6.513289213180542,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,600,120,0,10,6.728959965705871,5.551115123125783e-17,0.308,1.8023101049109684e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,200.0,360,0,10,3.819419097900391,0.0,0.31599999999999995,0.0
+QH,0.3,500.0,0.0005,9000,3,3,3,300.0,200.0,120.0,0,10,2.8247506380081178,5.551115123125783e-17,0.308,1.8023101049109684e-16
+QH,0.3,500,0.0005,3000,3,3,3,300,200,120,0,10,2.1508986234664915,0.0,0.31599999999999995,0.0
+QH,0.3,1500,0.0005,3000,3,3,3,300,200,120,0,10,3.249243974685669,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0015,3000,3,3,3,300,200,120,0,10,3.044373631477356,0.0,0.33199999999999996,0.0
+QH,0.3,500.0,0.0005,3000,3,3,3,900,200,120,0,10,5.110504889488221,5.551115123125783e-17,0.3200000000000001,1.7347234759768064e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,600,120,0,10,4.952587676048279,5.551115123125783e-17,0.308,1.8023101049109684e-16
+QH,0.3,500.0,0.0005,3000,3,3,3,300.0,200.0,360,0,10,3.2851766109466554,0.0,0.31599999999999995,0.0
+QH,0.3,500.0,0.0005,9000,3,3,3,300.0,200.0,120.0,0,10,2.356355142593384,5.551115123125783e-17,0.308,1.8023101049109684e-16
diff --git a/plot_opt.py b/plot_opt.py
index 170f67b..248dd01 100644
--- a/plot_opt.py
+++ b/plot_opt.py
@@ -33,11 +33,15 @@
 elif QA_or_QH == 'QH': nfp=4
 elif QA_or_QH == 'QI': nfp=3
 out_dir = f'out_s{s_initial}_NFP{nfp}'
+out_dir = os.environ.get('EP_OPT_OUT_DIR', out_dir)
+if not os.path.isdir(out_dir) and os.path.isdir(out_dir + '_smoke'):
+    out_dir = out_dir + '_smoke'
 out_csv = out_dir+f'/output_{optimizer}_{QA_or_QH}_maxmode{max_mode}.csv'
 df = pd.read_csv(out_csv)
 #################################
 if plt_opt_res:
-    df['aspect-6'] = df.apply(lambda row: np.abs(row.aspect - 7), axis=1)
+    aspect_target = 6 if QA_or_QH == 'QA' else 7 if QA_or_QH == 'QH' else 8
+    df['aspect-target'] = df.apply(lambda row: np.abs(row.aspect - aspect_target), axis=1)
     df['-iota'] = df.apply(lambda row: -np.abs(row.mean_iota), axis=1)
     df['iota'] = df.apply(lambda row: np.min([np.abs(row.mean_iota),1.5]), axis=1)
     df['normalized_time'] = df.apply(lambda row: np.min([np.max([np.mean(row.eff_time),0]),10]), axis=1)
@@ -56,7 +60,8 @@
     # plt.savefig(out_dir+'/loss_vs_normtime.pdf')
     # df.plot.scatter(y='loss_fraction', x='iota')
     # plt.savefig(out_dir+'/loss_vs_iota.pdf')
-    plt.show()
+    if os.environ.get('EP_OPT_SHOW', '0') == '1':
+        plt.show()
 #################################
 location_min = df['loss_fraction'].nsmallest(3).index[0] # chose the index to see smales, second smallest, etc
 df_min = df.iloc[location_min]
@@ -195,4 +200,4 @@
     plt.xlabel(r'$s=\psi/\psi_b$', fontsize=12)
     plt.ylabel(r'$\epsilon_{eff}$', fontsize=14)
     plt.tight_layout()
-    fig.savefig('neo_out.pdf', dpi=fig.dpi)#, bbox_inches = 'tight', pad_inches = 0)
\ No newline at end of file
+    fig.savefig('neo_out.pdf', dpi=fig.dpi)#, bbox_inches = 'tight', pad_inches = 0)
diff --git a/prime_direct_scbo.py b/prime_direct_scbo.py
new file mode 100755
index 0000000..b949dee
--- /dev/null
+++ b/prime_direct_scbo.py
@@ -0,0 +1,174 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+from pathlib import Path
+
+from build_direct_scbo_response import jeffreys_variance
+from evaluate_vmec_geometry import evaluate as evaluate_geometry
+
+
+def file_sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def observation(value: float, variance: float, geometry: dict) -> dict:
+    return {
+        "value": float(value),
+        "variance": float(variance),
+        "constraints": [float(value) for value in geometry["constraints"]],
+        "constraint_variances": [0.0, 0.0],
+    }
+
+
+def evaluation_row(candidate_id: int, unit_x: list[float], payload: dict) -> dict:
+    return {
+        "candidate_id": candidate_id,
+        "unit_x": [float(value) for value in unit_x],
+        "observation": payload,
+        "status": "ok",
+        "failure_kind": None,
+        "started_seconds": 0.0,
+        "completed_seconds": 0.0,
+        "worker_pid": 0,
+        "worker_thread": 0,
+    }
+
+
+def prime(args: argparse.Namespace) -> None:
+    from simsopt_dfo.scbo_checkpoint import (
+        issue_candidates,
+        prime_state,
+        write_checkpoint,
+    )
+
+    source = json.loads(args.validation_summary.read_text())
+    candidates = source["candidates"]
+    if not candidates:
+        raise ValueError("validation summary contains no candidates")
+    campaign = args.validation_summary.resolve().parents[2]
+    reference_fraction = float(candidates[0]["windows"]["total"]["reference_fraction"])
+    reference_particles = int(candidates[0]["windows"]["total"]["particles"])
+    reference_losses = round(reference_fraction * reference_particles)
+    reference_geometry = evaluate_geometry(
+        args.reference_wout,
+        mirror_limit=args.mirror_limit,
+        elongation_limit=args.elongation_limit,
+    )
+    rows = [
+        evaluation_row(
+            0,
+            [0.5] * len(candidates[0]["unit_x"]),
+            observation(
+                reference_fraction,
+                jeffreys_variance(reference_losses, reference_particles),
+                reference_geometry,
+            ),
+        )
+    ]
+    provenance = [
+        {
+            "candidate_id": 0,
+            "source": "reference",
+            "source_candidate_id": 0,
+            "wout_sha256": file_sha256(args.reference_wout),
+            "particles": reference_particles,
+            "total_loss": reference_fraction,
+            "geometry": reference_geometry,
+        }
+    ]
+    for candidate_id, candidate in enumerate(candidates, start=1):
+        wout = campaign / candidate["case_root"] / candidate["wout"]
+        if file_sha256(wout) != candidate["wout_sha256"]:
+            raise ValueError(f"candidate {candidate['candidate_id']} wout hash differs")
+        total = candidate["windows"]["total"]
+        particles = int(total["particles"])
+        value = float(total["candidate_fraction"])
+        losses = round(value * particles)
+        seed_variance = float(total["seed_se"]) ** 2
+        geometry = evaluate_geometry(
+            wout,
+            mirror_limit=args.mirror_limit,
+            elongation_limit=args.elongation_limit,
+        )
+        rows.append(
+            evaluation_row(
+                candidate_id,
+                candidate["unit_x"],
+                observation(
+                    value,
+                    max(seed_variance, jeffreys_variance(losses, particles)),
+                    geometry,
+                ),
+            )
+        )
+        provenance.append(
+            {
+                "candidate_id": candidate_id,
+                "source": "completed_multiseed_direct_validation",
+                "source_candidate_id": int(candidate["candidate_id"]),
+                "wout_sha256": candidate["wout_sha256"],
+                "particles": particles,
+                "total_loss": value,
+                "geometry": geometry,
+            }
+        )
+
+    configuration = {
+        "dimension": len(rows[0]["unit_x"]),
+        "constraint_count": 2,
+        "budget": len(rows) + args.new_calls,
+        "seed": args.seed,
+        "workers": args.workers,
+        "initial_points": len(rows),
+        "initial_length": args.initial_length,
+    }
+    state = prime_state(configuration, rows)
+    state, requests = issue_candidates(state)
+    write_checkpoint(args.state, state)
+    args.requests.write_text(
+        json.dumps({"requests": requests}, indent=2, sort_keys=True) + "\n"
+    )
+    args.priming.write_text(
+        json.dumps(
+            {
+                "schema_name": "alpha-loss.direct-scbo-priming",
+                "schema_version": 1,
+                "configuration": configuration,
+                "source_summary_sha256": file_sha256(args.validation_summary),
+                "constraint_names": ["mirror_ratio", "max_elongation"],
+                "constraint_limits": [args.mirror_limit, args.elongation_limit],
+                "observations": provenance,
+            },
+            indent=2,
+            sort_keys=True,
+            allow_nan=False,
+        )
+        + "\n"
+    )
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--validation-summary", type=Path, required=True)
+    root.add_argument("--reference-wout", type=Path, required=True)
+    root.add_argument("--state", type=Path, required=True)
+    root.add_argument("--requests", type=Path, required=True)
+    root.add_argument("--priming", type=Path, required=True)
+    root.add_argument("--new-calls", type=int, default=128)
+    root.add_argument("--workers", type=int, default=8)
+    root.add_argument("--seed", type=int, default=7301)
+    root.add_argument("--initial-length", type=float, default=0.4)
+    root.add_argument("--mirror-limit", type=float, default=0.20)
+    root.add_argument("--elongation-limit", type=float, default=6.0)
+    return root
+
+
+def main() -> None:
+    prime(parser().parse_args())
+
+
+if __name__ == "__main__":
+    main()
diff --git a/pyproject.toml b/pyproject.toml
new file mode 100644
index 0000000..fc9d19c
--- /dev/null
+++ b/pyproject.toml
@@ -0,0 +1,37 @@
+[project]
+name = "epoptimization"
+version = "0.1.0"
+description = "Energetic particle stellarator optimization driver"
+requires-python = ">=3.11"
+dependencies = [
+    "numpy",
+    "scipy",
+    "pandas",
+    "matplotlib",
+    "mpi4py",
+    "simsopt",
+    "booz-xform",
+    "netcdf4",
+    "pysimple",
+    "vmec",
+    "neatstel",
+    "h5py>=3.16.0",
+    "weightedpca",
+    "ground==9",
+    "bentley-ottmann==8",
+]
+
+[tool.uv]
+package = false
+
+[tool.uv.sources]
+pysimple = { path = "../SIMPLE", editable = true }
+vmec = { path = "../VMEC2000", editable = true }
+neatstel = { path = "../NEAT", editable = true }
+weightedpca = { git = "ssh://git@github.com/byoungj/weightedpca.git", rev = "6c7b83dd6b245f14dbdbb8abeff70f62f75ec8d8" }
+
+[dependency-groups]
+dev = [
+    "pytest>=9.1.1",
+    "ruff>=0.15.21",
+]
diff --git a/raw_fourier_surface.py b/raw_fourier_surface.py
new file mode 100644
index 0000000..29cf6a1
--- /dev/null
+++ b/raw_fourier_surface.py
@@ -0,0 +1,173 @@
+"""Non-data-informed low-order Fourier coordinates for optimizer comparisons."""
+
+from __future__ import annotations
+
+import json
+import hashlib
+import re
+from pathlib import Path
+
+import numpy as np
+from scipy import optimize
+
+_MODE = re.compile(r"(?:.*:)?(rc|zs)\((\d+),(-?\d+)\)$")
+
+
+def load_boundary(base_input: Path):
+    """Read the boundary straight from the VMEC input namelist.
+
+    ``simsopt.mhd.Vmec`` would also serve, but it requires the compiled VMEC2000
+    Python extension and mpi4py. Nothing here runs VMEC — equilibria are solved
+    by the standalone ``xvmec`` binary on the worker — so the pure-Python
+    surface reader is enough and keeps the driver free of that toolchain.
+    """
+    from simsopt.geo import SurfaceRZFourier
+
+    return SurfaceRZFourier.from_vmec_input(str(Path(base_input).resolve()))
+
+
+def write_vmec_input(base_input: Path, surface, path: Path) -> None:
+    """Write a VMEC input carrying ``surface`` and the base file's settings.
+
+    Only the boundary coefficient block is replaced. Resolution, pressure and
+    current profiles, and solver controls are inherited verbatim from the base
+    input, which ``SurfaceRZFourier.get_nml`` alone would drop.
+    """
+    boundary = [
+        line
+        for line in surface.get_nml().splitlines()
+        if line.strip().startswith(("RBC(", "ZBS("))
+    ]
+    if not boundary:
+        raise ValueError("surface namelist carries no boundary coefficients")
+    out: list[str] = []
+    inserted = False
+    for line in Path(base_input).read_text().splitlines():
+        if line.strip().startswith(("RBC(", "ZBS(")):
+            if not inserted:
+                out.extend(boundary)
+                inserted = True
+            continue
+        out.append(line.rstrip())
+    if not inserted:
+        raise ValueError(f"{base_input} carries no boundary block to replace")
+    Path(path).write_text("\n".join(out).rstrip() + "\n")
+
+
+def raw_coordinate_contract(base_input: Path, max_mode: int = 2) -> dict:
+    surface = load_boundary(base_input)
+    surface.fix_all()
+    surface.fixed_range(
+        mmin=0,
+        mmax=max_mode,
+        nmin=-max_mode,
+        nmax=max_mode,
+        fixed=False,
+    )
+    surface.fix("rc(0,0)")
+    names = [name.split(":", 1)[-1] for name in surface.dof_names]
+    center = np.asarray(surface.x, dtype=float)
+    scales = np.asarray([_mode_scale(name) for name in names])
+    return {
+        "schema_name": "alpha-loss.raw-fourier-contract",
+        "schema_version": 1,
+        "base_input_sha256": file_sha256(base_input),
+        "max_mode": max_mode,
+        "major_radius": float(surface.major_radius()),
+        "minor_radius": float(surface.minor_radius()),
+        "names": names,
+        "center": center.tolist(),
+        "half_width": scales.tolist(),
+    }
+
+
+def write_raw_candidate(
+    base_input: Path,
+    contract: dict,
+    unit_x: np.ndarray,
+    candidate_id: int,
+    output: Path,
+) -> dict:
+    unit = np.asarray(unit_x, dtype=float)
+    dimension = len(contract["names"])
+    if (
+        unit.shape != (dimension,)
+        or not np.isfinite(unit).all()
+        or np.any((unit < 0.0) | (unit > 1.0))
+    ):
+        raise ValueError("raw Fourier coordinates must lie in the unit box")
+    if file_sha256(base_input) != contract["base_input_sha256"]:
+        raise ValueError("raw Fourier base input hash differs")
+    surface = load_boundary(base_input)
+    values = np.asarray(contract["center"]) + (2.0 * unit - 1.0) * np.asarray(
+        contract["half_width"]
+    )
+    surface.unfix_all()
+    for name, value in zip(contract["names"], values, strict=True):
+        surface.set(name, float(value))
+    _enforce_radii(
+        surface,
+        float(contract["major_radius"]),
+        float(contract["minor_radius"]),
+    )
+    name = f"candidate-{candidate_id:08d}"
+    target = Path(output)
+    target.mkdir(parents=True, exist_ok=False)
+    request = {
+        "candidate_id": candidate_id,
+        "unit_x": unit.tolist(),
+        "case": name,
+    }
+    (target / "request.json").write_text(
+        json.dumps(request, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+    if surface.is_self_intersecting():
+        request.update({"status": "failed", "failure_kind": "self_intersection"})
+        return request
+    input_path = target / f"input.{name}"
+    write_vmec_input(base_input, surface, input_path)
+    normalize_vmec_input(input_path)
+    request.update(
+        {
+            "status": "ready",
+            "input": input_path.name,
+            "input_sha256": file_sha256(input_path),
+        }
+    )
+    return request
+
+
+def _mode_scale(name: str) -> float:
+    match = _MODE.fullmatch(name)
+    if match is None:
+        raise ValueError(f"unexpected Fourier degree of freedom {name}")
+    m = int(match.group(2))
+    n = int(match.group(3))
+    return 0.05 / (1.0 + m + abs(n))
+
+
+def _enforce_radii(surface, major_radius: float, minor_radius: float) -> None:
+    target_aspect = major_radius / minor_radius
+
+    def residual(value):
+        dofs = surface.x.copy()
+        dofs[0] = value
+        surface.x = dofs
+        return surface.aspect_ratio() - target_aspect
+
+    root = optimize.newton(residual, x0=major_radius)
+    residual(root)
+    surface.x = surface.x * (minor_radius / surface.minor_radius())
+
+
+def file_sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with Path(path).open("rb") as stream:
+        for block in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def normalize_vmec_input(path: Path) -> None:
+    lines = [line.rstrip() for line in Path(path).read_text().splitlines()]
+    Path(path).write_text("\n".join(lines).rstrip() + "\n")
diff --git a/run_barrier_candidate.sh b/run_barrier_candidate.sh
new file mode 100755
index 0000000..3aa9414
--- /dev/null
+++ b/run_barrier_candidate.sh
@@ -0,0 +1,85 @@
+#!/bin/bash
+set -Eeuo pipefail
+
+index=${1:?candidate manifest index required}
+wave_root=$CAMPAIGN_ROOT/$WAVE
+line=$(sed -n "$((index + 1))p" "$wave_root/manifest.tsv")
+IFS=$'\t' read -r case_name relative_input input_sha <<< "$line"
+test -n "$case_name"
+case_root=$wave_root/candidates/$case_name
+input_name=$(basename "$relative_input")
+
+failure_kind=worker_failure
+failure_response() {
+    if ! test -f "$case_root/response.json"; then
+        python3 "$CODE_ROOT/build_barrier_scbo_response.py" \
+            --request "$case_root/request.json" \
+            --out "$case_root/response.json" \
+            --failure-kind "$failure_kind"
+    fi
+}
+trap failure_response ERR
+
+test "$(sha256sum "$wave_root/candidates/$relative_input" | cut -d' ' -f1)" = "$input_sha"
+test "$(sha256sum "$XVMEC" | cut -d' ' -f1)" = "$XVMEC_SHA256"
+test "$(sha256sum "$SIMPLE_X" | cut -d' ' -f1)" = "$SIMPLE_SHA256"
+test "$(sha256sum "$CODE_MANIFEST" | cut -d' ' -f1)" = "$CODE_MANIFEST_SHA256"
+(cd "$CODE_ROOT" && sha256sum -c "$CODE_MANIFEST")
+
+failure_kind=equilibrium_failure
+set +e
+(cd "$case_root" && timeout "${VMEC_TIMEOUT_SECONDS:-600}" "$XVMEC" "$input_name" > vmec.stdout 2>&1)
+vmec_exit=$?
+set -e
+if test "$vmec_exit" -ne 0 || ! grep -q "EXECUTION TERMINATED NORMALLY" "$case_root/vmec.stdout"; then
+    trap - ERR
+    failure_response
+    exit 0
+fi
+
+wout=$case_root/wout_${case_name}.nc
+wout_sha=$(sha256sum "$wout" | cut -d' ' -f1)
+
+failure_kind=geometry_failure
+python3 "$CODE_ROOT/evaluate_vmec_geometry.py" \
+    --wout "$wout" \
+    --mirror-limit "${MIRROR_LIMIT:-0.20}" \
+    --elongation-limit "${ELONGATION_LIMIT:-6.0}" \
+    --out "$case_root/geometry.json"
+
+failure_kind=barrier_overlap_failure
+export OMP_NUM_THREADS=$ALLOCATED_CPUS
+python3 "$CODE_ROOT/evaluate_barrier_overlap.py" \
+    --wout "$wout" \
+    --wout-sha256 "$wout_sha" \
+    --out "$case_root/barrier_result" \
+    --simple-executable "$SIMPLE_X" \
+    --simple-sha256 "$SIMPLE_SHA256" \
+    --work-root "${CLASSIFIER_WORK_ROOT:-$case_root/classifier-work}" \
+    --surfaces "${SURFACES:-0.25,0.4,0.55,0.7}" \
+    --ntheta "${NTHETA:-8}" \
+    --nzeta "${NZETA:-8}" \
+    --npitch "${NPITCH:-16}" \
+    --mu-nodes "${MU_NODES:-24}" \
+    --trace-time "${TRACE_TIME:-0.02}" \
+    --prompt-time "${PROMPT_TIME:-0.001}" \
+    --nturns "${NTURNS:-8}" \
+    --seed "${PARTICLE_SEED:-12345}" \
+    --trapped-width "${TRAPPED_WIDTH:-0.15}" \
+    --mu-width-factor "${MU_WIDTH_FACTOR:-0.75}" \
+    --jpar-temperature "${JPAR_TEMPERATURE:-0.1}" \
+    --rotation-temperature "${ROTATION_TEMPERATURE:-0.02}" \
+    --timeout "${SIMPLE_TIMEOUT_SECONDS:-3600}"
+
+failure_kind=response_failure
+python3 "$CODE_ROOT/build_barrier_scbo_response.py" \
+    --request "$case_root/request.json" \
+    --result "$case_root/barrier_result/result.json" \
+    --geometry "$case_root/geometry.json" \
+    --inner-surface "${INNER_SURFACE:-0.25}" \
+    --outer-surface "${OUTER_SURFACE:-0.7}" \
+    --particles-per-surface "$(( ${NTHETA:-8} * ${NZETA:-8} * ${NPITCH:-16} ))" \
+    --prompt-limit "${PROMPT_LIMIT:-0.05}" \
+    --objective "${OBJECTIVE:-barrier-jpar}" \
+    --out "$case_root/response.json"
+trap - ERR
diff --git a/run_direct_scbo_candidate.sh b/run_direct_scbo_candidate.sh
new file mode 100755
index 0000000..0e90516
--- /dev/null
+++ b/run_direct_scbo_candidate.sh
@@ -0,0 +1,75 @@
+#!/bin/bash
+set -Eeuo pipefail
+
+index=${1:?candidate manifest index required}
+wave_root=$CAMPAIGN_ROOT/$WAVE
+line=$(sed -n "$((index + 1))p" "$wave_root/manifest.tsv")
+IFS=$'\t' read -r case_name relative_input input_sha <<< "$line"
+test -n "$case_name"
+case_root=$wave_root/candidates/$case_name
+input_name=$(basename "$relative_input")
+
+failure_kind=worker_failure
+failure_response() {
+    if ! test -f "$case_root/response.json"; then
+        python3 "$CODE_ROOT/build_direct_scbo_response.py" \
+            --request "$case_root/request.json" \
+            --out "$case_root/response.json" \
+            --failure-kind "$failure_kind"
+    fi
+}
+trap failure_response ERR
+
+test "$(sha256sum "$wave_root/candidates/$relative_input" | cut -d' ' -f1)" = "$input_sha"
+test "$(sha256sum "$XVMEC" | cut -d' ' -f1)" = "$XVMEC_SHA256"
+test "$(sha256sum "$SIMPLE_X" | cut -d' ' -f1)" = "$SIMPLE_SHA256"
+test "$(sha256sum "$CODE_MANIFEST" | cut -d' ' -f1)" = "$CODE_MANIFEST_SHA256"
+(cd "$CODE_ROOT" && sha256sum -c "$CODE_MANIFEST")
+
+failure_kind=equilibrium_failure
+set +e
+(cd "$case_root" && timeout "${VMEC_TIMEOUT_SECONDS:-600}" "$XVMEC" "$input_name" > vmec.stdout 2>&1)
+vmec_exit=$?
+set -e
+if test "$vmec_exit" -ne 0 || ! grep -q "EXECUTION TERMINATED NORMALLY" "$case_root/vmec.stdout"; then
+    trap - ERR
+    failure_response
+    exit 0
+fi
+
+wout=$case_root/wout_${case_name}.nc
+wout_sha=$(sha256sum "$wout" | cut -d' ' -f1)
+
+failure_kind=geometry_failure
+python3 "$CODE_ROOT/evaluate_vmec_geometry.py" \
+    --wout "$wout" \
+    --mirror-limit "${MIRROR_LIMIT:-0.20}" \
+    --elongation-limit "${ELONGATION_LIMIT:-6.0}" \
+    --out "$case_root/geometry.json"
+
+failure_kind=direct_loss_failure
+export OMP_NUM_THREADS=$ALLOCATED_CPUS
+python3 "$CODE_ROOT/evaluate_direct_loss.py" \
+    --wout "$wout" \
+    --wout-sha256 "$wout_sha" \
+    --out "$case_root/direct_result" \
+    --simple-executable "$SIMPLE_X" \
+    --simple-sha256 "$SIMPLE_SHA256" \
+    --particles "${PARTICLES:-256}" \
+    --seed "${PARTICLE_SEED:-12345}" \
+    --birth-surface "${BIRTH_SURFACE:-0.25}" \
+    --prompt-time "${PROMPT_TIME:-0.001}" \
+    --trace-time "${TRACE_TIME:-0.1}" \
+    --timeout "${SIMPLE_TIMEOUT_SECONDS:-900}"
+
+failure_kind=response_failure
+python3 "$CODE_ROOT/build_direct_scbo_response.py" \
+    --request "$case_root/request.json" \
+    --result "$case_root/direct_result/result.json" \
+    --geometry "$case_root/geometry.json" \
+    --particles "${PARTICLES:-256}" \
+    --seed "${PARTICLE_SEED:-12345}" \
+    --birth-surface "${BIRTH_SURFACE:-0.25}" \
+    --trace-time "${TRACE_TIME:-0.1}" \
+    --out "$case_root/response.json"
+trap - ERR
diff --git a/run_optimizer_comparison.py b/run_optimizer_comparison.py
new file mode 100755
index 0000000..a00deed
--- /dev/null
+++ b/run_optimizer_comparison.py
@@ -0,0 +1,303 @@
+#!/usr/bin/env python3
+"""Run one raw-Fourier optimizer against externally scheduled direct evaluations."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import subprocess
+from pathlib import Path
+
+import numpy as np
+
+from raw_fourier_surface import raw_coordinate_contract, write_raw_candidate
+
+
+class ClusterObjective:
+    def __init__(self, args: argparse.Namespace, contract: dict):
+        self.args = args
+        self.contract = contract
+        self.root = args.root.resolve()
+        self.method_root = self.root / args.method
+        self.method_root.mkdir(parents=True, exist_ok=False)
+        self.ledger_path = self.method_root / "ledger.json"
+        self.records: list[dict] = []
+
+    def __call__(self, unit_x) -> float:
+        if len(self.records) >= self.args.budget:
+            return min(row["penalized_value"] for row in self.records)
+        candidate_id = len(self.records)
+        unit = np.clip(np.asarray(unit_x, dtype=float), 0.0, 1.0)
+        wave = f"{self.args.method}/eval-{candidate_id:03d}"
+        wave_root = self.root / wave
+        case_name = f"candidate-{candidate_id:08d}"
+        case_root = wave_root / "candidates" / case_name
+        generated = write_raw_candidate(
+            self.args.base_input,
+            self.contract,
+            unit,
+            candidate_id,
+            case_root,
+        )
+        if generated["status"] != "ready":
+            response = {
+                "candidate_id": candidate_id,
+                "unit_x": unit.tolist(),
+                "status": "failed",
+                "failure_kind": generated["failure_kind"],
+                "observation": None,
+            }
+            (case_root / "response.json").write_text(
+                json.dumps(response, indent=2, sort_keys=True) + "\n"
+            )
+            return self._record(response, None)
+        relative = f"{case_name}/{generated['input']}"
+        (wave_root / "manifest.tsv").write_text(
+            f"{case_name}\t{relative}\t{generated['input_sha256']}\n"
+        )
+        (wave_root / "logs").mkdir()
+        remote_wave = f"{self.args.remote}/campaign/{wave}"
+        _run(["ssh", self.args.host, "mkdir", "-p", f"{remote_wave}/logs"])
+        _run(
+            [
+                "rsync",
+                "-az",
+                "--exclude",
+                "logs/",
+                f"{wave_root}/",
+                f"{self.args.host}:{remote_wave}/",
+            ]
+        )
+        submitted = subprocess.run(
+            [
+                "ssh",
+                self.args.host,
+                "cd",
+                self.args.remote,
+                "&&",
+                "sbatch",
+                "--wait",
+                "--parsable",
+                f"--export=ALL,METHOD={self.args.method},"
+                f"EVAL={candidate_id:03d},METRIC={self.args.metric}",
+                f"--output={remote_wave}/logs/%j.out",
+                "run_single.sbatch",
+            ],
+            text=True,
+            capture_output=True,
+            check=False,
+        )
+        job_id = submitted.stdout.strip().split(";", 1)[0]
+        (wave_root / "job.id").write_text(job_id + "\n")
+        _run(
+            [
+                "rsync",
+                "-az",
+                f"{self.args.host}:{remote_wave}/candidates/",
+                f"{wave_root}/candidates/",
+            ]
+        )
+        response_path = case_root / "response.json"
+        if not response_path.exists():
+            response = {
+                "candidate_id": candidate_id,
+                "unit_x": unit.tolist(),
+                "status": "failed",
+                "failure_kind": "scheduler_failure",
+                "observation": None,
+            }
+        else:
+            response = json.loads(response_path.read_text())
+        return self._record(response, job_id)
+
+    def _record(self, response: dict, job_id: str | None) -> float:
+        observation = response.get("observation")
+        if observation is None:
+            penalty = 2.0
+        else:
+            violation = np.maximum(np.asarray(observation["constraints"]), 0.0)
+            penalty = float(observation["value"] + 10.0 * np.dot(violation, violation))
+        record = {
+            "evaluation_id": len(self.records),
+            "job_id": job_id,
+            "unit_x": response["unit_x"],
+            "status": response["status"],
+            "failure_kind": response.get("failure_kind"),
+            "observation": observation,
+            "penalized_value": penalty,
+        }
+        self.records.append(record)
+        _atomic_json(
+            self.ledger_path,
+            {
+                "schema_name": "alpha-loss.optimizer-comparison-ledger",
+                "schema_version": 2,
+                "method": self.args.method,
+                "metric": self.args.metric,
+                "budget": self.args.budget,
+                "seed": self.args.seed,
+                "records": self.records,
+            },
+        )
+        return penalty
+
+
+def run_turbo(
+    objective: ClusterObjective, args: argparse.Namespace, dimension: int
+) -> dict:
+    from simsopt_dfo.scbo_checkpoint import (
+        complete_candidates,
+        issue_candidates,
+        prime_state,
+        write_checkpoint,
+    )
+
+    anchor = np.full(dimension, 0.5)
+    objective(anchor)
+    response = _response_from_record(objective.records[0])
+    observation = response["observation"]
+    if observation is None:
+        raise RuntimeError("the anchor evaluation failed; cannot prime TuRBO")
+    state = prime_state(
+        {
+            "dimension": dimension,
+            "constraint_count": len(observation["constraints"]),
+            "budget": args.budget,
+            "seed": args.seed,
+            "workers": 1,
+            "initial_points": min(2 * dimension, args.budget - 1),
+            "initial_length": 0.8,
+        },
+        [response],
+    )
+    checkpoint = objective.method_root / "state.json"
+    while len(objective.records) < args.budget:
+        state, requests = issue_candidates(state)
+        request = requests[0]
+        objective(request["unit_x"])
+        state = complete_candidates(
+            state, [_response_from_record(objective.records[-1])]
+        )
+        write_checkpoint(checkpoint, state)
+    best = min(
+        (row for row in objective.records if row["observation"] is not None),
+        key=lambda row: row["penalized_value"],
+    )
+    return {"best": best, "trust_region": state["trust_region"]}
+
+
+def run_dual_annealing(
+    objective: ClusterObjective, args: argparse.Namespace, dimension: int
+) -> dict:
+    from scipy.optimize import dual_annealing
+
+    result = dual_annealing(
+        objective,
+        [(0.0, 1.0)] * dimension,
+        x0=np.full(dimension, 0.5),
+        seed=args.seed,
+        maxiter=10_000,
+        maxfun=args.budget,
+        no_local_search=False,
+    )
+    return {
+        "best": min(objective.records, key=lambda row: row["penalized_value"]),
+        "termination": {"message": str(result.message), "nfev": int(result.nfev)},
+    }
+
+
+def run_bobyqa(
+    objective: ClusterObjective, args: argparse.Namespace, dimension: int
+) -> dict:
+    import pybobyqa
+
+    result = pybobyqa.solve(
+        objective,
+        np.full(dimension, 0.5),
+        bounds=(np.zeros(dimension), np.ones(dimension)),
+        maxfun=args.budget,
+        rhobeg=0.2,
+        rhoend=0.01,
+        seek_global_minimum=False,
+        print_progress=False,
+    )
+    return {
+        "best": min(objective.records, key=lambda row: row["penalized_value"]),
+        "termination": {"message": str(result.msg), "nfev": int(result.nf)},
+    }
+
+
+def _response_from_record(record: dict) -> dict:
+    return {
+        "candidate_id": record["evaluation_id"],
+        "unit_x": record["unit_x"],
+        "status": record["status"],
+        "failure_kind": record["failure_kind"],
+        "observation": record["observation"],
+    }
+
+
+def _atomic_json(path: Path, document: dict) -> None:
+    temporary = path.with_suffix(".tmp")
+    temporary.write_text(
+        json.dumps(document, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+    os.replace(temporary, path)
+
+
+def _run(command: list[str]) -> None:
+    subprocess.run(command, check=True)
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument(
+        "--method", choices=("turbo", "dual-annealing", "bobyqa"), required=True
+    )
+    root.add_argument("--root", type=Path, required=True)
+    root.add_argument("--base-input", type=Path, required=True)
+    root.add_argument("--budget", type=int, default=64)
+    root.add_argument("--seed", type=int, required=True)
+    root.add_argument(
+        "--metric",
+        choices=("direct-loss", "barrier-overlap"),
+        default="barrier-overlap",
+        help="objective evaluated on the cluster for each candidate",
+    )
+    root.add_argument("--host", default="acluster")
+    root.add_argument("--remote", default="/home/ert/runs/alpha-optimizer-methods-v1")
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    contract = raw_coordinate_contract(args.base_input)
+    args.root.mkdir(parents=True, exist_ok=True)
+    contract_path = args.root / "raw-fourier-contract.json"
+    if contract_path.exists() and json.loads(contract_path.read_text()) != contract:
+        raise ValueError("raw Fourier comparison contract changed")
+    contract_path.write_text(json.dumps(contract, indent=2, sort_keys=True) + "\n")
+    objective = ClusterObjective(args, contract)
+    runners = {
+        "turbo": run_turbo,
+        "dual-annealing": run_dual_annealing,
+        "bobyqa": run_bobyqa,
+    }
+    result = runners[args.method](objective, args, len(contract["names"]))
+    _atomic_json(
+        objective.method_root / "result.json",
+        {
+            "schema_name": "alpha-loss.optimizer-comparison-result",
+            "schema_version": 2,
+            "method": args.method,
+            "metric": args.metric,
+            "budget": args.budget,
+            "seed": args.seed,
+            **result,
+        },
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/run_single.sbatch b/run_single.sbatch
new file mode 100644
index 0000000..6e9e830
--- /dev/null
+++ b/run_single.sbatch
@@ -0,0 +1,41 @@
+#!/bin/bash
+#SBATCH --job-name=alpha-barrier
+#SBATCH --partition=compute
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --cpus-per-task=16
+#SBATCH --time=04:00:00
+set -Eeuo pipefail
+
+# One optimizer candidate. The driver exports METHOD, EVAL and METRIC.
+: "${METHOD:?METHOD is required}"
+: "${EVAL:?EVAL is required}"
+METRIC=${METRIC:-barrier-overlap}
+
+# The driver submits over ssh, so --export=ALL carries only that session's
+# environment. The campaign pins its toolchain here.
+if [ -f "$SLURM_SUBMIT_DIR/env.sh" ]; then
+    # shellcheck source=/dev/null
+    source "$SLURM_SUBMIT_DIR/env.sh"
+fi
+
+export CAMPAIGN_ROOT=${CAMPAIGN_ROOT:-$SLURM_SUBMIT_DIR/campaign}
+export WAVE="$METHOD/eval-$EVAL"
+export CODE_ROOT=${CODE_ROOT:-$HOME/code/EPoptimization}
+export ALLOCATED_CPUS=${SLURM_CPUS_PER_TASK:-16}
+export OMP_NUM_THREADS=$ALLOCATED_CPUS
+
+export XVMEC=${XVMEC:?XVMEC is required}
+export XVMEC_SHA256=${XVMEC_SHA256:?XVMEC_SHA256 is required}
+export SIMPLE_X=${SIMPLE_X:?SIMPLE_X is required}
+export SIMPLE_SHA256=${SIMPLE_SHA256:?SIMPLE_SHA256 is required}
+export CODE_MANIFEST=${CODE_MANIFEST:?CODE_MANIFEST is required}
+export CODE_MANIFEST_SHA256=${CODE_MANIFEST_SHA256:?CODE_MANIFEST_SHA256 is required}
+
+case "$METRIC" in
+    barrier-overlap) worker=run_barrier_candidate.sh ;;
+    direct-loss)     worker=run_direct_scbo_candidate.sh ;;
+    *) echo "unknown METRIC: $METRIC" >&2; exit 2 ;;
+esac
+
+bash "$CODE_ROOT/$worker" 0
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/manifest.json b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/manifest.json
new file mode 100644
index 0000000..92703e9
--- /dev/null
+++ b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/manifest.json
@@ -0,0 +1,99 @@
+{
+  "b_scale": 5.870331735243639,
+  "coordinate_convention": "SIMPLE Boozer angles mapped to VMEC reference starts",
+  "input_kind": "boozer_chartmap",
+  "invariant_calibration": "same executable, same point, 10 microsecond trace",
+  "lambda_definition": "mu * 5.865 T / E",
+  "mpol": 16,
+  "nmu": 9,
+  "ntheta": 16,
+  "ntor": 16,
+  "nzeta": 16,
+  "records": [
+    {
+      "design_sha256": "79d948c848c8ee415f54dba9758e5891732baaf4472b940e80003268216995da",
+      "name": "s0p25000",
+      "particles": 9216,
+      "start_sha256": "b3bcce85090fa47c95f9b76b1c10cf022f222ecd821e41afb5f324bbe78da097",
+      "surface": 0.25
+    },
+    {
+      "design_sha256": "5a8a87d97469cc90bf7ba228ac89c8cbfbb5c73e17d1c5de372ff21ab9a31ace",
+      "name": "s0p30000",
+      "particles": 9216,
+      "start_sha256": "df72a737cc4f29876c122ab1ebacaa330a01840ba1aa6a58813b8e6cc34f9005",
+      "surface": 0.3
+    },
+    {
+      "design_sha256": "c973598b5cdcac54169c2fa734c8c2f52bb4f0fc3a825f5061f35c53cb58d8f5",
+      "name": "s0p42500",
+      "particles": 9216,
+      "start_sha256": "c2ecf50abe312fa0b68262813f7439674b9c35ea2d40f25c4257d52a91ae97dc",
+      "surface": 0.425
+    },
+    {
+      "design_sha256": "7630560d0bbc43a90c9bd819e336bc83eaf35b14a2ace940296aa7804f9ac67d",
+      "name": "s0p44062",
+      "particles": 9216,
+      "start_sha256": "4198ce838f98ba4d6d79811c9071f440e14ab57ca0f0281d5701a0143b9752fe",
+      "surface": 0.440625
+    },
+    {
+      "design_sha256": "ae9590f82332109d34a6805ea9478bd9e6f52adc70111e84c715485efa99c856",
+      "name": "s0p45625",
+      "particles": 9216,
+      "start_sha256": "fc0aa41893a9c4b31ae89ee3f332bd171e0dcb5ebf3705c48da11621b95dce94",
+      "surface": 0.45625
+    },
+    {
+      "design_sha256": "14385962fd2d86385e670ab15b78afb749191660e05c041c005f3f629a355e87",
+      "name": "s0p48750",
+      "particles": 9216,
+      "start_sha256": "a6cca86ce3b9267878caffe731b7dc8a7daddea3d917d0eb0f3890a18caccb16",
+      "surface": 0.4875
+    },
+    {
+      "design_sha256": "0b3c539d739574ee75fe5efd72266ba0d6783a44d03d1662e29407cc4d349059",
+      "name": "s0p51875",
+      "particles": 9216,
+      "start_sha256": "397300efc690883f62f38acd4ba78f90b3c58c9c5152b6fa4c2306ecae223b7c",
+      "surface": 0.51875
+    },
+    {
+      "design_sha256": "5fc6de2f13beb6e30b0f21f0c8c1014e5d3eef480422b195e7064a690f829560",
+      "name": "s0p55000",
+      "particles": 9216,
+      "start_sha256": "388f1d0574a5b5f5c2553a6f9a5c1b276de6af14640edaa20a0de06f4cd5e51b",
+      "surface": 0.55
+    },
+    {
+      "design_sha256": "4110cec1541985a01c0c1da5d27aa8b5ed9068c8666ed7b8a31277adab0dd4c1",
+      "name": "s0p61250",
+      "particles": 9216,
+      "start_sha256": "2647c223f3be108aaf2e4b79d017a259986f3d1f3092428f1d7be757653ad0ef",
+      "surface": 0.6125
+    },
+    {
+      "design_sha256": "5f57517ee5c0ec4101564e1ea11313aefc50ee5fcb176be49cc516941488bfc3",
+      "name": "s0p67500",
+      "particles": 9216,
+      "start_sha256": "aa03f96df8d5dcf3f77ae3234d82218d347ca5714bb13ba84e16e9f6a3259ec8",
+      "surface": 0.675
+    },
+    {
+      "design_sha256": "09245c45405b25426637c30c4cfb0c5d76ba3e8540feb3c114b4d82a3f6d3d40",
+      "name": "s0p80000",
+      "particles": 9216,
+      "start_sha256": "779c7d67e899ff7f44b8cb0dea3d139cdd603b8b2244a16815d4ee7883fdebc5",
+      "surface": 0.8
+    }
+  ],
+  "rz_scale": 10.1265838202802,
+  "schema_name": "alpha-loss.spatial-topology-design",
+  "schema_version": 1,
+  "shifts": [
+    0.0,
+    0.5
+  ],
+  "wout_sha256": "2c0f1d9914997b214aa095181af0ea6c3e4f9f9af67204f67877cd0ee1fe56bc"
+}
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/design.npz
new file mode 100644
index 0000000..e4e3ce0
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/start.dat
new file mode 100644
index 0000000..a644d00
--- /dev/null
+++ b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p25000/start.dat
@@ -0,0 +1,9216 @@
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p30000/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p30000/design.npz
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index 0000000..ba212ad
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p30000/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p30000/start.dat
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p42500/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p42500/design.npz
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index 0000000..6082578
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p42500/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p42500/start.dat
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--- /dev/null
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p44062/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p44062/design.npz
new file mode 100644
index 0000000..b2a0ab1
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p44062/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p44062/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p44062/start.dat
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index 0000000..82d1192
--- /dev/null
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p45625/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p45625/design.npz
new file mode 100644
index 0000000..2a520e7
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p45625/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p45625/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p45625/start.dat
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--- /dev/null
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p48750/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p48750/design.npz
new file mode 100644
index 0000000..877e2f1
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p48750/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p48750/start.dat
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p51875/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p51875/design.npz
new file mode 100644
index 0000000..4d07817
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p51875/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p51875/start.dat
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p55000/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p55000/design.npz
new file mode 100644
index 0000000..425ad66
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p55000/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p55000/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p55000/start.dat
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index 0000000..8d266ff
--- /dev/null
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/design.npz
new file mode 100644
index 0000000..60e0b11
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/start.dat
new file mode 100644
index 0000000..6010a3f
--- /dev/null
+++ b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p61250/start.dat
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p67500/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p67500/design.npz
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index 0000000..99b52a0
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p67500/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p67500/start.dat
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diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p80000/design.npz b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p80000/design.npz
new file mode 100644
index 0000000..e454044
Binary files /dev/null and b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p80000/design.npz differ
diff --git a/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p80000/start.dat b/runs/plasma_simple_proxy_correlation_v1/cases/plunk_beta03/design/s0p80000/start.dat
new file mode 100644
index 0000000..c57fc1d
--- /dev/null
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diff --git a/scbo_backend.py b/scbo_backend.py
new file mode 100644
index 0000000..7b08aab
--- /dev/null
+++ b/scbo_backend.py
@@ -0,0 +1,219 @@
+from __future__ import annotations
+
+import argparse
+import json
+import shlex
+import subprocess
+from pathlib import Path
+
+
+def runnable_nodes(snapshot: str, required_cpus: int = 48) -> list[str]:
+    nodes = []
+    for line in snapshot.splitlines():
+        if not line.strip():
+            continue
+        name, state, counts = line.split("|", 2)
+        _, idle, _, _ = (int(value) for value in counts.split("/"))
+        if state.rstrip("*") in {"idle", "mix"} and idle >= required_cpus:
+            nodes.append(name)
+    return nodes
+
+
+def choose_backend(snapshot: str, workers: int = 8, required_cpus: int = 48) -> str:
+    return "slurm" if len(runnable_nodes(snapshot, required_cpus)) >= workers else "condor"
+
+
+def _condor_environment(values: dict[str, str]) -> str:
+    items = [f"{key}={value}" for key, value in sorted(values.items())]
+    if any('"' in item or "\n" in item for item in items):
+        raise ValueError("Condor environment values cannot contain quotes or newlines")
+    return " ".join(items)
+
+
+def condor_submit_text(
+    *,
+    executable: Path,
+    campaign_root: Path,
+    wave: str,
+    environment: dict[str, str],
+    jobs: int,
+    cpus: int,
+    memory_mb: int,
+    max_materialize: int | None = None,
+) -> str:
+    if jobs <= 0 or cpus <= 0 or memory_mb <= 0:
+        raise ValueError("jobs, cpus, and memory must be positive")
+    if max_materialize is not None and max_materialize <= 0:
+        raise ValueError("max_materialize must be positive")
+    logs = campaign_root / wave / "logs"
+    merged = {
+        **environment,
+        "ALLOCATED_CPUS": str(cpus),
+        "CAMPAIGN_ROOT": str(campaign_root),
+        "WAVE": wave,
+    }
+    lines = [
+        "universe = vanilla",
+        f"executable = {executable}",
+        "arguments = $(Process)",
+        f"initialdir = {campaign_root}",
+        f'environment = "{_condor_environment(merged)}"',
+        f"request_cpus = {cpus}",
+        f"request_memory = {memory_mb}MB",
+        'requirements = (OpSys == "LINUX") && (Arch == "X86_64")',
+        "should_transfer_files = NO",
+        "getenv = False",
+        f"output = {logs}/condor_$(Cluster)_$(Process).out",
+        f"error = {logs}/condor_$(Cluster)_$(Process).err",
+        f"log = {logs}/condor_$(Cluster).log",
+        "notification = Never",
+    ]
+    if max_materialize is not None:
+        lines.append(f"max_materialize = {max_materialize}")
+    lines.extend([f"queue {jobs}", ""])
+    return "\n".join(lines)
+
+
+def slurm_array_text(
+    *,
+    executable: Path,
+    campaign_root: Path,
+    wave: str,
+    environment: dict[str, str],
+    jobs: int,
+    cpus: int,
+    memory_mb: int,
+    time_limit: str,
+    max_concurrent: int,
+) -> str:
+    if min(jobs, cpus, memory_mb, max_concurrent) <= 0:
+        raise ValueError("jobs, resources, and concurrency must be positive")
+    if not time_limit or "\n" in time_limit:
+        raise ValueError("time limit must be one nonempty line")
+    merged = {
+        **environment,
+        "ALLOCATED_CPUS": str(cpus),
+        "CAMPAIGN_ROOT": str(campaign_root),
+        "WAVE": wave,
+    }
+    for key in merged:
+        if not key.isidentifier():
+            raise ValueError(f"invalid environment key {key}")
+    logs = campaign_root / wave / "logs"
+    lines = [
+        "#!/bin/bash",
+        f"#SBATCH --array=0-{jobs - 1}%{max_concurrent}",
+        "#SBATCH --nodes=1",
+        "#SBATCH --ntasks=1",
+        f"#SBATCH --cpus-per-task={cpus}",
+        f"#SBATCH --mem={memory_mb}M",
+        f"#SBATCH --time={time_limit}",
+        f"#SBATCH --output={logs}/slurm_%A_%a.out",
+        f"#SBATCH --error={logs}/slurm_%A_%a.err",
+        "set -euo pipefail",
+        "",
+    ]
+    lines.extend(
+        f"export {key}={shlex.quote(str(value))}"
+        for key, value in sorted(merged.items())
+    )
+    lines.extend(
+        [
+            "",
+            f'{shlex.quote(str(executable))} "$SLURM_ARRAY_TASK_ID"',
+            "",
+        ]
+    )
+    return "\n".join(lines)
+
+
+def snapshot_aclustercapacity(host: str) -> str:
+    command = [
+        "ssh",
+        host,
+        'sinfo -N -h -p compute -o "%N|%t|%C"',
+    ]
+    return subprocess.run(command, check=True, text=True, capture_output=True).stdout
+
+
+def write_submit(args: argparse.Namespace) -> None:
+    environment = json.loads(args.environment.read_text())
+    text = condor_submit_text(
+        executable=args.executable.resolve(),
+        campaign_root=args.campaign_root.resolve(),
+        wave=args.wave,
+        environment=environment,
+        jobs=args.jobs,
+        cpus=args.cpus,
+        memory_mb=args.memory_mb,
+        max_materialize=args.max_materialize,
+    )
+    args.out.write_text(text)
+
+
+def write_slurm(args: argparse.Namespace) -> None:
+    environment = json.loads(args.environment.read_text())
+    text = slurm_array_text(
+        executable=args.executable.resolve(),
+        campaign_root=args.campaign_root.resolve(),
+        wave=args.wave,
+        environment=environment,
+        jobs=args.jobs,
+        cpus=args.cpus,
+        memory_mb=args.memory_mb,
+        time_limit=args.time,
+        max_concurrent=args.max_concurrent,
+    )
+    args.out.write_text(text)
+
+
+def report_choice(args: argparse.Namespace) -> None:
+    snapshot = snapshot_aclustercapacity(args.host)
+    nodes = runnable_nodes(snapshot, args.required_cpus)
+    result = {
+        "backend": "slurm" if len(nodes) >= args.workers else "condor",
+        "required_cpus": args.required_cpus,
+        "runnable_nodes": nodes,
+        "snapshot": snapshot.splitlines(),
+        "workers": args.workers,
+    }
+    print(json.dumps(result, indent=2, sort_keys=True))
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    commands = root.add_subparsers(required=True)
+    choose = commands.add_parser("choose")
+    choose.add_argument("--host", default="acluster")
+    choose.add_argument("--workers", type=int, default=8)
+    choose.add_argument("--required-cpus", type=int, default=48)
+    choose.set_defaults(action=report_choice)
+    submit = commands.add_parser("write-condor")
+    submit.add_argument("--executable", type=Path, required=True)
+    submit.add_argument("--campaign-root", type=Path, required=True)
+    submit.add_argument("--wave", required=True)
+    submit.add_argument("--environment", type=Path, required=True)
+    submit.add_argument("--jobs", type=int, default=8)
+    submit.add_argument("--cpus", type=int, required=True)
+    submit.add_argument("--memory-mb", type=int, required=True)
+    submit.add_argument("--max-materialize", type=int)
+    submit.add_argument("--out", type=Path, required=True)
+    submit.set_defaults(action=write_submit)
+    slurm = commands.add_parser("write-slurm")
+    slurm.add_argument("--executable", type=Path, required=True)
+    slurm.add_argument("--campaign-root", type=Path, required=True)
+    slurm.add_argument("--wave", required=True)
+    slurm.add_argument("--environment", type=Path, required=True)
+    slurm.add_argument("--jobs", type=int, default=8)
+    slurm.add_argument("--cpus", type=int, required=True)
+    slurm.add_argument("--memory-mb", type=int, required=True)
+    slurm.add_argument("--time", default="04:00:00")
+    slurm.add_argument("--max-concurrent", type=int, default=8)
+    slurm.add_argument("--out", type=Path, required=True)
+    slurm.set_defaults(action=write_slurm)
+    return root
+
+
+if __name__ == "__main__":
+    arguments = parser().parse_args()
+    arguments.action(arguments)
diff --git a/scripts/scale_vmec_input.py b/scripts/scale_vmec_input.py
new file mode 100644
index 0000000..96e7d0c
--- /dev/null
+++ b/scripts/scale_vmec_input.py
@@ -0,0 +1,156 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import re
+from pathlib import Path
+
+
+_ASSIGN_RE = re.compile(
+    r"(?P<key>RBC|RBS|ZBC|ZBS)\(\s*(?P<n>-?\d+)\s*,\s*(?P<m>-?\d+)\s*\)\s*=\s*(?P<val>[^,!\n]+)"
+)
+
+
+def _format_like(original: str, value: float) -> str:
+    text = original.strip()
+    if "E" in text or "e" in text or "D" in text or "d" in text:
+        exp_char = "E"
+        if "d" in original or "D" in original:
+            exp_char = "D"
+        mantissa = re.split(r"[eEdD]", text, maxsplit=1)[0]
+        digits = 16
+        if "." in mantissa:
+            digits = len(mantissa.split(".", maxsplit=1)[1])
+        digits = max(6, digits)
+        formatted = f"{value:.{digits}E}"
+        if exp_char == "D":
+            formatted = formatted.replace("E", "D", 1)
+        return formatted
+    return f"{value:.16g}"
+
+
+def _parse_float_fortran(text: str) -> float:
+    return float(text.strip().replace("d", "e").replace("D", "E"))
+
+
+def scale_vmec_input(
+    *,
+    input_path: Path,
+    output_path: Path,
+    geo_scale: float,
+    phiedge_scale: float | None = None,
+    set_ns: int | None = None,
+    set_niter: int | None = None,
+    set_ns_array: list[int] | None = None,
+) -> None:
+    if geo_scale <= 0.0:
+        raise ValueError("geo_scale must be positive")
+    if phiedge_scale is not None and phiedge_scale <= 0.0:
+        raise ValueError("phiedge_scale must be positive")
+    if not input_path.exists():
+        raise FileNotFoundError(input_path)
+
+    lines = input_path.read_text(encoding="utf-8").splitlines()
+    out_lines: list[str] = []
+
+    out_lines.append("&INDATA")
+    out_lines.append(f"! Scaled from {input_path.name} with geo_scale={geo_scale:g}.")
+    out_lines.append("! Boundary Fourier coefficients (RBC/RBS/ZBC/ZBS) were scaled.")
+    if phiedge_scale is not None:
+        out_lines.append(f"! PHIEDGE was scaled by phiedge_scale={phiedge_scale:g}.")
+    out_lines.append("! License and provenance: see initial_configs/NOTICE.ALPES_QUASR_0021326.")
+
+    in_indata = False
+    for raw in lines:
+        line = raw.rstrip("\n")
+        if line.strip().upper().startswith("&INDATA"):
+            in_indata = True
+            continue
+        if not in_indata:
+            continue
+
+        if line.strip().startswith("!"):
+            continue
+
+        if phiedge_scale is not None and re.match(r"^\s*PHIEDGE\b", line, flags=re.IGNORECASE):
+            key, val_text = line.split("=", maxsplit=1)
+            val = _parse_float_fortran(val_text)
+            scaled = phiedge_scale * val
+            out_lines.append(f"{key.strip()} = {_format_like(val_text, scaled)}")
+            continue
+
+        if set_ns_array is not None and re.match(r"^\s*NS_ARRAY\b", line, flags=re.IGNORECASE):
+            ns_text = ", ".join(str(v) for v in set_ns_array)
+            out_lines.append(f"  NS_ARRAY = {ns_text}")
+            continue
+        if set_ns is not None and re.match(r"^\s*NS_ARRAY\b", line, flags=re.IGNORECASE):
+            out_lines.append(f"  NS_ARRAY = {set_ns:d}")
+            continue
+        if set_niter is not None and re.match(r"^\s*NITER\b", line, flags=re.IGNORECASE):
+            out_lines.append(f"  NITER = {set_niter:d}")
+            continue
+
+        def repl(match: re.Match[str]) -> str:
+            key = match.group("key")
+            val_text = match.group("val")
+            val = _parse_float_fortran(val_text)
+            scaled = geo_scale * val
+            formatted = _format_like(val_text, scaled)
+            return f"{key}({match.group('n')},{match.group('m')}) = {formatted}"
+
+        if any(k in line for k in ("RBC(", "RBS(", "ZBC(", "ZBS(")):
+            new_line = _ASSIGN_RE.sub(repl, line)
+            out_lines.append(new_line)
+        else:
+            out_lines.append(line)
+
+        if line.strip().startswith("/"):
+            break
+
+    if not out_lines or out_lines[-1].strip() != "/":
+        out_lines.append("/")
+
+    output_path.write_text("\n".join(out_lines) + "\n", encoding="utf-8")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(
+        description="Scale a VMEC fixed-boundary input file by scaling boundary Fourier coefficients."
+    )
+    parser.add_argument("--in", dest="input_path", type=Path, required=True)
+    parser.add_argument("--out", dest="output_path", type=Path, required=True)
+    parser.add_argument("--geo-scale", dest="geo_scale", type=float, required=True)
+    parser.add_argument(
+        "--scale-phiedge",
+        dest="scale_phiedge",
+        action="store_true",
+        help="Also scale PHIEDGE by geo_scale^2 (keeps B approximately constant under geometric scaling).",
+    )
+    parser.add_argument("--set-ns", dest="set_ns", type=int, default=None)
+    parser.add_argument(
+        "--set-ns-array",
+        dest="set_ns_array",
+        type=str,
+        default=None,
+        help="Set NS_ARRAY explicitly, e.g. 16,32,64",
+    )
+    parser.add_argument("--set-niter", dest="set_niter", type=int, default=None)
+    args = parser.parse_args()
+
+    set_ns_array: list[int] | None = None
+    if args.set_ns_array is not None:
+        set_ns_array = [int(x.strip()) for x in args.set_ns_array.split(",") if x.strip()]
+
+    scale_vmec_input(
+        input_path=args.input_path,
+        output_path=args.output_path,
+        geo_scale=args.geo_scale,
+        phiedge_scale=(args.geo_scale * args.geo_scale) if args.scale_phiedge else None,
+        set_ns=args.set_ns,
+        set_niter=args.set_niter,
+        set_ns_array=set_ns_array,
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/simple_direct.py b/simple_direct.py
new file mode 100644
index 0000000..58d4947
--- /dev/null
+++ b/simple_direct.py
@@ -0,0 +1,208 @@
+"""Pinned direct SIMPLE loss evaluation for the optimizer."""
+
+from __future__ import annotations
+
+import hashlib
+import os
+import shutil
+import subprocess
+import tempfile
+from pathlib import Path
+
+import numpy as np
+
+A_TARGET = 1.704
+B_TARGET = 5.865
+
+DIRECT_NAMELIST = """&config
+  netcdffile = 'wout.nc'
+  startmode = 1
+  num_surf = 1
+  notrace_passing = 0
+  ntestpart = {n}
+  trace_time = {ttime}
+  sbeg = {sbeg}d0
+  contr_pp = -1.0d10
+  n_e = 2
+  n_d = 4
+  facE_al = 1.0d0
+  npoiper = 100
+  npoiper2 = 256
+  ns_s = 5
+  ns_tp = 5
+  multharm = 5
+  isw_field_type = 2
+  integmode = 1
+  relerr = 1d-13
+  nturns = 8
+  tcut = -1d0
+  vmec_RZ_scale = {rz}
+  vmec_B_scale = {b}
+  fast_class = .False.
+  swcoll = .False.
+  deterministic = .True.
+  ran_seed = {seed}
+/
+"""
+
+
+def find_simple_x(explicit: str | os.PathLike | None = None) -> Path:
+    if explicit is not None:
+        path = Path(explicit)
+        if not path.exists():
+            raise FileNotFoundError(path)
+        return path
+    environment = os.environ.get("SIMPLE_X") or os.environ.get("SIMPLE_EXE")
+    if environment:
+        path = Path(environment)
+        if not path.exists():
+            raise FileNotFoundError(path)
+        return path
+    for candidate in (
+        Path.home() / "code" / "SIMPLE" / "build" / "simple.x",
+        Path.home() / "bin" / "simple.x",
+    ):
+        if candidate.exists():
+            return candidate
+    installed = shutil.which("simple.x")
+    if installed:
+        return Path(installed)
+    raise FileNotFoundError("Could not locate SIMPLE executable")
+
+
+def file_sha256(path: str | os.PathLike) -> str:
+    digest = hashlib.sha256()
+    with Path(path).open("rb") as handle:
+        for block in iter(lambda: handle.read(1024 * 1024), b""):
+            digest.update(block)
+    return digest.hexdigest()
+
+
+def reactor_scale(wout_path: str | os.PathLike) -> tuple[float, float]:
+    """Return scales that put a VMEC equilibrium at the ARIES-CS point."""
+    from scipy.io import netcdf_file
+
+    with netcdf_file(str(wout_path), "r", mmap=False) as dataset:
+        minor_radius = float(dataset.variables["Aminor_p"][()])
+        mean_field = float(dataset.variables["volavgB"][()])
+    return A_TARGET / minor_radius, B_TARGET / abs(mean_field)
+
+
+def loss_windows(
+    lost_times: np.ndarray,
+    *,
+    prompt_time: float,
+    final_time: float,
+) -> dict[str, float | int]:
+    times = np.asarray(lost_times, dtype=float)
+    if times.ndim != 1 or times.size == 0:
+        raise ValueError("lost_times must be a nonempty vector")
+    if not 0.0 < prompt_time < final_time:
+        raise ValueError("loss windows require 0 < prompt < final")
+    prompt = (times > 0.0) & (times <= prompt_time)
+    late = (times > prompt_time) & (times < final_time)
+    total = prompt | late
+    particles = times.size
+    return {
+        "particles": int(particles),
+        "prompt_count": int(prompt.sum()),
+        "late_count": int(late.sum()),
+        "total_count": int(total.sum()),
+        "prompt_loss": float(prompt.mean()),
+        "late_loss": float(late.mean()),
+        "total_loss": float(total.mean()),
+    }
+
+
+def direct_loss_metrics(
+    wout_path: str | os.PathLike,
+    *,
+    ntestpart: int,
+    expected_simple_sha256: str,
+    trace_time: float,
+    prompt_time: float,
+    sbeg: float,
+    seed: int,
+    simple_executable: str | os.PathLike | None = None,
+    keep_workdir: bool = False,
+    timeout_s: float = 900.0,
+) -> dict[str, float | int | str]:
+    if ntestpart <= 0 or not 0.0 < sbeg < 1.0:
+        raise ValueError("particle count and birth surface are invalid")
+    if trace_time <= prompt_time:
+        raise ValueError("trace time must exceed prompt time")
+    simple_x = find_simple_x(simple_executable)
+    binary_hash = file_sha256(simple_x)
+    if binary_hash != expected_simple_sha256:
+        raise ValueError("unexpected SIMPLE executable hash")
+    rz_scale, b_scale = reactor_scale(wout_path)
+    workdir = Path(tempfile.mkdtemp(prefix="direct_loss_"))
+    try:
+        shutil.copyfile(wout_path, workdir / "wout.nc")
+        (workdir / "simple.in").write_text(
+            DIRECT_NAMELIST.format(
+                n=int(ntestpart),
+                ttime=_fortran_d(trace_time),
+                sbeg=_fortran_d(sbeg),
+                rz=_fortran_d(rz_scale),
+                b=_fortran_d(b_scale),
+                seed=int(seed),
+            )
+        )
+        log_path = workdir / "simple_stdout.txt"
+        with log_path.open("w") as log:
+            completed = subprocess.run(
+                [str(simple_x)],
+                cwd=str(workdir),
+                stdout=log,
+                stderr=subprocess.STDOUT,
+                text=True,
+                timeout=timeout_s,
+                check=False,
+            )
+        if completed.returncode != 0:
+            raise RuntimeError(
+                f"SIMPLE failed with exit code {completed.returncode}; see {log_path}"
+            )
+        particle_path = workdir / "times_lost.dat"
+        curve_path = workdir / "confined_fraction.dat"
+        particles = np.loadtxt(particle_path, ndmin=2)
+        curve = np.loadtxt(curve_path, ndmin=2)
+        if particles.shape[0] != ntestpart or particles.shape[1] < 2:
+            raise ValueError(f"unexpected times_lost shape {particles.shape}")
+        if curve.shape[0] == 0 or curve.shape[1] < 3:
+            raise ValueError(f"unexpected confined_fraction shape {curve.shape}")
+        expected_ids = np.arange(1, ntestpart + 1)
+        if not np.array_equal(particles[:, 0].astype(int), expected_ids):
+            raise ValueError("particle indices are not sequential")
+        trace_endpoint = float(curve[-1, 0])
+        if not np.isclose(trace_endpoint, trace_time, rtol=0.0, atol=1.0e-12):
+            raise ValueError("SIMPLE trace endpoint differs from the contract")
+        metrics = loss_windows(
+            particles[:, 1], prompt_time=prompt_time, final_time=trace_endpoint
+        )
+        curve_loss_count = int(
+            round((1.0 - float(curve[-1, 1]) - float(curve[-1, 2])) * ntestpart)
+        )
+        if metrics["total_count"] != curve_loss_count:
+            raise ValueError("particle losses disagree with the confinement curve")
+        metrics.update(
+            {
+                "vmec_RZ_scale": float(rz_scale),
+                "vmec_B_scale": float(b_scale),
+                "facE_al": 1.0,
+                "simple_sha256": binary_hash,
+                "wout_sha256": file_sha256(wout_path),
+                "seed": int(seed),
+                "trace_endpoint": trace_endpoint,
+                "workdir": str(workdir) if keep_workdir else "",
+            }
+        )
+        return metrics
+    finally:
+        if not keep_workdir:
+            shutil.rmtree(workdir, ignore_errors=True)
+
+
+def _fortran_d(value: float) -> str:
+    return f"{float(value):.16g}".replace("e", "d").replace("E", "d")
diff --git a/smooth_barrier.py b/smooth_barrier.py
new file mode 100644
index 0000000..af5a79e
--- /dev/null
+++ b/smooth_barrier.py
@@ -0,0 +1,308 @@
+"""Continuous fields from SIMPLE's two fast orbit classifiers.
+
+The production quantities in this module never use an integer class, a
+classifier threshold, a legacy monotonicity margin, or a radial max-minus-min.
+They consume the raw finite-time scores written by SIMPLE:
+
+``jpar``
+    RMS relative drift rate of the parallel adiabatic invariant per achieved
+    poloidal precession turn.
+``rotation``
+    Absolute drift between the first- and second-half rotation numbers of the
+    banana-tip map.
+
+For a score ``C(s, mu)`` (zero is best), an intact radial barrier is the best
+regular surface along the escape path.  Since regularity is ``R = -C``, the
+soft maximum of regularity is reported in score units as
+
+``C_barrier(mu) = -tau log(sum_s q_s exp(-C(s, mu) / tau))``.
+
+This is a weighted soft minimum of the raw score.  It equals the score when
+all surfaces agree and approaches the best surface as ``tau`` tends to zero.
+The final scalar is its integral against the sampled alpha-birth density in
+``mu``.  Gaussian reconstruction in ``mu`` and a soft trapped-passing weight
+avoid moving bins and hard masks.
+"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Sequence
+
+import numpy as np
+
+
+@dataclass(frozen=True)
+class ClassifierScores:
+    """One SIMPLE run's raw fast-classifier scores and diagnostics."""
+
+    jpar_variation_rate: np.ndarray
+    rotation_number_drift: np.ndarray
+    precession_turns: np.ndarray
+    jpar_sample_count: np.ndarray
+    rotation_half_count: np.ndarray
+    tip_count: np.ndarray
+    legacy_jpar_spread: np.ndarray
+    legacy_jpar_reference: np.ndarray
+    legacy_topology_margin: np.ndarray
+    legacy_status: np.ndarray
+    trap_par: np.ndarray
+
+    def __len__(self) -> int:
+        return int(self.jpar_variation_rate.size)
+
+    def subset(self, rows: slice | np.ndarray) -> "ClassifierScores":
+        """Select particles while preserving the score schema."""
+        return ClassifierScores(
+            jpar_variation_rate=self.jpar_variation_rate[rows],
+            rotation_number_drift=self.rotation_number_drift[rows],
+            precession_turns=self.precession_turns[rows],
+            jpar_sample_count=self.jpar_sample_count[rows],
+            rotation_half_count=self.rotation_half_count[rows],
+            tip_count=self.tip_count[rows],
+            legacy_jpar_spread=self.legacy_jpar_spread[rows],
+            legacy_jpar_reference=self.legacy_jpar_reference[rows],
+            legacy_topology_margin=self.legacy_topology_margin[rows],
+            legacy_status=self.legacy_status[rows],
+            trap_par=self.trap_par[rows],
+        )
+
+
+@dataclass(frozen=True)
+class SurfaceScoreField:
+    """Kernel reconstruction of one raw score on fixed ``mu`` nodes."""
+
+    values: np.ndarray
+    resolved_coverage: np.ndarray
+    birth_density: np.ndarray
+
+
+@dataclass(frozen=True)
+class BarrierMetric:
+    """Birth-weighted barrier defect and the fields needed to audit it."""
+
+    value: float
+    barrier_field: np.ndarray
+    birth_density: np.ndarray
+    resolved_coverage: float
+    surface_fields: tuple[SurfaceScoreField, ...]
+
+
+def load_class_scores(run: str | Path) -> ClassifierScores:
+    """Read the 12-column ``class_scores.dat`` schema from SIMPLE."""
+    path = Path(run) / "class_scores.dat"
+    table = np.loadtxt(path, ndmin=2)
+    if table.shape[1] < 12:
+        raise ValueError(
+            f"{path} has {table.shape[1]} columns; expected at least 12: "
+            "index, two raw "
+            "scores, five resolution values, three legacy diagnostics, "
+            "legacy status and trap_par"
+        )
+    expected = np.arange(1, table.shape[0] + 1)
+    if not np.array_equal(table[:, 0].astype(int), expected):
+        raise ValueError(f"{path} particle indices are not sequential")
+    integer_columns = table[:, [4, 5, 6, 10]]
+    if not np.array_equal(integer_columns, integer_columns.astype(int)):
+        raise ValueError(f"{path} contains non-integral resolution metadata")
+    return ClassifierScores(
+        jpar_variation_rate=table[:, 1],
+        rotation_number_drift=table[:, 2],
+        precession_turns=table[:, 3],
+        jpar_sample_count=table[:, 4].astype(int),
+        rotation_half_count=table[:, 5].astype(int),
+        tip_count=table[:, 6].astype(int),
+        legacy_jpar_spread=table[:, 7],
+        legacy_jpar_reference=table[:, 8],
+        legacy_topology_margin=table[:, 9],
+        legacy_status=table[:, 10].astype(int),
+        trap_par=table[:, 11],
+    )
+
+
+def logistic(x: np.ndarray, *, width: float) -> np.ndarray:
+    """Numerically stable smooth replacement for a zero-centred step."""
+    if not np.isfinite(width) or width <= 0.0:
+        raise ValueError("width must be finite and positive")
+    values = np.asarray(x, dtype=float)
+    return 0.5 * (1.0 + np.tanh(values / (2.0 * width)))
+
+
+def trapped_weight(trap_par: np.ndarray, *, width: float) -> np.ndarray:
+    """Soft weight for the physically trapped side of ``trap_par = 0``."""
+    return logistic(np.asarray(trap_par, dtype=float), width=width)
+
+
+def score_and_resolution(
+    scores: ClassifierScores, *, classifier: str
+) -> tuple[np.ndarray, np.ndarray]:
+    """Return a raw score and its independently recorded resolution mask."""
+    if classifier == "jpar":
+        values = np.asarray(scores.jpar_variation_rate, dtype=float)
+        resolved = np.asarray(scores.jpar_sample_count) > 0
+    elif classifier == "rotation":
+        values = np.asarray(scores.rotation_number_drift, dtype=float)
+        resolved = np.asarray(scores.rotation_half_count) > 0
+    else:
+        raise ValueError(f"unknown fast classifier {classifier}")
+    if np.any(values < 0.0) or not np.all(np.isfinite(values)):
+        raise ValueError(f"{classifier} scores must be finite and non-negative")
+    return values, resolved.astype(float)
+
+
+def resolved_fraction(scores: ClassifierScores, *, classifier: str) -> float:
+    """Fraction carrying a raw score; legacy class status is irrelevant."""
+    _, resolved = score_and_resolution(scores, classifier=classifier)
+    return float(np.mean(resolved))
+
+
+def gaussian_kernel(mu: np.ndarray, nodes: np.ndarray, *, width: float) -> np.ndarray:
+    """Normal-density kernel with shape ``(nodes, particles)``."""
+    if not np.isfinite(width) or width <= 0.0:
+        raise ValueError("mu width must be finite and positive")
+    mu = np.asarray(mu, dtype=float)
+    nodes = np.asarray(nodes, dtype=float)
+    if mu.ndim != 1 or nodes.ndim != 1 or nodes.size < 2:
+        raise ValueError("mu and at least two fixed nodes must be one-dimensional")
+    if not np.all(np.diff(nodes) > 0.0):
+        raise ValueError("mu nodes must be strictly increasing")
+    z = (nodes[:, None] - mu[None, :]) / width
+    return np.exp(-0.5 * z * z) / (np.sqrt(2.0 * np.pi) * width)
+
+
+def _sample_weights(count: int, supplied: np.ndarray | None) -> np.ndarray:
+    if supplied is None:
+        return np.ones(count, dtype=float)
+    weights = np.asarray(supplied, dtype=float)
+    if weights.shape != (count,):
+        raise ValueError("sample weights and classifier scores have different lengths")
+    if np.any(weights < 0.0) or not np.all(np.isfinite(weights)):
+        raise ValueError("sample weights must be finite and non-negative")
+    if not np.any(weights > 0.0):
+        raise ValueError("at least one sample weight must be positive")
+    return weights
+
+
+def surface_score_field(
+    scores: ClassifierScores,
+    mu: np.ndarray,
+    nodes: np.ndarray,
+    *,
+    classifier: str,
+    trapped_width: float,
+    mu_width: float,
+    sample_weights: np.ndarray | None = None,
+) -> SurfaceScoreField:
+    """Reconstruct ``C(s, mu)`` as a resolved, trapped weighted mean."""
+    mu = np.asarray(mu, dtype=float)
+    if mu.shape != (len(scores),):
+        raise ValueError("mu and classifier scores have different lengths")
+    values, resolved = score_and_resolution(scores, classifier=classifier)
+    weights = _sample_weights(len(scores), sample_weights)
+    phase_weight = weights * trapped_weight(scores.trap_par, width=trapped_width)
+    kernel = gaussian_kernel(mu, nodes, width=mu_width)
+    birth_density = kernel @ phase_weight
+    resolved_density = kernel @ (phase_weight * resolved)
+    numerator = kernel @ (phase_weight * resolved * values)
+    field = np.full(np.asarray(nodes).shape, np.nan, dtype=float)
+    coverage = np.zeros_like(field)
+    np.divide(numerator, resolved_density, out=field, where=resolved_density > 0.0)
+    np.divide(
+        resolved_density,
+        birth_density,
+        out=coverage,
+        where=birth_density > 0.0,
+    )
+    return SurfaceScoreField(field, coverage, birth_density)
+
+
+def softmin_across_surfaces(
+    values: np.ndarray,
+    *,
+    temperature: float,
+    surface_weights: np.ndarray | None = None,
+) -> np.ndarray:
+    """Weighted log-mean-exp soft minimum, independently at each node."""
+    values = np.asarray(values, dtype=float)
+    if values.ndim != 2 or values.shape[0] == 0:
+        raise ValueError("surface fields must have shape (surfaces, nodes)")
+    if not np.isfinite(temperature) or temperature <= 0.0:
+        raise ValueError("softmin temperature must be finite and positive")
+    weights = _sample_weights(values.shape[0], surface_weights)
+    weights = weights / weights.sum()
+    result = np.full(values.shape[1], np.nan, dtype=float)
+    valid = np.all(np.isfinite(values), axis=0)
+    if not np.any(valid):
+        return result
+    selected = values[:, valid]
+    minimum = np.min(selected, axis=0)
+    shifted = np.exp(-(selected - minimum[None, :]) / temperature)
+    result[valid] = minimum - temperature * np.log(weights @ shifted)
+    return result
+
+
+def birth_weighted_integral(
+    nodes: np.ndarray, values: np.ndarray, density: np.ndarray
+) -> float:
+    """Integrate a field against a non-negative birth density."""
+    nodes = np.asarray(nodes, dtype=float)
+    values = np.asarray(values, dtype=float)
+    density = np.asarray(density, dtype=float)
+    if values.shape != nodes.shape or density.shape != nodes.shape:
+        raise ValueError("nodes, values and density must have the same shape")
+    if not np.all(np.isfinite(values)):
+        return float("nan")
+    if np.any(density < 0.0) or not np.all(np.isfinite(density)):
+        raise ValueError("birth density must be finite and non-negative")
+    normalisation = float(np.trapezoid(density, nodes))
+    if normalisation <= 0.0:
+        return float("nan")
+    return float(np.trapezoid(values * density, nodes) / normalisation)
+
+
+def continuous_barrier_metric(
+    scores_by_surface: Sequence[ClassifierScores],
+    mu_by_surface: Sequence[np.ndarray],
+    nodes: np.ndarray,
+    *,
+    classifier: str,
+    temperature: float,
+    trapped_width: float,
+    mu_width: float,
+    sample_weights_by_surface: Sequence[np.ndarray] | None = None,
+    surface_weights: np.ndarray | None = None,
+) -> BarrierMetric:
+    """Build and birth-integrate the continuous radial-barrier defect."""
+    if len(scores_by_surface) != len(mu_by_surface) or not scores_by_surface:
+        raise ValueError("scores and mu must name the same non-empty surface set")
+    if sample_weights_by_surface is None:
+        sample_weights_by_surface = [None] * len(scores_by_surface)
+    if len(sample_weights_by_surface) != len(scores_by_surface):
+        raise ValueError("sample weights must name every surface")
+    fields = tuple(
+        surface_score_field(
+            scores,
+            mu,
+            nodes,
+            classifier=classifier,
+            trapped_width=trapped_width,
+            mu_width=mu_width,
+            sample_weights=weights,
+        )
+        for scores, mu, weights in zip(
+            scores_by_surface, mu_by_surface, sample_weights_by_surface
+        )
+    )
+    barrier = softmin_across_surfaces(
+        np.stack([field.values for field in fields]),
+        temperature=temperature,
+        surface_weights=surface_weights,
+    )
+    birth_density = fields[0].birth_density
+    value = birth_weighted_integral(nodes, barrier, birth_density)
+    node_coverage = np.min(
+        np.stack([field.resolved_coverage for field in fields]), axis=0
+    )
+    coverage = birth_weighted_integral(nodes, node_coverage, birth_density)
+    return BarrierMetric(value, barrier, birth_density, coverage, fields)
diff --git a/stage_campaign.sh b/stage_campaign.sh
new file mode 100755
index 0000000..3595715
--- /dev/null
+++ b/stage_campaign.sh
@@ -0,0 +1,74 @@
+#!/bin/bash
+# Stage a campaign root: snapshot the code and the SIMPLE binary, pin their
+# hashes, and write the environment the Slurm worker sources.
+#
+# A campaign must not read the live checkout or the live build tree. The worker
+# verifies a code manifest and the executable hash on every candidate, so any
+# edit or rebuild while a campaign runs fails every job in flight. Snapshotting
+# makes a run reproducible and immune to work continuing in the repository.
+set -Eeuo pipefail
+
+root=${1:?campaign root required}
+simple_x=${2:?path to simple.x required}
+xvmec=${XVMEC:-/home/ert/runs/alpha_total_late_turbo_v1/toolchain/vmec2000/build-cluster/build/bin/xvmec}
+code_src=${CODE_SRC:-$HOME/code/EPoptimization}
+
+# Everything the worker executes or imports.
+files=(
+    barrier_overlap.py
+    smooth_barrier.py
+    evaluate_barrier_overlap.py
+    build_barrier_scbo_response.py
+    evaluate_vmec_geometry.py
+    Alan_objectives.py
+    raw_fourier_surface.py
+    run_barrier_candidate.sh
+    simple_direct.py
+    validate_barrier_optimum.py
+)
+
+mkdir -p "$root/code" "$root/toolchain"
+for file in "${files[@]}"; do
+    cp "$code_src/$file" "$root/code/$file"
+done
+cp "$simple_x" "$root/toolchain/simple.x"
+chmod +x "$root/toolchain/simple.x" "$root/code/run_barrier_candidate.sh"
+
+(cd "$root/code" && sha256sum "${files[@]}" > "$root/code-manifest.sha256")
+sha256sum "$root/code-manifest.sha256" | cut -d' ' -f1 > "$root/code-manifest.sha256.digest"
+
+cat > "$root/env.sh" <<EOF
+export PATH=${WORKER_VENV:-/home/ert/runs/alpha-direct-runtime/worker-venv}/bin:\$PATH
+export XVMEC=$xvmec
+export XVMEC_SHA256=$(sha256sum "$xvmec" | cut -d' ' -f1)
+export SIMPLE_X=$root/toolchain/simple.x
+export SIMPLE_SHA256=$(sha256sum "$root/toolchain/simple.x" | cut -d' ' -f1)
+export CODE_ROOT=$root/code
+export CODE_MANIFEST=$root/code-manifest.sha256
+export CODE_MANIFEST_SHA256=$(cat "$root/code-manifest.sha256.digest")
+export CAMPAIGN_ROOT=$root/campaign
+export INNER_SURFACE=${INNER_SURFACE:-0.25}
+export OUTER_SURFACE=${OUTER_SURFACE:-0.7}
+export SURFACES=${SURFACES:-0.25,0.4,0.55,0.7}
+export NTHETA=${NTHETA:-8}
+export NZETA=${NZETA:-8}
+export NPITCH=${NPITCH:-16}
+export MU_NODES=${MU_NODES:-24}
+export TRACE_TIME=${TRACE_TIME:-0.02}
+export PROMPT_TIME=${PROMPT_TIME:-0.001}
+export PROMPT_LIMIT=${PROMPT_LIMIT:-0.25}
+export NTURNS=${NTURNS:-8}
+export PARTICLE_SEED=${PARTICLE_SEED:-12345}
+export OBJECTIVE=${OBJECTIVE:-barrier-jpar}
+export TRAPPED_WIDTH=${TRAPPED_WIDTH:-0.15}
+export MU_WIDTH_FACTOR=${MU_WIDTH_FACTOR:-0.75}
+export JPAR_TEMPERATURE=${JPAR_TEMPERATURE:-0.1}
+export ROTATION_TEMPERATURE=${ROTATION_TEMPERATURE:-0.02}
+export SIMPLE_TIMEOUT_SECONDS=${SIMPLE_TIMEOUT_SECONDS:-3600}
+EOF
+
+cp "$code_src/run_single.sbatch" "$root/run_single.sbatch"
+echo "staged $root"
+echo "  simple.x $(sha256sum "$root/toolchain/simple.x" | cut -c1-12)"
+echo "  code     $(cat "$root/code-manifest.sha256.digest" | cut -c1-12)"
+echo "  objective ${OBJECTIVE:-barrier-jpar}"
diff --git a/test_barrier_overlap.py b/test_barrier_overlap.py
new file mode 100644
index 0000000..94d2e45
--- /dev/null
+++ b/test_barrier_overlap.py
@@ -0,0 +1,445 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+import barrier_overlap as bo
+
+
+def test_pitch_grid_is_symmetric_and_inside_the_unit_interval() -> None:
+    pitch = bo.pitch_grid(8, pitch_max=1.0)
+    assert pitch.size == 8
+    assert np.allclose(np.sort(pitch), pitch)
+    assert np.allclose(pitch, -pitch[::-1])
+    assert np.all(np.abs(pitch) < 1.0)
+    assert np.all(np.abs(pitch) > 0.0)
+
+
+def test_pitch_quadrature_integrates_isotropic_pitch_second_moment() -> None:
+    pitch, weights = bo.pitch_quadrature(7)
+    assert weights.sum() == pytest.approx(1.0)
+    assert np.sum(weights * pitch**2) == pytest.approx(1.0 / 3.0)
+
+
+def test_pitch_grid_respects_the_trapped_bound() -> None:
+    pitch = bo.pitch_grid(16, pitch_max=0.6)
+    assert np.max(np.abs(pitch)) <= 0.6
+    assert np.max(np.abs(pitch)) > 0.5
+
+
+def test_pitch_grid_rejects_bounds_outside_the_unit_interval() -> None:
+    with pytest.raises(ValueError):
+        bo.pitch_grid(8, pitch_max=1.5)
+    with pytest.raises(ValueError):
+        bo.pitch_grid(8, pitch_max=0.0)
+
+
+def test_starting_grid_is_the_full_product_of_its_axes() -> None:
+    rows = bo.starting_grid(0.25, ntheta=8, nzeta=8, npitch=16, nfp=4)
+    assert rows.shape == (1024, 5)
+    assert np.allclose(rows[:, 0], 0.25)
+    assert np.allclose(rows[:, 3], 1.0)
+    assert len(np.unique(rows[:, 1].round(12))) == 8
+    assert len(np.unique(rows[:, 2].round(12))) == 8
+    assert len(np.unique(rows[:, 4].round(12))) == 16
+    # every (theta, zeta, pitch) combination appears exactly once
+    assert len(np.unique(rows[:, [1, 2, 4]].round(12), axis=0)) == 1024
+
+
+def test_starting_grid_spans_one_field_period_in_zeta() -> None:
+    rows = bo.starting_grid(0.3, ntheta=4, nzeta=4, npitch=2, nfp=5)
+    assert rows[:, 2].max() < 2.0 * np.pi / 5.0
+    assert rows[:, 1].max() < 2.0 * np.pi
+
+
+def test_starting_grid_avoids_symmetry_planes() -> None:
+    rows = bo.starting_grid(0.3, ntheta=4, nzeta=4, npitch=2, nfp=2)
+    assert np.all(rows[:, 1] > 0.0)
+    assert np.all(rows[:, 2] > 0.0)
+
+
+def test_starting_weights_match_grid_order_and_normalise() -> None:
+    weights = bo.starting_weights(3, 2, 8)
+    assert weights.shape == (48,)
+    assert weights.sum() == pytest.approx(1.0)
+    assert np.array_equal(weights[:8], weights[8:16])
+
+
+def test_overlap_is_zero_when_the_barrier_surface_is_wholly_regular() -> None:
+    mu = np.array([0.01, 0.02, 0.03, 0.04])
+    trapped = np.ones(4, dtype=bool)
+    edges = np.linspace(0.0, 0.05, 3)
+    value = bo.barrier_overlap_samples(
+        mu,
+        np.array([2, 2, 2, 2]),
+        trapped,
+        mu,
+        np.array([1, 1, 1, 1]),
+        trapped,
+        edges=edges,
+    )
+    assert value == 0.0
+
+
+def test_overlap_is_one_when_both_surfaces_are_wholly_chaotic() -> None:
+    mu = np.array([0.01, 0.02, 0.03, 0.04])
+    trapped = np.ones(4, dtype=bool)
+    edges = np.linspace(0.0, 0.05, 3)
+    value = bo.barrier_overlap_samples(
+        mu,
+        np.array([2, 2, 2, 2]),
+        trapped,
+        mu,
+        np.array([2, 2, 2, 2]),
+        trapped,
+        edges=edges,
+    )
+    assert value == pytest.approx(1.0)
+
+
+def test_overlap_matches_a_hand_computed_two_bin_case() -> None:
+    # bin [0, 0.02): inner 1 of 2 chaotic, outer 1 of 2 chaotic
+    # bin [0.02, 0.04]: inner 2 of 2 chaotic, outer 0 of 2 chaotic
+    # overlap = (1/4)*(1/2) + (2/4)*(0/2) = 0.125
+    mu = np.array([0.005, 0.015, 0.025, 0.035])
+    trapped = np.ones(4, dtype=bool)
+    edges = np.array([0.0, 0.02, 0.04])
+    value = bo.barrier_overlap_samples(
+        mu,
+        np.array([2, 1, 2, 2]),
+        trapped,
+        mu,
+        np.array([2, 1, 1, 1]),
+        trapped,
+        edges=edges,
+    )
+    assert value == pytest.approx(0.125)
+
+
+def test_overlap_ignores_passing_particles() -> None:
+    mu = np.array([0.01, 0.01, 0.03, 0.03])
+    edges = np.array([0.0, 0.02, 0.04])
+    trapped_only_first = np.array([True, False, True, False])
+    chaotic = np.array([2, 2, 2, 2])
+    regular_where_passing = np.array([2, 1, 2, 1])
+    assert bo.barrier_overlap_samples(
+        mu,
+        chaotic,
+        trapped_only_first,
+        mu,
+        chaotic,
+        trapped_only_first,
+        edges=edges,
+    ) == bo.barrier_overlap_samples(
+        mu,
+        regular_where_passing,
+        trapped_only_first,
+        mu,
+        regular_where_passing,
+        trapped_only_first,
+        edges=edges,
+    )
+
+
+def test_overlap_is_nan_without_trapped_particles() -> None:
+    mu = np.array([0.01, 0.02])
+    none = np.zeros(2, dtype=bool)
+    value = bo.barrier_overlap_samples(
+        mu,
+        np.array([2, 2]),
+        none,
+        mu,
+        np.array([2, 2]),
+        np.ones(2, dtype=bool),
+        edges=np.array([0.0, 0.05]),
+    )
+    assert np.isnan(value)
+
+
+def test_mu_edges_do_not_depend_on_the_sample() -> None:
+    first = bo.fixed_mu_edges(1.0, nbins=16)
+    second = bo.fixed_mu_edges(2.0, nbins=16)
+    assert np.array_equal(first, second)
+    assert first.size == 17
+
+
+def test_mu_edges_sit_on_the_gauss_scale_simple_actually_uses() -> None:
+    """A measured trapped band from a reactor-scale run must land inside.
+
+    SIMPLE carries the field in Gauss, so perp_inv is of order 1e-5, not 0.1.
+    Edges on the Tesla scale put every trapped particle in the first bin and
+    silently reduce a mu-resolved metric to a single-bin one.
+    """
+    edges = bo.fixed_mu_edges(1.0, nbins=16)
+    observed_low, observed_high = 1.4324e-05, 1.7896e-05
+    assert edges[0] < observed_low
+    assert edges[-1] > observed_high
+    occupied = np.unique(np.digitize([observed_low, observed_high], edges))
+    assert occupied.size > 1, "the trapped band must span more than one bin"
+
+
+def test_mu_band_is_centred_not_started_at_zero() -> None:
+    edges = bo.fixed_mu_edges(1.0, nbins=8)
+    centre = bo.reference_mu()
+    assert edges[0] > 0.0
+    assert edges[0] < centre < edges[-1]
+
+
+def test_namelist_pins_the_fast_classifier_without_the_fractal_cut() -> None:
+    text = bo.CLASSIFY_NAMELIST.format(
+        n=1024,
+        ttime="2d-2",
+        num_surf=1,
+        sbeg="2.5d-1",
+        field_type=2,
+        integmode=3,
+        nturns=8,
+        rz="1d0",
+        b="1d0",
+        seed=12345,
+    )
+    assert "fast_class = .True." in text
+    assert "class_plot = .False." in text
+    assert "tcut = -1d0" in text
+    assert "notrace_passing = 1" in text
+    assert "multharm = 5" in text
+    assert "startmode = 2" in text
+    assert "integmode = 3" in text
+    assert "isw_field_type = 2" in text
+
+
+def test_multi_surface_namelist_requests_radial_bminmax_cache(
+    tmp_path, monkeypatch
+) -> None:
+    executable = tmp_path / "simple.x"
+    executable.touch()
+    wout = tmp_path / "wout.nc"
+    wout.touch()
+    captured = {}
+
+    def fake_run(command, **kwargs):
+        captured["namelist"] = (Path(kwargs["cwd"]) / "simple.in").read_text()
+        (Path(kwargs["cwd"]) / "class_parts.dat").touch()
+        return type("Result", (), {"returncode": 0})()
+
+    monkeypatch.setattr(bo.subprocess, "run", fake_run)
+    work = tmp_path / "run"
+    bo.run_classification(
+        wout,
+        surface=0.25,
+        surface_bounds=(0.25, 0.7),
+        starts=np.zeros((2, 5)),
+        rz_scale=1.0,
+        b_scale=1.0,
+        trace_time=0.02,
+        nturns=8,
+        seed=1,
+        workdir=work,
+        simple_executable=executable,
+    )
+    assert "num_surf = 2" in captured["namelist"]
+    assert (
+        "sbeg = 2.5000000000000000d-01, 6.9999999999999996d-01" in captured["namelist"]
+    )
+
+
+def test_loss_windows_partition_the_trace(tmp_path) -> None:
+    rows = np.array(
+        [
+            [1, -1.0, 0.5],
+            [2, 5.0e-4, 0.5],
+            [3, 5.0e-3, 0.5],
+            [4, 2.0e-2, 0.5],
+        ]
+    )
+    np.savetxt(tmp_path / "times_lost.dat", rows)
+    metrics = bo.classification_loss_metrics(
+        tmp_path, prompt_time=1.0e-3, trace_time=2.0e-2
+    )
+    assert metrics["prompt_count"] == 1
+    assert metrics["late_count"] == 1
+    assert metrics["prompt_loss"] == pytest.approx(0.25)
+    assert metrics["total_loss"] == pytest.approx(0.5)
+
+
+def test_classification_reader_rejects_mismatched_particle_indices(tmp_path) -> None:
+    np.savetxt(tmp_path / "class_parts.dat", np.array([[1, 0.25, 0.01, 1, 2, 0]]))
+    np.savetxt(tmp_path / "times_lost.dat", np.array([[2, -1.0, 0.5]]))
+    with pytest.raises(ValueError):
+        bo.load_classification(tmp_path, 4)
+
+
+def test_coarse_equilibria_are_rejected_before_simple_runs(monkeypatch) -> None:
+    monkeypatch.setattr(bo, "flux_surface_count", lambda path: 3)
+    with pytest.raises(ValueError, match="flux surfaces"):
+        bo.check_radial_resolution("wout_coarse.nc")
+
+
+def test_the_threshold_is_the_spline_stencil_width(monkeypatch) -> None:
+    monkeypatch.setattr(bo, "flux_surface_count", lambda path: bo.MINIMUM_FLUX_SURFACES)
+    assert bo.check_radial_resolution("wout.nc") == bo.MINIMUM_FLUX_SURFACES
+    monkeypatch.setattr(
+        bo, "flux_surface_count", lambda path: bo.MINIMUM_FLUX_SURFACES - 1
+    )
+    with pytest.raises(ValueError):
+        bo.check_radial_resolution("wout.nc")
+
+
+def test_adequate_radial_resolution_passes(monkeypatch) -> None:
+    monkeypatch.setattr(bo, "flux_surface_count", lambda path: 16)
+    assert bo.check_radial_resolution("wout_fine.nc") == 16
+
+
+def test_classifier_work_directory_uses_requested_storage(
+    monkeypatch, tmp_path
+) -> None:
+    requested = tmp_path / "campaign-scratch"
+    observed = {}
+
+    def fake_mkdtemp(*, prefix, dir):
+        observed.update(prefix=prefix, parent=dir)
+        path = Path(dir) / f"{prefix}oracle"
+        path.mkdir()
+        return str(path)
+
+    monkeypatch.setattr(bo.tempfile, "mkdtemp", fake_mkdtemp)
+    monkeypatch.setattr(bo, "find_simple_x", lambda path: tmp_path / "simple.x")
+    monkeypatch.setattr(bo, "file_sha256", lambda path: "expected")
+    monkeypatch.setattr(bo, "check_radial_resolution", lambda path: 51)
+    monkeypatch.setattr(bo, "reactor_scale", lambda path: (1.0, 1.0))
+    monkeypatch.setattr(bo, "field_periods", lambda path: 4)
+    monkeypatch.setattr(
+        bo,
+        "run_classification",
+        lambda *args, **kwargs: (_ for _ in ()).throw(RuntimeError("oracle stop")),
+    )
+
+    with pytest.raises(RuntimeError, match="oracle stop"):
+        bo.barrier_metrics(
+            "wout.nc",
+            expected_simple_sha256="expected",
+            surfaces=[0.25, 0.7],
+            ntheta=1,
+            nzeta=1,
+            npitch=2,
+            pitch_max=1.0,
+            nmu=3,
+            trace_time=0.02,
+            prompt_time=0.001,
+            nturns=4,
+            seed=1,
+            simple_executable="simple.x",
+            work_root=requested,
+        )
+
+    assert requested.is_dir()
+    assert observed == {"prefix": "continuous_barrier_", "parent": requested}
+
+
+def test_continuous_aggregator_reports_only_raw_fast_classifiers(tmp_path) -> None:
+    n = 6
+    runs = []
+    for index, (jpar, rotation) in enumerate(((0.2, 0.03), (0.4, 0.05))):
+        run = tmp_path / f"surface_{index}"
+        run.mkdir()
+        score_rows = np.column_stack(
+            [
+                np.arange(1, n + 1),
+                np.full(n, jpar),
+                np.full(n, rotation),
+                np.ones(n),
+                np.full(n, 4),
+                np.full(n, 2),
+                np.full(n, 6),
+                np.zeros(n),
+                np.ones(n),
+                np.zeros(n),
+                np.ones(n),
+                np.ones(n),
+            ]
+        )
+        class_rows = np.column_stack(
+            [
+                np.arange(1, n + 1),
+                np.full(n, 0.25 + 0.25 * index),
+                np.linspace(1.3e-5, 1.9e-5, n),
+                np.zeros((n, 3)),
+            ]
+        )
+        np.savetxt(run / "class_scores.dat", score_rows)
+        np.savetxt(run / "class_parts.dat", class_rows)
+        runs.append(run)
+
+    nodes = bo.fixed_mu_nodes(8)
+    result = bo._continuous_metrics(
+        runs,
+        np.full(n, 1.0 / n),
+        nodes=nodes,
+        radial_weights=np.array([0.5, 0.5]),
+        settings=None,
+    )
+    expected_jpar = 0.2 - 0.1 * np.log((1.0 + np.exp(-2.0)) / 2.0)
+    assert result["jpar"]["birth_mean"] == pytest.approx(0.2)
+    assert result["jpar"]["barrier_defect"] == pytest.approx(expected_jpar)
+    assert result["rotation"]["birth_mean"] == pytest.approx(0.03)
+    assert "topology" not in result
+    assert "radial" not in result
+
+
+def test_batched_surface_output_preserves_the_same_softmin_oracle(tmp_path) -> None:
+    n = 6
+    score_rows = []
+    class_rows = []
+    for index, (jpar, rotation) in enumerate(((0.2, 0.03), (0.4, 0.05))):
+        score_rows.append(
+            np.column_stack(
+                [
+                    np.arange(index * n + 1, (index + 1) * n + 1),
+                    np.full(n, jpar),
+                    np.full(n, rotation),
+                    np.ones(n),
+                    np.full(n, 4),
+                    np.full(n, 2),
+                    np.full(n, 6),
+                    np.zeros(n),
+                    np.ones(n),
+                    np.zeros(n),
+                    np.ones(n),
+                    np.ones(n),
+                ]
+            )
+        )
+        class_rows.append(
+            np.column_stack(
+                [
+                    np.arange(index * n + 1, (index + 1) * n + 1),
+                    np.full(n, 0.25 + 0.25 * index),
+                    np.linspace(1.3e-5, 1.9e-5, n),
+                    np.zeros((n, 3)),
+                ]
+            )
+        )
+    np.savetxt(tmp_path / "class_scores.dat", np.concatenate(score_rows))
+    np.savetxt(tmp_path / "class_parts.dat", np.concatenate(class_rows))
+
+    result = bo._continuous_metrics(
+        [tmp_path],
+        np.full(n, 1.0 / n),
+        nodes=bo.fixed_mu_nodes(8),
+        radial_weights=np.array([0.5, 0.5]),
+        settings=None,
+        surface_slices=[slice(0, n), slice(n, 2 * n)],
+    )
+    expected_jpar = 0.2 - 0.1 * np.log((1.0 + np.exp(-2.0)) / 2.0)
+    assert result["jpar"]["birth_mean"] == pytest.approx(0.2)
+    assert result["jpar"]["barrier_defect"] == pytest.approx(expected_jpar)
+
+
+def test_radial_quadrature_matches_a_linear_integral() -> None:
+    surfaces = np.array([0.2, 0.3, 0.7])
+    weights = bo.radial_quadrature_weights(surfaces)
+    average = np.sum(weights * surfaces)
+    assert weights.sum() == pytest.approx(1.0)
+    assert average == pytest.approx(0.45)
diff --git a/test_build_barrier_scbo_response.py b/test_build_barrier_scbo_response.py
new file mode 100644
index 0000000..5565a84
--- /dev/null
+++ b/test_build_barrier_scbo_response.py
@@ -0,0 +1,151 @@
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from build_barrier_scbo_response import base_response, successful_response
+
+REQUEST = {"candidate_id": 7, "unit_x": [0.5, 0.25]}
+
+GEOMETRY = {
+    "schema_name": "alpha-loss.direct-geometry",
+    "constraint_names": ["mirror_ratio", "max_elongation"],
+    "constraint_limits": [0.2, 6.0],
+    "constraints": [-0.5, -0.25],
+    "feasible": True,
+    "metrics": {"aspect": 4.5},
+}
+
+
+def barrier_result(**overrides):
+    barrier = {
+        "continuous": {
+            "jpar": {
+                "birth_mean": 0.10,
+                "barrier_defect": 0.0875,
+                "resolved_fraction_by_surface": [0.9, 0.8],
+            },
+            "rotation": {
+                "birth_mean": 0.03,
+                "barrier_defect": 0.04,
+                "resolved_fraction_by_surface": [0.85, 0.75],
+            },
+        },
+        "prompt_loss_birth": 0.02,
+        "trapped_count_by_surface": [300, 295, 290, 280],
+        "particles_per_surface": 1024,
+        "s_inner": 0.25,
+        "s_outer": 0.7,
+    }
+    barrier.update(overrides)
+    return {
+        "schema_name": "alpha-loss.continuous-fast-classifier-result",
+        "barrier": barrier,
+        "wout_sha256": "abc",
+    }
+
+
+def build(result=None, geometry=None, **kwargs):
+    options = {
+        "objective": "barrier-jpar",
+        "inner_surface": 0.25,
+        "outer_surface": 0.7,
+        "particles_per_surface": 1024,
+        "prompt_limit": 0.05,
+    }
+    options.update(kwargs)
+    return successful_response(
+        REQUEST, result or barrier_result(), geometry or GEOMETRY, **options
+    )
+
+
+def test_objective_is_the_continuous_barrier_defect() -> None:
+    response = build()
+    assert response["observation"]["value"] == pytest.approx(0.0875)
+    assert response["status"] == "ok"
+
+
+def test_prompt_loss_enters_as_a_third_constraint() -> None:
+    response = build()
+    constraints = response["observation"]["constraints"]
+    assert len(constraints) == 3
+    # 0.02 / 0.05 - 1 = -0.6, satisfied
+    assert constraints[2] == pytest.approx(-0.6)
+    assert response["metrics"]["constraint_names"][2] == "prompt_loss"
+
+
+def test_prompt_loss_above_the_limit_is_a_violation() -> None:
+    response = build(barrier_result(prompt_loss_birth=0.10))
+    assert response["observation"]["constraints"][2] == pytest.approx(1.0)
+
+
+def test_surface_mismatch_is_rejected() -> None:
+    with pytest.raises(ValueError):
+        build(barrier_result(s_outer=0.5))
+
+
+def test_particle_count_mismatch_is_rejected() -> None:
+    with pytest.raises(ValueError):
+        build(barrier_result(particles_per_surface=512))
+
+
+def test_empty_trapped_population_is_rejected() -> None:
+    with pytest.raises(ValueError):
+        build(barrier_result(trapped_count_by_surface=[300, 0]))
+
+
+def test_non_finite_overlap_is_rejected() -> None:
+    result = barrier_result()
+    result["barrier"]["continuous"]["jpar"]["barrier_defect"] = float("nan")
+    with pytest.raises(ValueError):
+        build(result)
+
+
+def test_wrong_schema_is_rejected() -> None:
+    result = barrier_result()
+    result["schema_name"] = "something-else"
+    with pytest.raises(ValueError):
+        build(result)
+
+
+def test_failure_response_carries_no_observation() -> None:
+    response = base_response(REQUEST, "failed", "equilibrium_failure")
+    assert response["observation"] is None
+    assert response["failure_kind"] == "equilibrium_failure"
+    assert json.dumps(response)
+
+
+# --- objective selection --------------------------------------------------
+
+
+def test_raw_and_barrier_objectives_are_selectable() -> None:
+    assert build(objective="jpar")["observation"]["value"] == pytest.approx(0.10)
+    assert build(objective="rotation")["observation"]["value"] == pytest.approx(0.03)
+    assert build(objective="barrier-rotation")["observation"]["value"] == pytest.approx(0.04)
+
+
+def test_both_continuous_classifiers_are_recorded() -> None:
+    response = build(objective="barrier-jpar")
+    recorded = response["metrics"]["continuous_fast_classifier"]
+    assert set(recorded) == {"jpar", "rotation"}
+    assert response["metrics"]["objective_kind"] == "barrier-jpar"
+
+
+def test_an_objective_without_scores_is_rejected() -> None:
+    result = barrier_result()
+    result["barrier"]["continuous"] = {}
+    with pytest.raises(ValueError, match="no value"):
+        build(result, objective="barrier-jpar")
+
+
+def test_unknown_objective_is_rejected() -> None:
+    with pytest.raises(ValueError):
+        build(objective="fractal")
+
+
+def test_a_null_continuous_value_reports_resolution() -> None:
+    result = barrier_result()
+    result["barrier"]["continuous"]["rotation"]["barrier_defect"] = None
+    with pytest.raises(ValueError, match="resolved fractions"):
+        build(result, objective="barrier-rotation")
diff --git a/test_data_informed_surface.py b/test_data_informed_surface.py
new file mode 100644
index 0000000..3ea7b41
--- /dev/null
+++ b/test_data_informed_surface.py
@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import h5py
+import numpy as np
+
+from data_informed_surface import (
+    fit_weighted_surface_transform,
+    load_weighted_surface_transform,
+    surface_from_unit,
+)
+
+
+def _write_training_data(path: Path) -> None:
+    rng = np.random.default_rng(9)
+    data = rng.normal(size=(24, 8))
+    weights = np.repeat([1.0, 2.0, 4.0], 8)
+    with h5py.File(path, "w") as archive:
+        archive["data"] = data
+        archive["weights"] = weights
+        archive["n_theta"] = 2
+        archive["n_phi"] = 2
+
+
+def test_weighted_surface_transform_roundtrips_and_freezes(tmp_path: Path) -> None:
+    source = tmp_path / "training.h5"
+    sidecar = tmp_path / "transform.npz"
+    _write_training_data(source)
+    transform = fit_weighted_surface_transform(source, dimension=8)
+    repeated = fit_weighted_surface_transform(source, dimension=8)
+    unit = np.linspace(0.15, 0.85, 8)
+
+    decoded = transform.decode(unit)
+    reconstructed = transform.decode(transform.encode(decoded))
+    transform.save(sidecar)
+    loaded = load_weighted_surface_transform(sidecar)
+
+    np.testing.assert_allclose(reconstructed, decoded, rtol=0.0, atol=1.0e-12)
+    np.testing.assert_array_equal(loaded.decode(unit), transform.decode(unit))
+    np.testing.assert_array_equal(repeated.components, transform.components)
+
+
+def test_weighted_surface_chart_preserves_geometry_contract(tmp_path: Path) -> None:
+    source = tmp_path / "training.h5"
+    _write_training_data(source)
+    transform = fit_weighted_surface_transform(source, dimension=4)
+    surface = surface_from_unit(
+        transform,
+        np.full(4, 0.5),
+        nfp=2,
+        major_radius=1.0,
+        minor_radius=0.25,
+        mpol=2,
+        ntor=2,
+    )
+
+    assert surface.nfp == 2
+    assert surface.stellsym
+    np.testing.assert_allclose(surface.major_radius(), 1.0, rtol=0.0, atol=1.0e-10)
+    np.testing.assert_allclose(surface.minor_radius(), 0.25, rtol=0.0, atol=1.0e-10)
+
+
+def test_anchored_chart_places_reference_at_box_center(tmp_path: Path) -> None:
+    source = tmp_path / "training.h5"
+    _write_training_data(source)
+    transform = fit_weighted_surface_transform(source, dimension=4)
+    anchor = np.linspace(-0.3, 0.4, 8)
+
+    center = transform.decode_anchored(np.full(4, 0.5), anchor)
+
+    np.testing.assert_allclose(center, anchor, rtol=0.0, atol=1.0e-15)
+    np.testing.assert_allclose(
+        transform.encode_anchored(center, anchor),
+        np.full(4, 0.5),
+        rtol=0.0,
+        atol=1.0e-15,
+    )
diff --git a/test_direct_scbo_study.py b/test_direct_scbo_study.py
new file mode 100644
index 0000000..4b48c59
--- /dev/null
+++ b/test_direct_scbo_study.py
@@ -0,0 +1,49 @@
+import numpy as np
+
+from build_direct_scbo_response import jeffreys_variance, successful_response
+
+
+def test_direct_response_uses_only_measured_total_loss_and_geometry_constraints():
+    result = {
+        "particles": 256,
+        "seed": 12345,
+        "birth_surface": 0.25,
+        "trace_time": 0.1,
+        "wout_sha256": "a" * 64,
+        "direct": {
+            "prompt_count": 32,
+            "late_count": 48,
+            "total_count": 80,
+            "prompt_loss": 0.125,
+            "late_loss": 0.1875,
+            "total_loss": 0.3125,
+        },
+    }
+    geometry = {
+        "schema_name": "alpha-loss.direct-geometry",
+        "constraint_names": ["mirror_ratio", "max_elongation"],
+        "constraint_limits": [0.2, 6.0],
+        "constraints": [-0.5, -0.25],
+        "feasible": True,
+        "metrics": {"mirror_ratio": 0.1, "max_elongation": 4.5},
+    }
+    response = successful_response(
+        {"candidate_id": 9, "unit_x": [0.2, 0.8]},
+        result,
+        geometry,
+        particles=256,
+        seed=12345,
+        birth_surface=0.25,
+        trace_time=0.1,
+    )
+    assert response["observation"]["value"] == 0.3125
+    assert response["observation"]["constraints"] == [-0.5, -0.25]
+    assert response["metrics"]["objective_name"] == (
+        "direct_total_loss_fraction_100ms_s025"
+    )
+
+
+def test_jeffreys_variance_remains_positive_at_zero_and_complete_loss():
+    assert jeffreys_variance(0, 256) > 0.0
+    assert jeffreys_variance(256, 256) > 0.0
+    assert np.isclose(jeffreys_variance(0, 256), jeffreys_variance(256, 256))
diff --git a/test_generate_scbo_candidates.py b/test_generate_scbo_candidates.py
new file mode 100644
index 0000000..d6f4256
--- /dev/null
+++ b/test_generate_scbo_candidates.py
@@ -0,0 +1,41 @@
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from generate_scbo_candidates import load_requests
+
+
+def test_load_requests_preserves_ordered_bounded_coordinates(tmp_path) -> None:
+    path = tmp_path / "requests.json"
+    path.write_text(
+        json.dumps(
+            {
+                "requests": [
+                    {"candidate_id": 12, "unit_x": [0.2, 0.8]},
+                    {"candidate_id": 13, "unit_x": [0.4, 0.6]},
+                ]
+            }
+        )
+    )
+
+    rows = load_requests(path, 2)
+
+    assert [row["candidate_id"] for row in rows] == [12, 13]
+    assert rows[0]["unit_x"] == [0.2, 0.8]
+
+
+def test_load_requests_rejects_duplicate_candidate(tmp_path) -> None:
+    path = tmp_path / "requests.json"
+    path.write_text(
+        json.dumps(
+            [
+                {"candidate_id": 2, "unit_x": [0.2]},
+                {"candidate_id": 2, "unit_x": [0.3]},
+            ]
+        )
+    )
+
+    with pytest.raises(ValueError, match="unique"):
+        load_requests(path, 1)
diff --git a/test_generate_vmec_audit_inputs.py b/test_generate_vmec_audit_inputs.py
new file mode 100644
index 0000000..693f88b
--- /dev/null
+++ b/test_generate_vmec_audit_inputs.py
@@ -0,0 +1,45 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+from generate_vmec_audit_inputs import (
+    case_specs,
+    normalize_vmec_input,
+    relative_case_path,
+)
+
+
+def test_case_specs_are_deterministic_and_cover_sobol_block() -> None:
+    first = case_specs(8, 4, 29)
+    second = case_specs(8, 4, 29)
+
+    assert len(first) == 16
+    assert [item[:3] for item in first] == [item[:3] for item in second]
+    assert [item[0] for item in first] == [f"d08_{index:03d}" for index in range(16)]
+    np.testing.assert_array_equal(
+        np.stack([item[3] for item in first]),
+        np.stack([item[3] for item in second]),
+    )
+    assert np.all((np.stack([item[3] for item in first]) >= 0.0))
+    assert np.all((np.stack([item[3] for item in first]) <= 1.0))
+
+
+def test_case_specs_reject_invalid_shape() -> None:
+    with pytest.raises(ValueError, match="outside"):
+        case_specs(0, 2, 1)
+
+
+def test_relative_case_path_keeps_directories_bounded() -> None:
+    assert str(relative_case_path(12, 95, "d12_095")) == "d12/b02/d12_095"
+
+
+def test_normalize_vmec_input_removes_only_layout_noise(tmp_path: Path) -> None:
+    path = tmp_path / "input.case"
+    path.write_text("&INDATA  \n  MPOL = 9 \n/\n\n")
+
+    normalize_vmec_input(path)
+
+    assert path.read_text() == "&INDATA\n  MPOL = 9\n/\n"
diff --git a/test_optimization/input.QI_000_000000 b/test_optimization/input.QI_000_000000
new file mode 100644
index 0000000..fc350aa
--- /dev/null
+++ b/test_optimization/input.QI_000_000000
@@ -0,0 +1,42 @@
+&INDATA
+! This file created by simsopt on July 15 2026, 22:01:10
+
+! ---- Geometric parameters ----
+NFP = 3
+LASYM = F
+
+! ---- Resolution parameters ----
+MPOL = 5
+NTOR = 5
+NTHETA = 16
+NZETA = 14
+NS_ARRAY    =     16
+NITER_ARRAY =   1000
+FTOL_ARRAY  =  1e-11
+
+! ---- Boundary toroidal flux ----
+PHIEDGE = 0.03141592653589793
+
+! ---- Pressure profile specification ----
+PMASS_TYPE = "power_series"
+AM = 0.0 
+PRES_SCALE = 1.0
+
+! ---- Profile specification of iota or current ----
+NCURR = 1
+CURTOR = 0.0
+PCURR_TYPE = "power_series"
+AC = 0.0 
+
+! ---- Other numerical parameters ----
+DELT = 0.9
+NSTEP = 200
+
+! ---- Boundary shape. Array index order is (n, m) ----
+RBC(   0,   0) =  1.000000000000000e+00,    ZBS(   0,   0) =  0.000000000000000e+00
+RBC(   1,   0) = -1.645010471975988e-01,    ZBS(   1,   0) =  0.000000000000000e+00
+RBC(  -1,   1) = -1.161700347228537e-01,    ZBS(  -1,   1) =  6.202491211906338e-02
+RBC(   0,   1) =  1.675416036603739e-01,    ZBS(   0,   1) =  1.342910783180185e-01
+RBC(   1,   1) =  1.285613616151160e-02,    ZBS(   1,   1) = -7.578190687144301e-03
+/
+
diff --git a/test_optimization/input.QI_000_000033 b/test_optimization/input.QI_000_000033
new file mode 100644
index 0000000..ed55e22
--- /dev/null
+++ b/test_optimization/input.QI_000_000033
@@ -0,0 +1,42 @@
+&INDATA
+! This file created by simsopt on July 15 2026, 22:02:47
+
+! ---- Geometric parameters ----
+NFP = 3
+LASYM = F
+
+! ---- Resolution parameters ----
+MPOL = 5
+NTOR = 5
+NTHETA = 16
+NZETA = 14
+NS_ARRAY    =     16
+NITER_ARRAY =   1000
+FTOL_ARRAY  =  1e-11
+
+! ---- Boundary toroidal flux ----
+PHIEDGE = 0.03141592653589793
+
+! ---- Pressure profile specification ----
+PMASS_TYPE = "power_series"
+AM = 0.0 
+PRES_SCALE = 1.0
+
+! ---- Profile specification of iota or current ----
+NCURR = 1
+CURTOR = 0.0
+PCURR_TYPE = "power_series"
+AC = 0.0 
+
+! ---- Other numerical parameters ----
+DELT = 0.9
+NSTEP = 200
+
+! ---- Boundary shape. Array index order is (n, m) ----
+RBC(   0,   0) =  1.000000000000000e+00,    ZBS(   0,   0) =  0.000000000000000e+00
+RBC(   1,   0) = -1.761516556143761e-01,    ZBS(   1,   0) =  0.000000000000000e+00
+RBC(  -1,   1) = -1.161700347228537e-01,    ZBS(  -1,   1) =  6.202491211906338e-02
+RBC(   0,   1) =  1.675416036603739e-01,    ZBS(   0,   1) =  1.342910783180185e-01
+RBC(   1,   1) =  1.285613616151160e-02,    ZBS(   1,   1) = -7.578190687144301e-03
+/
+
diff --git a/test_optimization/min_dofs_loss.csv b/test_optimization/min_dofs_loss.csv
new file mode 100644
index 0000000..f4652fe
--- /dev/null
+++ b/test_optimization/min_dofs_loss.csv
@@ -0,0 +1,6 @@
+x(0),x(1),x(2),x(3),x(4),x(5),x(6),x(7),mean_iota,aspect,loss_fraction,quasisymmetry,well,effective_1o_time
+-0.011981051415205002,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.73597231469977,8.127206405378717,0.45799999999999996,9.883238246565895,-0.07734855421144393,0.0
+0.18354052305221558,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7246393362626838,7.87921843439944,0.44400000000000006,23.839200735161285,-0.09731255789039374,0.0
+0.211071601510048,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7190596692213961,7.844299647026575,0.42800000000000005,33.00897629426319,-0.105870530530718,0.0
+0.12672974076122046,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7328816407011374,7.951273861880808,0.42466666666666664,14.440110607902634,-0.084757968569695,0.0
+0.1140567666850984,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7341065841972602,7.967347510714617,0.42200000000000004,13.311849356524585,-0.0828629584002384,0.0
diff --git a/test_optimization/opt_dofs_loss.csv b/test_optimization/opt_dofs_loss.csv
new file mode 100644
index 0000000..81a89ae
--- /dev/null
+++ b/test_optimization/opt_dofs_loss.csv
@@ -0,0 +1,35 @@
+x(0),x(1),x(2),x(3),x(4),x(5),x(6),x(7),mean_iota,aspect,loss_fraction,quasisymmetry,well,effective_1o_time
+-0.16450104719759878,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7265167453373906,8.320653723869723,0.4753333333333333,15.254485396647933,-0.0780058499716041,0.1740624174223556
+-0.2017788141965866,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7253042309697239,8.367934633027216,0.4926666666666667,18.19927816403466,-0.0769871537090694,0.21689568501586964
+-0.011981051415205002,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.73597231469977,8.127206405378717,0.45799999999999996,9.883238246565895,-0.07734855421144393,0.10450805399114604
+-0.011981051415205002,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.73597231469977,8.127206405378717,0.45799999999999996,9.883238246565895,-0.07734855421144393,0.10450805399114604
+-0.012580103985965253,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7359450244505328,8.127966208136735,0.45866666666666667,9.887224319596148,-0.07735776745942761,0.10457760368582507
+-0.011381998844444751,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7359990617075794,8.126446602620733,0.45999999999999996,9.87938871742806,-0.07733890449866371,0.022873313371275825
+-0.012280577700585127,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7359587042222059,8.127586306757815,0.45866666666666667,9.885214243387587,-0.07735313320727102,0.10470801608647173
+-0.012280577700585127,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7359587042222059,8.127586306757815,0.45866666666666667,9.885214243387587,-0.07735313320727102,0.10470801608647173
+0.18354052305221558,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7246393362626838,7.87921843439944,0.44400000000000006,23.839200735161285,-0.09731255789039374,0.023089946508284637
+-0.07433899492025375,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7322156877856859,8.206297523207407,0.44933333333333336,10.997593739089078,-0.07847192845654818,0.21134981435476932
+0.18354052305221558,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7246393362626838,7.87921843439944,0.44400000000000006,23.839200735161285,-0.09731255789039374,0.023089946508284637
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+0.12672974076122046,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7328816407011374,7.951273861880808,0.42466666666666664,14.440110607902634,-0.084757968569695,0.011456535111183016
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+-0.23575957119464874,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.725144245498209,8.411033810206229,0.5433333333333333,21.722936889743632,-0.07597244745800354,0.14638467793410148
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+-0.17465469427406788,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7260900494031338,8.333532007728621,0.4773333333333334,15.973991476054888,-0.07775786560413335,0.06751401629782935
+0.07818616181612015,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7364684530859076,8.012843658868539,0.43333333333333335,11.187613900999319,-0.07911264330860839,0.032546731053176924
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+-0.17615165561437607,-0.1161700347228537,0.1675416036603739,0.0128561361615116,0.0,0.06202491211906338,0.1342910783180185,-0.007578190687144301,-0.7260327712621136,8.335430664725598,0.4786666666666667,16.085006536237195,-0.07771859536333262,0.1435955088310066
diff --git a/test_optimization/parvmecinfo.txt b/test_optimization/parvmecinfo.txt
new file mode 100644
index 0000000..d134bc7
--- /dev/null
+++ b/test_optimization/parvmecinfo.txt
@@ -0,0 +1,137 @@
+ ============================================================
+ PARVMEC =  T
+ > available processor count:           1
+ > global rank:           0
+ > nzeta:                14
+ > ntheta3:               9
+ > ntor:                  5
+ > mpol1:                 4
+ > ntmax:                 2
+ > blocksize:            30
+ ============================================================
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
+ >>> grid resolution:             16
+ >>> active processors:            1
+ >>> xc/gc size:                2880
+ ------------------------------------------------------------
+
diff --git a/test_optimization/wout_QI_000_000000.nc b/test_optimization/wout_QI_000_000000.nc
new file mode 100644
index 0000000..192f137
Binary files /dev/null and b/test_optimization/wout_QI_000_000000.nc differ
diff --git a/test_optimization/wout_QI_000_000033.nc b/test_optimization/wout_QI_000_000033.nc
new file mode 100644
index 0000000..5a1cb2a
Binary files /dev/null and b/test_optimization/wout_QI_000_000033.nc differ
diff --git a/test_raw_fourier_input.py b/test_raw_fourier_input.py
new file mode 100644
index 0000000..2750f75
--- /dev/null
+++ b/test_raw_fourier_input.py
@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import pytest
+
+from raw_fourier_surface import write_vmec_input
+
+BASE = """&INDATA
+NFP = 2
+MPOL = 9
+NTOR = 6
+NS_ARRAY = 16 51
+PHIEDGE = 1.234
+RBC(   0,   0) =  1.0,    ZBS(   0,   0) =  0.0
+RBC(   1,   0) =  0.1,    ZBS(   1,   0) =  0.1
+CURTOR = 0.0
+/
+"""
+
+
+class FakeSurface:
+    def __init__(self, namelist: str) -> None:
+        self._namelist = namelist
+
+    def get_nml(self) -> str:
+        return self._namelist
+
+
+NEW = """&INDATA
+LASYM = .FALSE.
+NFP = 2
+RBC(   0,   0) =  2.0,    ZBS(   0,   0) =  0.0
+RBC(   1,   0) =  0.5,    ZBS(   1,   0) =  0.5
+/
+"""
+
+
+def write(tmp_path, base: str = BASE, namelist: str = NEW):
+    base_path = tmp_path / "input.base"
+    base_path.write_text(base)
+    out = tmp_path / "input.candidate"
+    write_vmec_input(base_path, FakeSurface(namelist), out)
+    return out.read_text()
+
+
+def test_base_settings_survive_the_rewrite(tmp_path) -> None:
+    text = write(tmp_path)
+    for setting in ("MPOL = 9", "NTOR = 6", "NS_ARRAY = 16 51", "PHIEDGE = 1.234",
+                    "CURTOR = 0.0"):
+        assert setting in text
+
+
+def test_new_boundary_replaces_the_old_one(tmp_path) -> None:
+    text = write(tmp_path)
+    assert "RBC(   0,   0) =  2.0" in text
+    assert "RBC(   1,   0) =  0.5" in text
+    assert "1.0," not in text
+    assert text.count("RBC(") == 2
+    assert text.count("ZBS(") == 2
+
+
+def test_boundary_lands_where_the_old_block_was(tmp_path) -> None:
+    lines = write(tmp_path).splitlines()
+    boundary = [i for i, line in enumerate(lines) if line.startswith("RBC(")]
+    assert lines.index("PHIEDGE = 1.234") < min(boundary)
+    assert max(boundary) < lines.index("CURTOR = 0.0")
+    assert lines[-1] == "/"
+
+
+def test_a_base_without_a_boundary_block_is_rejected(tmp_path) -> None:
+    with pytest.raises(ValueError):
+        write(tmp_path, base="&INDATA\nNFP = 2\n/\n")
+
+
+def test_a_surface_without_coefficients_is_rejected(tmp_path) -> None:
+    with pytest.raises(ValueError):
+        write(tmp_path, namelist="&INDATA\nNFP = 2\n/\n")
diff --git a/test_raw_fourier_surface.py b/test_raw_fourier_surface.py
new file mode 100644
index 0000000..b706ee2
--- /dev/null
+++ b/test_raw_fourier_surface.py
@@ -0,0 +1,23 @@
+from pathlib import Path
+
+import numpy as np
+
+from raw_fourier_surface import _mode_scale, raw_coordinate_contract
+
+
+BASE = Path(
+    "/home/ert/proj/alpha-loss-optimization-data/optimization/"
+    "local_search_20260711/base/candidate/input.vmec"
+)
+
+
+def test_raw_contract_matches_rogerio_low_order_dimension():
+    contract = raw_coordinate_contract(BASE)
+    assert len(contract["names"]) == 24
+    assert contract["max_mode"] == 2
+    assert len(contract["center"]) == len(contract["half_width"]) == 24
+
+
+def test_mode_box_decays_with_harmonic_order():
+    assert np.isclose(_mode_scale("rc(0,1)"), 0.025)
+    assert _mode_scale("zs(2,2)") < _mode_scale("zs(1,0)")
diff --git a/test_scbo_backend.py b/test_scbo_backend.py
new file mode 100644
index 0000000..3b76f5d
--- /dev/null
+++ b/test_scbo_backend.py
@@ -0,0 +1,61 @@
+from pathlib import Path
+
+from scbo_backend import (
+    choose_backend,
+    condor_submit_text,
+    runnable_nodes,
+    slurm_array_text,
+)
+
+
+SNAPSHOT = """node1|idle|0/64/0/64
+node2|mix|16/48/0/64
+node3|mix|32/32/0/64
+node4|down*|0/64/0/64
+"""
+
+
+def test_capacity_requires_whole_candidate_slots() -> None:
+    assert runnable_nodes(SNAPSHOT) == ["node1", "node2"]
+    assert choose_backend(SNAPSHOT, workers=2) == "slurm"
+    assert choose_backend(SNAPSHOT, workers=3) == "condor"
+
+
+def test_condor_submit_is_shared_filesystem_and_credential_free() -> None:
+    text = condor_submit_text(
+        executable=Path("/temp/ert/run_scbo_candidate.sh"),
+        campaign_root=Path("/temp/ert/runs/campaign"),
+        wave="wave03",
+        environment={"CODE_ROOT": "/temp/ert/code", "SIMPLE_X": "/temp/ert/simple.x"},
+        jobs=8,
+        cpus=4,
+        memory_mb=4096,
+        max_materialize=8,
+    )
+    assert "queue 8" in text
+    assert "request_cpus = 4" in text
+    assert "request_memory = 4096MB" in text
+    assert "should_transfer_files = NO" in text
+    assert "getenv = False" in text
+    assert "CAMPAIGN_ROOT=/temp/ert/runs/campaign" in text
+    assert "WAVE=wave03" in text
+    assert "max_materialize = 8" in text
+
+
+def test_slurm_array_caps_workers_and_exports_contract() -> None:
+    text = slurm_array_text(
+        executable=Path("/home/ert/code/run_scbo_candidate.sh"),
+        campaign_root=Path("/home/ert/runs/campaign"),
+        wave="wave03",
+        environment={"CODE_ROOT": "/home/ert/code", "PARTICLES": "256"},
+        jobs=28,
+        cpus=48,
+        memory_mb=4096,
+        time_limit="04:00:00",
+        max_concurrent=8,
+    )
+    assert "#SBATCH --array=0-27%8" in text
+    assert "#SBATCH --cpus-per-task=48" in text
+    assert "#SBATCH --mem=4096M" in text
+    assert "export CAMPAIGN_ROOT=/home/ert/runs/campaign" in text
+    assert '/home/ert/code/run_scbo_candidate.sh "$SLURM_ARRAY_TASK_ID"' in text
diff --git a/test_simple_direct.py b/test_simple_direct.py
new file mode 100644
index 0000000..3e9f12c
--- /dev/null
+++ b/test_simple_direct.py
@@ -0,0 +1,24 @@
+import numpy as np
+
+from simple_direct import DIRECT_NAMELIST, loss_windows
+
+
+def test_direct_contract_uses_production_resolution_and_symplectic_euler():
+    assert "npoiper2 = 256" in DIRECT_NAMELIST
+    assert "ns_s = 5" in DIRECT_NAMELIST
+    assert "ns_tp = 5" in DIRECT_NAMELIST
+    assert "multharm = 5" in DIRECT_NAMELIST
+    assert "integmode = 1" in DIRECT_NAMELIST
+    assert "fast_class = .False." in DIRECT_NAMELIST
+
+
+def test_recorded_endpoint_is_censored_as_survival():
+    endpoint = 0.09999999999999999
+    metrics = loss_windows(
+        np.array([0.0005, 0.02, endpoint]),
+        prompt_time=0.001,
+        final_time=endpoint,
+    )
+    assert metrics["prompt_count"] == 1
+    assert metrics["late_count"] == 1
+    assert metrics["total_count"] == 2
diff --git a/test_smooth_barrier.py b/test_smooth_barrier.py
new file mode 100644
index 0000000..fe45ebc
--- /dev/null
+++ b/test_smooth_barrier.py
@@ -0,0 +1,221 @@
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+import smooth_barrier as sb
+
+
+def scores(
+    jpar,
+    rotation,
+    *,
+    jpar_samples=None,
+    rotation_samples=None,
+    trap_par=None,
+    legacy_status=None,
+):
+    jpar = np.asarray(jpar, dtype=float)
+    rotation = np.asarray(rotation, dtype=float)
+    n = jpar.size
+    return sb.ClassifierScores(
+        jpar_variation_rate=jpar,
+        rotation_number_drift=rotation,
+        precession_turns=np.ones(n),
+        jpar_sample_count=np.asarray(
+            jpar_samples if jpar_samples is not None else np.ones(n), dtype=int
+        ),
+        rotation_half_count=np.asarray(
+            rotation_samples if rotation_samples is not None else np.ones(n),
+            dtype=int,
+        ),
+        tip_count=np.full(n, 6, dtype=int),
+        legacy_jpar_spread=np.zeros(n),
+        legacy_jpar_reference=np.ones(n),
+        legacy_topology_margin=np.zeros(n),
+        legacy_status=np.asarray(
+            legacy_status if legacy_status is not None else np.zeros(n), dtype=int
+        ),
+        trap_par=np.asarray(
+            trap_par if trap_par is not None else np.zeros(n), dtype=float
+        ),
+    )
+
+
+def test_logistic_is_monotone_bounded_and_centred() -> None:
+    x = np.linspace(-10.0, 10.0, 101)
+    y = sb.logistic(x, width=1.0)
+    assert np.all(np.diff(y) > 0.0)
+    assert y.min() > 0.0 and y.max() < 1.0
+    assert sb.logistic(np.array([0.0]), width=1.0)[0] == pytest.approx(0.5)
+
+
+def test_logistic_rejects_a_nonpositive_width() -> None:
+    for bad in (0.0, -1.0, np.inf, np.nan):
+        with pytest.raises(ValueError):
+            sb.logistic(np.array([0.0]), width=bad)
+
+
+def test_resolution_uses_raw_score_metadata_not_legacy_status() -> None:
+    sample = scores(
+        [1.0, 2.0, 3.0],
+        [0.1, 0.2, 0.3],
+        jpar_samples=[2, 0, 4],
+        rotation_samples=[0, 2, 2],
+        legacy_status=[1, 1, 3],
+    )
+    _, jpar = sb.score_and_resolution(sample, classifier="jpar")
+    _, rotation = sb.score_and_resolution(sample, classifier="rotation")
+    assert jpar.tolist() == [1.0, 0.0, 1.0]
+    assert rotation.tolist() == [0.0, 1.0, 1.0]
+
+
+def test_surface_field_matches_a_hand_weighted_mean() -> None:
+    sample = scores([1.0, 3.0], [0.0, 0.0])
+    field = sb.surface_score_field(
+        sample,
+        np.array([0.0, 0.0]),
+        np.array([-0.1, 0.1]),
+        classifier="jpar",
+        trapped_width=1.0,
+        mu_width=0.2,
+        sample_weights=np.array([1.0, 3.0]),
+    )
+    assert field.values == pytest.approx([2.5, 2.5])
+    assert field.resolved_coverage == pytest.approx([1.0, 1.0])
+
+
+def test_unresolved_sample_is_censored_and_reported_in_coverage() -> None:
+    sample = scores(
+        [2.0, 100.0],
+        [0.0, 0.0],
+        jpar_samples=[1, 0],
+    )
+    field = sb.surface_score_field(
+        sample,
+        np.array([0.0, 0.0]),
+        np.array([-0.1, 0.1]),
+        classifier="jpar",
+        trapped_width=1.0,
+        mu_width=0.2,
+    )
+    assert field.values == pytest.approx([2.0, 2.0])
+    assert field.resolved_coverage == pytest.approx([0.5, 0.5])
+
+
+def test_weighted_softmin_matches_log_mean_exp_oracle() -> None:
+    values = np.array([[0.0, 4.0], [2.0, 4.0]])
+    actual = sb.softmin_across_surfaces(values, temperature=1.0)
+    expected_first = -np.log((1.0 + np.exp(-2.0)) / 2.0)
+    assert actual == pytest.approx([expected_first, 4.0])
+
+
+def test_birth_weighted_integral_matches_trapezoid_oracle() -> None:
+    nodes = np.array([0.0, 1.0, 2.0])
+    value = sb.birth_weighted_integral(
+        nodes, np.array([0.0, 1.0, 2.0]), np.ones(3)
+    )
+    assert value == pytest.approx(1.0)
+
+
+def test_constant_surface_scores_give_an_exact_barrier_metric() -> None:
+    inner = scores(np.full(4, 1.0), np.full(4, 0.1))
+    outer = scores(np.full(4, 3.0), np.full(4, 0.4))
+    mu = np.linspace(-0.05, 0.05, 4)
+    nodes = np.linspace(-0.1, 0.1, 5)
+    metric = sb.continuous_barrier_metric(
+        [inner, outer],
+        [mu, mu],
+        nodes,
+        classifier="jpar",
+        temperature=1.0,
+        trapped_width=1.0,
+        mu_width=0.05,
+    )
+    expected = -np.log((np.exp(-1.0) + np.exp(-3.0)) / 2.0)
+    assert metric.value == pytest.approx(expected)
+    assert metric.barrier_field == pytest.approx(np.full(nodes.size, expected))
+    assert metric.resolved_coverage == pytest.approx(1.0)
+
+
+def test_intact_low_drift_surface_reduces_the_barrier_defect() -> None:
+    mu = np.linspace(-0.05, 0.05, 8)
+    nodes = np.linspace(-0.1, 0.1, 9)
+    low = scores(np.full(8, 0.1), np.zeros(8))
+    high = scores(np.full(8, 5.0), np.zeros(8))
+    kwargs = dict(
+        nodes=nodes,
+        classifier="jpar",
+        temperature=0.2,
+        trapped_width=1.0,
+        mu_width=0.05,
+    )
+    intact = sb.continuous_barrier_metric([high, low], [mu, mu], **kwargs)
+    broken = sb.continuous_barrier_metric([high, high], [mu, mu], **kwargs)
+    assert intact.value < broken.value
+
+
+def test_subthreshold_language_cannot_create_a_plateau() -> None:
+    """Any raw-score change moves the metric; no class threshold is applied."""
+    mu = np.linspace(-0.05, 0.05, 8)
+    nodes = np.linspace(-0.1, 0.1, 9)
+    first = scores(np.full(8, 0.10), np.zeros(8))
+    second = scores(np.full(8, 0.11), np.zeros(8))
+    kwargs = dict(
+        mu_by_surface=[mu],
+        nodes=nodes,
+        classifier="jpar",
+        temperature=0.2,
+        trapped_width=1.0,
+        mu_width=0.05,
+    )
+    value_first = sb.continuous_barrier_metric([first], **kwargs).value
+    value_second = sb.continuous_barrier_metric([second], **kwargs).value
+    assert value_second > value_first
+
+
+def test_quadrature_result_is_invariant_to_weight_preserving_duplication() -> None:
+    base = scores([1.0, 3.0], [0.1, 0.3])
+    duplicate = scores([1.0, 3.0, 1.0, 3.0], [0.1, 0.3, 0.1, 0.3])
+    nodes = np.array([-0.1, 0.1])
+    base_field = sb.surface_score_field(
+        base,
+        np.array([0.0, 0.0]),
+        nodes,
+        classifier="jpar",
+        trapped_width=1.0,
+        mu_width=0.2,
+        sample_weights=np.array([1.0, 3.0]),
+    )
+    duplicate_field = sb.surface_score_field(
+        duplicate,
+        np.zeros(4),
+        nodes,
+        classifier="jpar",
+        trapped_width=1.0,
+        mu_width=0.2,
+        sample_weights=np.array([0.5, 1.5, 0.5, 1.5]),
+    )
+    assert duplicate_field.values == pytest.approx(base_field.values)
+    assert duplicate_field.birth_density == pytest.approx(base_field.birth_density)
+
+
+def test_reader_round_trips_the_continuous_schema(tmp_path) -> None:
+    rows = np.array(
+        [
+            [1, 0.2, 0.03, 1.5, 4, 2, 7, 10.0, 100.0, -0.2, 1, 0.4],
+            [2, 0.7, 0.08, 2.0, 5, 3, 9, 20.0, 90.0, 0.1, 3, -0.2],
+        ]
+    )
+    np.savetxt(tmp_path / "class_scores.dat", rows)
+    loaded = sb.load_class_scores(tmp_path)
+    assert loaded.jpar_variation_rate == pytest.approx([0.2, 0.7])
+    assert loaded.rotation_number_drift == pytest.approx([0.03, 0.08])
+    assert loaded.jpar_sample_count.tolist() == [4, 5]
+    assert loaded.legacy_status.tolist() == [1, 3]
+
+
+def test_reader_rejects_the_old_thresholded_schema(tmp_path) -> None:
+    np.savetxt(tmp_path / "class_scores.dat", np.zeros((1, 8)))
+    with pytest.raises(ValueError, match="12"):
+        sb.load_class_scores(tmp_path)
diff --git a/test_validate_barrier_optimum.py b/test_validate_barrier_optimum.py
new file mode 100644
index 0000000..811441b
--- /dev/null
+++ b/test_validate_barrier_optimum.py
@@ -0,0 +1,48 @@
+from __future__ import annotations
+
+import pytest
+
+from validate_barrier_optimum import best_feasible_record
+
+
+def record(evaluation_id, value, constraints):
+    return {
+        "evaluation_id": evaluation_id,
+        "observation": {"value": value, "constraints": constraints},
+    }
+
+
+def test_best_feasible_beats_a_lower_infeasible_value() -> None:
+    ledger = {
+        "records": [
+            record(0, 0.30, [-1.0, -1.0, -1.0]),
+            record(1, 0.05, [0.4, -1.0, -1.0]),
+            record(2, 0.12, [-1.0, -1.0, -1.0]),
+        ]
+    }
+    assert best_feasible_record(ledger)["evaluation_id"] == 2
+
+
+def test_falls_back_to_the_best_infeasible_when_nothing_is_feasible() -> None:
+    ledger = {
+        "records": [
+            record(0, 0.30, [0.1, -1.0, -1.0]),
+            record(1, 0.05, [0.4, -1.0, -1.0]),
+        ]
+    }
+    assert best_feasible_record(ledger)["evaluation_id"] == 1
+
+
+def test_failed_evaluations_are_ignored() -> None:
+    ledger = {
+        "records": [
+            {"evaluation_id": 0, "observation": None},
+            record(1, 0.2, [-1.0, -1.0, -1.0]),
+        ]
+    }
+    assert best_feasible_record(ledger)["evaluation_id"] == 1
+
+
+def test_a_ledger_without_successes_is_rejected() -> None:
+    with pytest.raises(ValueError):
+        best_feasible_record({"records": [{"evaluation_id": 0, "observation": None}]})
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..3ded5de
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,1791 @@
+version = 1
+revision = 3
+requires-python = ">=3.11"
+resolution-markers = [
+    "python_full_version >= '3.14' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version == '3.13.*' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version == '3.12.*' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and platform_machine != 'ARM64' and sys_platform == 'win32'",
+    "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+    "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version == '3.13.*' and platform_machine != 'ARM64' and sys_platform == 'win32'",
+    "python_full_version == '3.12.*' and platform_machine != 'ARM64' and sys_platform == 'win32'",
+    "python_full_version == '3.13.*' and sys_platform == 'emscripten'",
+    "python_full_version == '3.12.*' and sys_platform == 'emscripten'",
+    "python_full_version == '3.13.*' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version == '3.12.*' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+    "python_full_version < '3.12' and platform_machine != 'ARM64' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and sys_platform == 'emscripten'",
+    "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
+[[package]]
+name = "bentley-ottmann"
+version = "8.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "dendroid" },
+    { name = "ground" },
+    { name = "prioq" },
+    { name = "reprit" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/23/4b/f79b694ff08cb12f9f7c758bfaf3be6be90f44afdfbb40c59d4e8c46663f/bentley_ottmann-8.0.0.tar.gz", hash = "sha256:01cee6d6340235d214f5ce6d95d83cab009e797c0cc32aa32d2039ece6890d59", size = 11721, upload-time = "2023-05-13T00:06:43.124Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/ea/30/0eafa875bfeda8b7b4824b6cc158c7022f7365c89426b1354acb046dc100/bentley_ottmann-8.0.0-py3-none-any.whl", hash = "sha256:de69dc79713da56a9c7ba58ada6d919394e61b75126c4cfaace0bccf2cf574f8", size = 12239, upload-time = "2023-05-13T00:06:41.337Z" },
+]
+
+[[package]]
+name = "booz-xform"
+version = "0.0.9"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy", version = "2.4.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
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diff --git a/validate_barrier_optimum.py b/validate_barrier_optimum.py
new file mode 100644
index 0000000..97eed2b
--- /dev/null
+++ b/validate_barrier_optimum.py
@@ -0,0 +1,129 @@
+#!/usr/bin/env python3
+"""Direct-loss validation of the best barrier-overlap candidate.
+
+The barrier overlap is a proxy. Whether it steered the optimizer anywhere real
+is only answerable by tracing the winning configuration the expensive way, on
+the same contract the direct campaign uses: 100 ms, 256 particles, s = 0.25.
+
+Run this after an optimizer finishes. It reads the ledger, picks the best
+feasible candidate, and evaluates the direct loss for it and for the anchor,
+so the pair can be compared.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import numpy as np
+
+from simple_direct import direct_loss_metrics
+
+
+def best_feasible_record(ledger: dict) -> dict:
+    records = [row for row in ledger["records"] if row.get("observation")]
+    if not records:
+        raise ValueError("ledger holds no successful evaluations")
+    feasible = [
+        row
+        for row in records
+        if max(row["observation"]["constraints"], default=1.0) <= 0.0
+    ]
+    pool = feasible or records
+    return min(pool, key=lambda row: row["observation"]["value"])
+
+
+def wout_for(campaign_root: Path, method: str, evaluation_id: int) -> Path:
+    case = f"candidate-{evaluation_id:08d}"
+    wave = campaign_root / method / f"eval-{evaluation_id:03d}"
+    path = wave / "candidates" / case / f"wout_{case}.nc"
+    if not path.exists():
+        raise FileNotFoundError(path)
+    return path
+
+
+def evaluate(wout: Path, args: argparse.Namespace) -> dict:
+    return direct_loss_metrics(
+        wout,
+        ntestpart=args.particles,
+        expected_simple_sha256=args.simple_sha256,
+        trace_time=args.trace_time,
+        prompt_time=args.prompt_time,
+        sbeg=args.birth_surface,
+        seed=args.seed,
+        simple_executable=args.simple_executable,
+        timeout_s=args.timeout,
+    )
+
+
+def parser() -> argparse.ArgumentParser:
+    root = argparse.ArgumentParser()
+    root.add_argument("--campaign-root", type=Path, required=True)
+    root.add_argument("--method", required=True)
+    root.add_argument("--out", type=Path, required=True)
+    root.add_argument("--simple-executable", type=Path, required=True)
+    root.add_argument("--simple-sha256", required=True)
+    root.add_argument("--particles", type=int, default=256)
+    root.add_argument("--seed", type=int, default=12345)
+    root.add_argument("--birth-surface", type=float, default=0.25)
+    root.add_argument("--prompt-time", type=float, default=0.001)
+    root.add_argument("--trace-time", type=float, default=0.1)
+    root.add_argument("--timeout", type=float, default=7200.0)
+    return root
+
+
+def main() -> None:
+    args = parser().parse_args()
+    ledger = json.loads(
+        (args.campaign_root / args.method / "ledger.json").read_text()
+    )
+    if ledger.get("metric") != "barrier-overlap":
+        raise ValueError("ledger was not produced by a barrier-overlap run")
+    best = best_feasible_record(ledger)
+    anchor = ledger["records"][0]
+
+    results = {}
+    for label, record in (("best", best), ("anchor", anchor)):
+        if not record.get("observation"):
+            continue
+        wout = wout_for(args.campaign_root, args.method, record["evaluation_id"])
+        results[label] = {
+            "evaluation_id": record["evaluation_id"],
+            "barrier_overlap": record["observation"]["value"],
+            "constraints": record["observation"]["constraints"],
+            "direct": evaluate(wout, args),
+        }
+
+    document = {
+        "schema_name": "alpha-loss.barrier-optimum-validation",
+        "schema_version": 1,
+        "method": args.method,
+        "metric": ledger["metric"],
+        "budget": ledger["budget"],
+        "seed": ledger["seed"],
+        "direct_contract": {
+            "particles": args.particles,
+            "birth_surface": args.birth_surface,
+            "trace_time": args.trace_time,
+            "prompt_time": args.prompt_time,
+            "seed": args.seed,
+        },
+        "results": results,
+    }
+    if "best" in results and "anchor" in results:
+        document["direct_loss_change"] = float(
+            results["best"]["direct"]["total_loss"]
+            - results["anchor"]["direct"]["total_loss"]
+        )
+        document["proxy_moved_the_direct_loss"] = bool(
+            np.isfinite(document["direct_loss_change"])
+            and document["direct_loss_change"] < 0.0
+        )
+    args.out.write_text(
+        json.dumps(document, indent=2, sort_keys=True, allow_nan=False) + "\n"
+    )
+
+
+if __name__ == "__main__":
+    main()
diff --git a/vmecPlot2.py b/vmecPlot2.py
index dece248..e97c50c 100755
--- a/vmecPlot2.py
+++ b/vmecPlot2.py
@@ -152,7 +152,7 @@ def main(file,name='',figures_folder='.', coils_curves=None, s_plot_ignore=0.2,s
     # plt.plot(s_half, iotas[1:],'.-',label='iotas')
     # plt.legend(fontsize='x-small')
     plt.xlabel(xLabel)
-    plt.ylabel(f'$\iota$')
+    plt.ylabel(r'$\iota$')
 
     plt.subplot(numRows,numCols,plotNum)
     plotNum += 1
@@ -387,4 +387,4 @@ def main(file,name='',figures_folder='.', coils_curves=None, s_plot_ignore=0.2,s
         figures_results_path = str(Path(sys.argv[2]).resolve())
         main(sys.argv[1], sys.argv[2])
     except:
-        main(sys.argv[1])
\ No newline at end of file
+        main(sys.argv[1])