Physics Traceability and Bounded Claims

This report is generated from validation/physics_traceability.json. It blocks full-fidelity public claims for entries whose evidence status is still open or bounded.

Summary

• Status: pass
• Registry entries: 54
• Open fidelity gaps: 53
• Full-fidelity public claims blocked: 53
• Resolved module paths: 54
• Resolved evidence paths: 354
• External validation trackers: 8
• Source marker coverage: 33/33

External Validation Collaboration Trackers

• External validation artefacts needed for full-fidelity SCPN-CONTROL claims: #46 — 0 open claim(s) — Parent tracker for external code, reference data, facility replay, benchmark, and hardware evidence requests.
• External gyrokinetic validation artefacts: #47 — 9 open claim(s) — TGLF, GENE, GS2, CGYRO, QuaLiKiz, nonlinear CBC, Miller geometry, species, JAX parity, OOD, and online-learning artefacts.
• Equilibrium and reconstruction reference artefacts: #48 — 5 open claim(s) — DIII-D or equivalent shots, EFIT, P-EFIT, GEQDSK, VMEC, and stellarator replay artefacts.
• Transport, edge, MHD, and scenario benchmark artefacts: #49 — 15 open claim(s) — Integrated transport, momentum, pedestal, ELM, MARFE, NTM, current drive, stability, tearing, SOL, orbit, UQ, and scenario benchmarks.
• Neural surrogate validation artefacts: #50 — 3 open claim(s) — QLKNN, QuaLiKiz, gyrokinetic, transport, turbulence, and equilibrium surrogate reference datasets and weight provenance.
• Plasma-control and facility replay artefacts: #51 — 12 open claim(s) — RZIP, RWM, free-boundary, density, digital twin, SOC learning, burn, volt-second, mu-synthesis, and reduced-plant replay evidence.
• Disruption, halo-current, and mitigation benchmark artefacts: #52 — 4 open claim(s) — Measured disruption databases, labelled disruption windows, halo/runaway envelopes, wall contact, impurity radiation, and mitigation metadata.
• Hardware, HDL, CODAC/EPICS, and runtime deployment evidence: #53 — 5 open claim(s) — Vivado, Quartus, Yosys, timing closure, simulator evidence, CODAC/EPICS timing, interlocks, backpressure, HIL replay, and runtime parity.

Module Traceability Table

Module	Equation or contract	References	Unit contract	Validation evidence	Status	Tracker
validation/reference_data/diiid	Replay claims require measured signal arrays, physical units, shot identifiers, retrieval timestamp, licence policy, immutable checksums, and source URI provenance.	DIII-D MDSplus facility data access contract; Repository real-data manifest schema 1.0	Signal-specific SI or dimensionless units; arbitrary units are rejected for real-shot evidence.	validation/validate_data_manifests.py; src/scpn_control/core/real_data_manifest.py; tests/test_real_diiid_shots.py; tests/test_validate_data_manifests.py; strict acquisition-readiness gate via --require-real-acquisition	reference_validated
src/scpn_control/control/burn_controller.py	Burn-control claims must declare Bosch-Hale DT reactivity, alpha-energy partition, Lawson triple product, burn-fraction approximation, alpha-heating integration volume, tokamak major/minor-radius ordering, strictly ordered normalised alpha-heating profile grids, reactivity-exponent stability boundary, and PI auxiliary-heating limits.	Bosch and Hale 1992 DT reactivity; Lawson 1957 ignition criterion; Mitarai and Muraoka 1999 delayed alpha-heating feedback; Repository fail-closed burn-control claim-admission contract	SI joules, m^-3, seconds, keV, MW, m^3/s, metres, normalised profile radius, dimensionless Q, and Lawson triple product units m^-3 s keV.	tests/test_burn_controller.py alpha-heating, Lawson, burn-fraction, profile-domain, control, and claim-admission checks; validation/validate_burn_reference.py strict burn-control reference artifact gate; validation/benchmark_burn_control_claims.py bounded claim-admission benchmark	bounded_model	#51
src/scpn_control/core/elm_model.py	ELM model claims must declare pedestal crash trigger, crash depth, recovery timescale, peeling-ballooning boundary, ELM cycle state, RMP suppression threshold, and energy-particle-loss accounting.	peeling-ballooning ELM trigger references; resonant magnetic perturbation ELM suppression references	Time in seconds, energy in joules, density in m^-3, temperature in eV or keV, pressure in pascals, magnetic perturbation amplitude dimensionless or tesla with explicit convention.	tests/test_elm_model.py; tests/test_integrated_scenario.py; tests/test_elm_reference_validation.py strict reference-artifact admission checks; validation/validate_elm_reference.py strict digest-bound ELM/RMP reference gate	validation_gap	#49
src/scpn_control/core/eped_pedestal.py	EPED claims must declare the pedestal-width scaling, collisionless width versus collisionality-narrowed effective-width ordering, peeling-ballooning pressure limit, bootstrap-current coupling, H-mode entry assumptions, global beta limits, and compatibility boundary to the transport solver.	Snyder et al. EPED pedestal model; Troyon beta-limit reference; Sauter bootstrap-current fit	Pedestal width in normalised flux or metres with convention metadata; pressure in pascals, temperature in eV or keV, density in m^-3, current in amperes, and beta dimensionless.	tests/test_eped_pedestal.py; tests/test_eped_reference_validation.py strict reference-artifact admission checks; validation/validate_eped_reference.py strict digest-bound EPED pedestal reference gate; tests/test_cross_module_physics.py; tests/test_transport_hmode_edge.py	validation_gap	#49
src/scpn_control/core/fusion_kernel.py	Fusion-kernel claims must declare the Grad-Shafranov residual, finite-difference grid, coil Green functions, source-profile parameterisation, boundary conditions, nonlinear iteration controls, convergence criteria, and Rust/Python parity boundary.	Grad-Shafranov equilibrium equation; Green-function tokamak coil-response references; repository Rust/Python fusion-kernel parity contract	SI metres, webers per radian, tesla, amperes, pascals, source derivatives, grid spacings, and dimensionless convergence tolerances.	tests/test_fusion_kernel.py; tests/test_geqdsk_regression.py; tests/test_rust_python_parity.py	validation_gap	#48
src/scpn_control/core/jax_gk_solver.py	JAX linear gyrokinetic claims must preserve the native local-dispersion eigenvalue formulation, expose identical physical input contracts, document numerical-precision or backend divergence, and keep the stiffness-to-transport closure bounded as a controller-tuning surrogate.	Repository native linear GK local-dispersion contract; JAX numerical backend reproducibility guidance	Same growth-rate, frequency, geometry, and species units as native linear GK; backend dtype, tolerance, and normalisation must be explicit in validation artefacts.	tests/test_jax_gk_solver.py local-dispersion parity, stiffness, fail-closed, and bounded chi_i-profile closure checks; tests/test_jax_gk_parity_validation.py schema-versioned artifact digest, case-parameter digest, mode-spectrum, and required case/backend admission checks; validation/benchmark_jax_gk_parity.py strict persisted multi-case backend parity artifact producer; validation/validate_jax_gk_parity.py strict persisted backend parity artifact gate with named case and backend coverage requirements; source-level native local-dispersion parity contract; validation/reports/jax_gk_parity/cyclone_base_case_cpu_cpu.json CPU parity artifact with canonical payload digest; validation/reports/jax_gk_parity/tem_kinetic_electron_cpu_cpu.json CPU parity artifact with kinetic-electron TEM mode-spectrum contract; validation/reports/jax_gk_parity/stable_mode_cpu_cpu.json CPU parity artifact with low-drive bounded-growth contract; validation/reports/jax_gk_parity/cyclone_base_case_gpu_nvidia_geforce_gtx_1060_6gb.json GPU parity artifact with canonical payload digest; validation/reports/jax_gk_parity/tem_kinetic_electron_gpu_nvidia_geforce_gtx_1060_6gb.json GPU parity artifact with kinetic-electron TEM mode-spectrum contract; validation/reports/jax_gk_parity/stable_mode_gpu_nvidia_geforce_gtx_1060_6gb.json GPU parity artifact with low-drive bounded-growth contract; validation/reports/jax_gk_parity/jax_gk_parity.md CPU/GPU parity evidence summary	validation_gap	#47
src/scpn_control/phase/kuramoto.py	Phase-runtime claims must declare the Kuramoto-Sakaguchi mean-field coupling, order-parameter calculation, exogenous global-driver injection, phase wrapping convention, Euler step, and optional Rust fast-path parity boundary.	Kuramoto and Sakaguchi phase oscillator model; Repository phase synchronisation runtime contract	Phases in radians, angular frequencies in radians per second, timestep in seconds, coupling gains dimensionless or radians per second by declared convention, order parameter dimensionless.	tests/test_phase_kuramoto.py; tests/test_phase_properties.py; tests/test_phase_properties_extended.py; validation/benchmark_kuramoto_runtime_evidence.py schema-versioned runtime parity and timestep-refinement evidence producer	bounded_model	#53
src/scpn_control/core/marfe.py	MARFE claims must declare impurity radiation loss, temperature scan, condensation criterion, Greenwald comparison, power-balance inputs, bounded impurity fraction, edge parallel connection-length scaling through q95 and R0, validated front-temperature state, and detection thresholds for detached high-radiation states.	Stangeby 2000 scrape-off-layer and divertor references; Greenwald 2002 density-limit reference; radiation-condensation MARFE onset references	Temperature in eV, density in m^-3, power in MW or W with explicit conversion, plasma current in MA or A with convention metadata, impurity fraction dimensionless on (0, 1], connection length in metres.	tests/test_marfe.py; tests/test_marfe_reference_validation.py strict reference-artifact admission checks; validation/validate_marfe_reference.py strict digest-bound MARFE reference gate; tests/test_cross_module_physics.py	validation_gap	#49
src/scpn_control/core/gk_geometry.py	Geometry claims must declare Miller-shape coordinates, derivative-resolved ballooning-angle grids, Jacobian, toroidal-field convention, safety-factor field-pitch relation, poloidal-field construction, b-dot-grad-theta metric, metric coefficients, contravariant metric determinant identity, and local-equilibrium validity bounds.	Miller et al. 1998 local equilibrium; Cyclone Base Case local Miller geometry benchmark	Major radius, minor radius, local radius, and gradient lengths in metres; angles in radians; magnetic-field strength in tesla; q, shear, elongation, triangularity, and shaping derivatives dimensionless.	tests/test_gk_geometry.py field-pitch, metric, contravariant metric-determinant identity, curvature, shaping, and interface checks; validation/validate_gk_geometry_reference.py schema-versioned immutable Miller reference cases with b-dot-grad-theta samples, per-case digests, unit contracts, tolerance metadata, and canonical payload SHA-256; source-level local Miller geometry contract	validation_gap	#47
src/scpn_control/core/ntm_dynamics.py	NTM dynamics claims must declare rational-surface search, rational-surface containment inside the minor radius, tokamak major/minor-radius ordering, modified Rutherford equation terms, bootstrap drive, polarisation and curvature terms, ECCD control coupling, seed-island assumptions, and controller-validity limits.	modified Rutherford equation NTM references; ECCD NTM control references; repository rational-surface and island-dynamics contract	Island width in metres, time in seconds, current in amperes, q dimensionless, rho dimensionless, ECCD power in MW or W with conversion metadata.	tests/test_ntm_dynamics.py; tests/test_ntm_reference_validation.py strict reference-artifact admission checks; validation/validate_ntm_reference.py strict digest-bound NTM reference gate; tests/test_cross_module_physics.py	validation_gap	#49
src/scpn_control/control/rzip_model.py	Rigid-plasma vertical stability claims must declare the linearised state vector [Z, dZ/dt, circuit currents], mutual-inductance derivative, vertical field index, tokamak major/minor-radius ordering, declared vertical inertia, wall-normalised feedback-gain threshold, wall or active-coil circuit model, calibration source, growth-rate comparison tolerance, tamper-evident calibration payload digest, and facility-claim admission status.	Lazarus et al. 1990 rigid plasma vertical stability model; Wesson 2011 tokamak vertical stability and field-index references; Repository vessel circuit model contract	SI metres, seconds, amperes, henries, ohms, tesla, and dimensionless vertical field index; growth time is reported in milliseconds; calibration evidence digests are SHA-256 hex strings.	tests/test_rzip_model.py vertical growth, field-index, declared-inertia, feedback-gain, physical-parameter, and controller-measurement checks; tests/test_rzip_model.py RZIP fallback and singular-circuit checks; validation/validate_rzip_reference.py strict RZIP reference artifact gate; tests/test_rzip_model.py calibration evidence, facility-claim admission, and persisted evidence checks; validation/benchmark_rzip_calibration.py bounded local RZIP calibration benchmark; validation/reports/rzip_calibration.json bounded local calibration report with evidence payload digest	bounded_model	#51
src/scpn_control/scpn/fpga_export.py	FPGA-export claims must declare LIF fixed-point quantisation, leak right-shift approximation, threshold scaling, signed weight saturation, generated HDL boundary, target family assumptions, and synthesis-tool responsibility.	Repository SCPN compiler and fixed-point export contract; Leaky integrate-and-fire digital implementation contract	Fixed-point values use declared bit width and fractional-bit scale; clock in MHz, timestep in seconds, FIFO depth and neuron counts dimensionless, weights and thresholds quantised by explicit integer scale.	tests/test_fpga_export.py; tests/test_scpn_compiler.py	bounded_model	#53
src/scpn_control/scpn/formal_verification.py	Formal verification claims must declare the compiled Petri-net transition relation, exact bounded reachability depth, rational marking arithmetic, marking-bound safety obligations, algebraic place-invariant weights, transition liveness obligations, bounded temporal response and recurrence specifications, inhibitor-arc semantics, and counterexample path reporting.	Petri-net reachability and P-invariant analysis; bounded temporal logic over finite transition systems; repository SCPN compiler transition-relation contract	Markings are dimensionless token densities; arc weights and invariant weights are rationalised from finite decimal inputs; max_depth is a non-negative integer firing bound; temporal response windows count transition firings.	tests/test_scpn_formal_verification.py exact reachability, marking bounds, transition liveness, algebraic place invariants, all-path bounded response, recurrence, counterexample, and invalid-domain checks; src/scpn_control/scpn/formal_verification.py exact explicit-state finite transition relation over rational markings; validation/reports/scpn_z3_formal.json schema-versioned bounded SMT evidence with canonical payload SHA-256; tests/test_controller_safety_case.py target-hardware readiness artifact digest and E2E latency admission checks	bounded_model	#53
src/scpn_control/core/vmec_lite.py	VMEC-lite claims must declare flux-surface parameterisation, rotational-transform profile, Fourier mode truncation, field-period count, positive R00 and sampled major-radius boundary state, pressure/current assumptions, residual metric, geometry/profile/current provenance, reference-comparison tolerances for R_mn, Z_mn, and iota, convergence status, and explicit exclusion from full VMEC-grade 3D MHD equilibrium claims unless matched references pass the fail-closed admission gate.	VMEC 3D equilibrium references; stellarator flux-surface Fourier parameterisation references	SI metres, tesla, pascals, amperes, webers, dimensionless rotational transform, and Fourier coefficients with declared length units.	tests/test_vmec_lite.py verifies finite spectral reconstruction, bounded force residuals, physical domains, and fail-closed VMEC-lite claim evidence admission; validation/benchmark_vmec_lite_claims.py publishes deterministic bounded synthetic claim evidence with explicit full-VMEC exclusion; validation/reports/vmec_lite_claims.json records bounded Fourier, field-period, profile, residual, q-domain, and positive-major-radius evidence; validation/validate_vmec_reference.py strict VMEC reference artefact gate	validation_gap	#48
src/scpn_control/control/advanced_soc_fusion_learning.py	SOC turbulence-learning claims must declare the sandpile lattice, critical-gradient threshold, predator-prey zonal-flow coupling, shear-suppression term, bounded substep relaxation, Q-learning state discretisation, action set, and random policy assumptions.	Diamond and Hahm 1995 SOC turbulence reference; Kim and Diamond 2003 zonal-flow predator-prey coupling; Biglari, Diamond and Terry 1990 shear-suppression reference	Dimensionless lattice gradients, flow amplitudes, shear, toppling counts, Q-table values, reward, and RNG-seeded action choices.	tests/test_advanced_soc.py SOC physics and learning checks; tests/test_advanced_soc_verbose_plot.py verbose and plotting-path checks; tests/test_visualization_paths.py SOC visualisation checks; validation/validate_soc_reference.py strict reference-artifact gate	bounded_model	#51
src/scpn_control/core/current_drive.py	Current-drive claims must declare ECCD, LHCD, and NBI source powers, radial deposition centres and widths, grid-normalised deposition conservation, density and temperature normalisation, Fisch-Boozer or Fisch efficiency coefficients, Prater launch-angle factor, Stix slowing-down time and critical energy for NBI, and the absence of ray-tracing or Fokker-Planck facility validation.	Fisch and Boozer 1980 electron-cyclotron current-drive efficiency; Prater 2004 ECCD launch-angle efficiency scaling; Fisch 1978 lower-hybrid current-drive efficiency; Stix 1972 neutral-beam slowing-down and critical-energy formulae; Ehst and Karney 1991 neutral-beam current-drive model; Repository fail-closed current-drive claim-admission contract	Power in MW or W with explicit conversion, rho dimensionless, density in 10^19 m^-3, temperatures and beam energy in keV, current density in A/m^2, total current in amperes, efficiency coefficients in declared normalised A/W form.	tests/test_current_drive.py ECCD, LHCD, and NBI deposition, scaling, source superposition, total-current integration, and claim-admission checks; validation/validate_current_drive_reference.py strict current-drive reference artifact gate; validation/benchmark_current_drive_claims.py bounded claim-admission benchmark	bounded_model	#49
src/scpn_control/core/blob_transport.py	Blob transport claims must declare interchange drive, sheath closure, radial velocity scaling, filament size, density and temperature perturbation assumptions, non-empty strictly ordered separatrix-to-wall scrape-off-layer profile coordinates, positive ordered detector-event domains, and scrape-off-layer validity bounds.	Stangeby 2000 scrape-off-layer transport references; blob-filament interchange transport scaling references	SI metres, seconds, m/s, density in m^-3, temperature in eV, magnetic field in tesla, and dimensionless normalised perturbations.	tests/test_blob_transport.py velocity-regime, size-scaling, ensemble, flux, strict-profile-grid, wall-flux, and detector-domain checks; tests/test_blob_transport_reference_validation.py strict reference-artifact admission checks; validation/validate_blob_transport_reference.py strict digest-bound SOL blob reference gate	validation_gap	#49
src/scpn_control/core	Analytical approximations must state their source equation, retained terms, omitted terms, unit contract, and allowed parameter domain.	Cordey 1981 orbit-width estimate; Sauter et al. 1999 neoclassical fits; Stangeby 2000 SOL two-point model	Per-module SI or declared normalised units with explicit conversion boundaries.	docs/physics_methods.md simplification declarations; source grep for simplification and approximation markers	bounded_model	#49
src/scpn_control/control	Control approximations must declare reduced-state dynamics, actuator assumptions, estimator assumptions, and facility-exclusion boundaries before any controller-readiness claim.	Tokamak control reduced-plant literature; Repository control safety and disruption contracts	Per-controller declared SI plasma, actuator, magnetic, force, and timing units.	src/scpn_control/control/gym_tokamak_env.py; src/scpn_control/control/free_boundary_tracking.py	bounded_model	#51
src/scpn_control	Runtime approximations must state phase wrapping, fixed-point shift approximations, replay fixture provenance, and hardware export limits.	Kuramoto phase oscillator reference model; Repository fixed-point spiking export contract	Declared phase radians, tick timing, fixed-point scale factors, and replay geometry units.	src/scpn_control/phase/kuramoto.py; src/scpn_control/scpn/fpga_export.py; src/scpn_control/scpn/geometry_neutral_replay.py	bounded_model	#53
src/scpn_control/control/mu_synthesis.py	Mu-analysis claims must declare the structured uncertainty blocks, positive block bounds, Riccati state-feedback K-step, bound-scaled static closed-loop DC robust-performance map, D-scaling upper-bound fit, finite controller state/timestep domains, and the exclusion of full frequency-dependent H-infinity D-K synthesis unless an external validated backend is wired.	Doyle 1982 structured singular value definition; Balas et al. 1993 mu-analysis and synthesis toolbox; Skogestad and Postlethwaite 2005 multivariable feedback control; Repository fail-closed static mu-analysis claim-admission contract	State, control, output, and uncertainty units inherit the supplied state-space plant contract; mu, uncertainty bounds, and D-scalings are dimensionless.	tests/test_mu_synthesis.py D-scaled upper-bound behaviour, uncertainty-bound scaling, finite-domain rejection, closed-loop plant dependence, claim-admission, persisted digest, tamper, and duplicate-key checks; validation/validate_mu_synthesis_reference.py strict mu-analysis reference artefact gate; validation/benchmark_mu_synthesis_claims.py bounded claim-admission benchmark; docs/learning/control_theory_primer.md states the bounded static analysis domain	bounded_model	#51
src/scpn_control/core/checkpoint.py	Checkpoint claims must declare serialised solver state, non-negative episode counter, object-valued metrics schema, finite-value policy, schema-version boundary, and fail-closed handling for corrupt or missing checkpoint artefacts.	repository restart and replay provenance contract	Units are inherited from stored state and metrics; checkpoint metadata must preserve schema version, episode index, and provenance boundaries.	tests/test_checkpoint.py round-trip, resume, finite-payload, schema-version, and corrupt-payload checks	bounded_model	#53
src/scpn_control/control/density_controller.py	Density-control claims must declare the Greenwald limit, ITER operating margin, radial particle transport grid, gas-puff source, pellet source, NBI source, cryopump sink, recycling source, controller gains, CFL-limited explicit transport step, geometry/transport/actuator/diagnostic provenance, source integral, particle-inventory change, and matched Greenwald-fraction and inventory reference tolerances before facility-calibrated density-control claims.	Greenwald 2002 density limit; ITER Physics Basis 1999 density operating margin; Parks and Turnbull 1978 neutral gas shielding pellet-ablation model; Milora 1995 neutral gas shielding pellet-ablation model	SI particles per second, metres, seconds, m^-3, m^2/s, m/s, pellet millimetres, beam keV, megawatts, and dimensionless Greenwald fraction.	tests/test_density_controller.py Greenwald, NGS pellet trajectory deposition, sink, controller, geometry, transport-profile, source-input, timestep guard, and fail-closed density-control claim evidence checks; tests/test_pellet_injection.py Parks-Turnbull NGS ablation and pellet trajectory checks; validation/benchmark_density_control_claims.py publishes deterministic bounded synthetic claim evidence with explicit facility-calibrated claim exclusion; validation/reports/density_control_claims.json records bounded geometry, transport, actuator, diagnostic, CFL, Greenwald, source-integral, and inventory evidence; validation/validate_density_reference.py strict density reference artefact gate	bounded_model	#51
src/scpn_control/core/differentiable_transport.py	Differentiable transport claims must declare the four-channel profile order, cylindrical Crank-Nicolson diffusion step, uniform normalised radial grid, source-term convention, core zero-gradient boundary, edge Dirichlet boundary, transport-coefficient gradients, one-step and multi-step source-schedule gradient targets, sampled finite-difference gradient audit, audited one-step and rollout gradient-admission latency metadata, runtime provenance for CPU/GPU comparison campaigns, bounded Z3 controller-formal evidence binding, neural and reduced-gyrokinetic closure coefficient mapping, campaign provenance metadata, schema-versioned replay metadata, traced JAX rollout-gradient loss construction, JAX x64 precision enablement before jax.numpy import, finite non-negative audit losses and errors, tolerance agreement with campaign metadata, unique in-domain sampled audit indices, pass/fail consistency with maximum audit error, ordered latency percentiles, and optional one-step and rollout Grad-Shafranov flux-map radial weighting contract.	repository JAX transport primitive contract; repository integrated transport solver contract	Profiles inherit channel units for electron temperature, ion temperature, electron density, and impurity density; chi uses m^2/s or the declared normalised diffusivity convention; sources use profile units per second; rho is dimensionless and uniformly spaced; audit loss, audit errors, and latency percentiles are finite non-negative scalar evidence.	tests/test_differentiable_transport.py diffusion, boundary, fallback, optional JAX coefficient-gradient, one-step and multi-step source-schedule-gradient, sampled finite-difference gradient audit, neural and reduced-GK closure coefficient mapping, campaign metadata provenance, schema-versioned replay metadata, replay-drift guard, audit-evidence admission semantics, latency-report runtime-provenance persistence guards, controller-formal readiness digest binding, and one-step plus rollout equilibrium-weighted GS-flux checks; tests/test_nmpc_controller.py NMPC neural-closure, one-step source-schedule, and multi-step source-rollout tuning fail closed without JAX and preserve gradient-audit admission results; tests/test_nmpc_controller.py NMPC coefficient, one-step source-schedule, and multi-step source-rollout tuning results carry campaign metadata, closure provenance, finite source bounds, and fail-closed gradient-audit evidence; validation/benchmark_differentiable_transport_latency.py audited one-step and rollout gradient-admission latency benchmarks or fail-closed JAX-unavailable reports; validation/reports/differentiable_transport_latency.json and validation/reports/differentiable_transport_rollout_latency.json bounded latency reports or blocked-backend status	bounded_model	#49
src/scpn_control/control/digital_twin_online_update.py	Online model-update claims must declare tunable bounded parameters, external TRANSP/TSC simulator artifact provenance, target summary metrics, tolerances, deterministic random seed, Gaussian-process acquisition settings, finite non-negative loss history, source-bound Bayesian results, parameter-domain admission, observation-unit coverage, and fail-closed behavior when external artifacts are absent or malformed.	TRANSP integrated modelling evidence contract; TSC time-dependent simulation evidence contract; Bayesian optimisation for bounded model calibration; Repository digital-twin runtime contract	Tunable density in m^-3, effective charge dimensionless, actuator lag in steps, actuator rate limit dimensionless per step, target metrics in declared digital-twin summary units, non-negative loss values, and simulator time base in seconds.	tests/test_digital_twin_online_update.py external artifact, loss, Bayesian-update, and deterministic benchmark checks; tests/test_digital_twin_reference_validation.py strict digital-twin artifact gate including TRANSP and TSC; validation/benchmark_digital_twin_online_update.py deterministic bounded online-update benchmark	bounded_model	#51
src/scpn_control/control/free_boundary_tracking.py	Free-boundary tracking claims must declare direct kernel-in-the-loop coil-response identification, bounded least-squares correction, actuator lag, slew limits, supervisor rejection, measurement bias, drift, latency, and observer compensation assumptions.	Grad-Shafranov free-boundary control references; Repository FusionKernel free-boundary objective contract; Repository deterministic free-boundary acceptance campaign; Repository fail-closed free-boundary claim-admission contract	SI coil currents, metres, webers per radian, seconds, amperes per second, objective-space residuals, and dimensionless supervisor gains.	tests/test_free_boundary_tracking.py controller, disturbance-observer, and claim-admission checks; tests/test_free_boundary_tracking_variants.py actuator, observer, latency, and supervisor edge-path checks; tests/test_free_boundary_tracking_acceptance.py deterministic acceptance campaign; validation/validate_free_boundary_reference.py strict free-boundary reference artifact gate; validation/benchmark_free_boundary_tracking_claims.py bounded claim-admission benchmark	bounded_model	#51
src/scpn_control/control/disruption_contracts.py	Disruption-contract claims must declare synthetic disruption signal generation, toroidal-mode amplitudes, mitigation-cocktail coupling, impurity transport response, halo/runaway post-disruption response, TBR equivalence scaling, and RL action bias assumptions.	Pautasso et al. 2017 disruption current-quench constraints; Riccardo et al. 2010 halo-current rise-time references; Abdou et al. 2015 blanket neutronics calibration references	SI seconds, milliseconds, mega-amperes, megajoules, moles, megawatts, dimensionless risk, toroidal mode amplitudes, and tritium breeding ratio.	tests/test_disruption_contracts.py contract smoke checks; tests/test_disruption_contracts_pure.py pure physics-path checks; tests/test_disruption_edge_cases.py edge-case disruption checks; validation/validate_disruption_reference.py strict disruption reference artifact gate	bounded_model	#52
src/scpn_control/core/disruption_sequence.py	Disruption-sequence claims must declare phase ordering, finite positive configuration domains, Rechester-Rosenbluth thermal-quench transport, post-quench radiative-cooling exposure, current-quench timing, mitigation action coupling, runaway-electron beam phase, stochastic event boundaries, halo-force convention, and replay provenance.	ITER disruption mitigation sequence references; repository disruption phase-state contract	Time in seconds or milliseconds with explicit convention, current in amperes or mega-amperes, energy in joules or megajoules, magnetic field in tesla, geometry in metres, density in 10^20 m^-3, and dimensionless phase labels.	tests/test_disruption_sequence.py post-quench cooling, phase ordering, current quench, runaway, and halo-force checks; tests/test_disruption_safe_api.py	validation_gap	#52
src/scpn_control/core/gk_interface.py	Generated input decks and parsed outputs must round-trip through real TGLF, GENE, GS2, CGYRO, or QuaLiKiz executables.	TGLF Staebler et al. 2007; GENE Jenko et al. 2000; GS2 Kotschenreuther et al. 1995; CGYRO Candy et al. 2016; QuaLiKiz Bourdelle et al. 2007	Code-specific flux, growth-rate, frequency, and geometry units converted into repository normalisation with explicit metadata.	docs/joss_paper.md external GK limitation; validation/validate_gk_interface_artifacts.py strict digest-bound external interface artefact gate with report schema, payload digest, artefact file digest, portable paths, duplicate code/run rejection, and blocked public-claim state	external_dependency_blocked	#47
src/scpn_control/control/federated_disruption.py	FedAvg/FedProx disruption classifiers must federate per-facility client updates without centralising raw arrays, validate the shared eight-feature disruption contract, clip and noise facility model deltas under a declared Gaussian differential-privacy budget, and preserve a serialisable privacy ledger.	McMahan et al. 2017 Communication-Efficient Learning of Deep Networks from Decentralized Data; Li et al. 2020 FedProx; Dwork and Roth 2014 Algorithmic Foundations of Differential Privacy; Abadi et al. 2016 Deep Learning with Differential Privacy	Eight disruption features use declared tokamak control variables: Ip, beta_N, q95, n/n_GW, li, dBp/dt, locked-mode amplitude, and n=1 RMS; labels are binary disruption indicators.	tests/test_federated_disruption.py module-specific federation, array-ingestion, DP-ledger, and benchmark contract tests; validation/benchmark_federated_disruption.py deterministic synthetic multi-facility benchmark; validation/reports/federated_disruption_benchmark.json synthetic report with explicit claim boundary	bounded_model	#52
src/scpn_control/core/uncertainty.py	Uncertainty claims must declare sampled variables, distributions, correlations, random seed, sample count, propagation chain, convergence and percentile-ordering criteria, finite-value rejection policy, D-T fuel dilution handling, sensitivity outputs, scenario/prior/sensitivity provenance, and matched central-value and sigma reference tolerances before calibrated predictive-UQ claims.	Monte Carlo uncertainty propagation references; repository fusion-performance uncertainty contract	Units inherit each propagated physical quantity; distribution parameters must preserve SI or declared normalised units and dimensionless uncertainty fractions.	tests/test_uncertainty.py verifies IPB98 monotonicity, Bosch-Hale domains, D-T fuel dilution, full-chain sampling, percentile ordering, finite-output checks, and fail-closed UQ claim evidence admission; tests/test_full_chain_uq.py full-chain UQ behavioural coverage; tests/test_uncertainty_sigma_guard.py sigma guard coverage; validation/benchmark_uq_claims.py publishes deterministic bounded synthetic claim evidence with explicit calibrated-UQ exclusion; validation/reports/uq_claims.json records bounded scenario, prior, seed, sample-count, percentile, finite-output, sensitivity, and claim-admission evidence; validation/validate_uncertainty_reference.py strict UQ reference artefact gate	validation_gap	#49
src/scpn_control/scpn/geometry_neutral_replay.py	Geometry-neutral replay claims must declare synthetic W7-X-like fixture provenance, field-line spread metric, actuator current bounds, latency model, stuck-actuator fault schedule, controller feature mapping, replay acceptance thresholds, tamper-evident manifest digests, and fail-closed scenario admission for initial-frame alignment, objective metric availability, current-envelope constraints, and actuator-supported fault modes.	Repository geometry-neutral control contract; W7-X-like reduced-order stellarator replay fixture	Field-line spread in radians, currents in amperes, timestep in seconds, latency in microseconds, effective ripple dimensionless, controller objectives and thresholds declared per replay manifest, manifest digests encoded as SHA-256 hex.	tests/test_geometry_neutral_replay.py; tests/test_geometry_neutral_contracts.py; tests/test_geometry_neutral_replay.py replay evidence admission, digest, bounded-claim, device-claim, tamper, and duplicate-key checks	bounded_model	#48
src/scpn_control/core/gk_ood_detector.py	OOD detector claims must declare the feature vector, training distribution, distance metric, symmetric positive-definite inverse-covariance calibration, threshold calibration, uncertainty handling, non-negative transport ensemble predictions, and behavior outside the calibrated gyrokinetic operating envelope.	Repository gyrokinetic scheduler OOD contract; statistical process monitoring distribution-shift controls	Feature units inherit declared GK inputs and outputs; detector scores are dimensionless with explicit calibration metadata, Mahalanobis metric provenance, threshold provenance, and transport prediction channels in non-negative diffusivity units.	tests/test_gk_ood_detector.py; tests/test_gk_hybrid_integration.py; validation/validate_gk_ood_calibration.py strict persisted campaign calibration gate with report and artefact digests, Mahalanobis-metric provenance, duplicate-campaign rejection, and acceptance-bound checks	validation_gap	#47
src/scpn_control/core/gk_online_learner.py	Online learner claims must declare training-window selection, non-empty train/validation split domains, nonnegative transport-coefficient targets, validation loss, rollback policy, OOD-score sample admission, optimiser settings, persisted retraining decisions, and compatibility boundary with gyrokinetic scheduler inputs.	online learning stability and rollback control references; repository gyrokinetic hybrid learner contract	Inputs inherit GK feature units; transport targets are nonnegative chi_e, chi_i, and D_e; losses and OOD scores are dimensionless with explicit scaling, learning rate, epoch count, generation limit, and threshold metadata.	tests/test_gk_online_learner.py OOD admission, holdout retraining, rollback, decision persistence, and invalid-domain checks; tests/test_gk_hybrid_integration.py scheduler integration checks; validation/benchmark_gk_online_learner.py deterministic bounded online-retraining benchmark	validation_gap	#47
src/scpn_control/core/gk_species.py	Species and collision claims must declare charge, mass, density, temperature, thermal speed, Larmor radius, gyroaverage Bessel evaluation, diamagnetic frequency, pitch-angle deflection coefficient, thermal energy-relaxation coefficient, electron-ion mass-ratio scaling, field-temperature dependence, valid species parameter bounds, valid velocity quadrature sizes, and strictly ordered finite lambda grids bounded by the local trapped-passing boundary.	Sugama et al. 2006 collision operator; gyrokinetic normalisation and species parameter contracts	Mass in kilograms, charge in coulombs, density in m^-3, temperature in electronvolts, velocity in m/s, gyrofrequency in rad/s, Larmor radius in metres, collision rates in s^-1, lambda on [0, 1] with lambda times B/B0 no greater than one, and positive magnetic-field ratio.	tests/test_gk_species.py thermal-speed, Larmor-radius, Bessel gyroaverage, diamagnetic-frequency sign, collision-frequency scaling, velocity-grid, and pitch-angle-domain checks; tests/test_gk_electromagnetic.py; validation/validate_gk_species_reference.py immutable species and collision reference cases with distinct deflection and energy-relaxation channels	validation_gap	#47
src/scpn_control/control/halo_re_physics.py	Post-disruption claims must declare the halo L/R circuit, contact fraction, toroidal peaking factor, current-quench waveform, Connor-Hastie primary generation, Rosenbluth-Putvinski avalanche generation, ensemble uncertainty assumptions, ITER-limit summaries, strict disruption-reference admission, and claim status.	Fitzpatrick 2002 halo current and error-field interaction; Connor and Hastie 1975 runaway electron generation; Rosenbluth and Putvinski 1997 avalanche generation	SI amperes, mega-amperes, seconds, milliseconds, ohms, henries, metres, volts per metre, rates per second, and meganewtons per metre.	tests/test_halo_re_physics.py halo-current, runaway-electron, ensemble, fail-closed claim evidence, and strict reference-admission regression checks; tests/test_halo_nonfinite_guards.py non-finite guard checks; tests/test_halo_validation_paths.py validation-path guard checks; validation/benchmark_disruption_mitigation_claims.py deterministic bounded halo/runaway claim-admission benchmark; validation/validate_disruption_reference.py strict disruption reference artifact gate	bounded_model	#52
src/scpn_control/core/stability_mhd.py	MHD stability claims must declare q-profile interpolation, magnetic shear, interior-point radial grids for profile-resolved criteria, Mercier and Troyon criteria, beta-limit inputs, first-unstable-radius search, bounded bootstrap-current fraction, and the exclusion boundary for full ideal-MHD or resistive-MHD eigenmode claims.	Troyon beta-limit reference; Mercier ideal-MHD stability criterion; tokamak q-profile and magnetic-shear references	q and beta dimensionless, plasma current in MA or A with explicit convention, minor radius and major radius in metres, magnetic field in tesla, rho dimensionless, and local bootstrap-current fraction within [0, 1].	tests/test_stability_mhd.py; tests/test_ballooning_solver.py; tests/test_cross_module_physics.py	validation_gap	#49
src/scpn_control/core/integrated_scenario.py	Integrated scenario claims must declare coupling order, current diffusion, transport, pedestal, ELM, NTM, sawtooth, burn, and control interactions, timestep policy, state exchange units, and failure isolation boundaries.	integrated tokamak scenario modelling references; repository scenario-coupling contract	All coupled states must preserve declared SI or normalised units for current, density, temperature, pressure, q, beta, power, flux, and timing.	tests/test_integrated_scenario.py; tests/test_cross_module_physics.py; validation/benchmark_integrated_scenario_coupling.py; validation/reports/integrated_scenario_coupling.json; validation/reports/integrated_scenario_coupling.md	validation_gap	#49
src/scpn_control/core/kinetic_efit.py	Kinetic-EFIT coupling claims must declare Thomson or profile-derived electron density and temperature points, ion-temperature points, fast-ion pressure fraction, anisotropy sigma, MSE pitch-angle constraints when used, radial interpolation geometry, pressure-consistency residual, diagnostic/profile/fast-ion/MSE source provenance, matched pressure, q-profile, and anisotropy reference tolerances, and exclusion from facility-grade P-EFIT unless matched reference equilibria pass the fail-closed admission gate.	Lao et al. 1985 EFIT equilibrium reconstruction; MSE-constrained kinetic EFIT workflow; Repository fixed-boundary realtime-EFIT contract	R and Z in metres, temperatures in keV, density in 10^19 m^-3, MSE pitch angle in degrees, pressure in pascals, beta dimensionless, and q-profile dimensionless.	tests/test_kinetic_efit.py requires measured profile channels, radial interpolation, measured Ti use, anisotropy residuals, MSE q-profile response, fast-ion pressure checks, and fail-closed kinetic-EFIT claim evidence admission; validation/benchmark_kinetic_efit_claims.py publishes deterministic bounded synthetic claim evidence with explicit facility-claim exclusion; validation/reports/kinetic_efit_claims.json records bounded provenance, interpolation geometry, pressure consistency, fast-ion beta, and q-profile endpoints	bounded_model	#48
src/scpn_control/core/gk_eigenvalue.py	Native linear GK eigenvalue solve must match external TGLF, GENE, GS2, CGYRO, or QuaLiKiz growth rates and real frequencies for the same Miller geometry and species inputs.	Miller et al. 1998 local equilibrium; GENE and GACODE published input-output contracts	Growth rate and frequency normalised consistently to c_s/a or declared external-code convention.	ROADMAP.md local-dispersion overprediction note; docs/competitive_analysis.md linear GK quantitative accuracy status; validation/validate_gk_crosscode.py strict real-binary schema-versioned and digest-bound evidence gate	external_dependency_blocked	#47
src/scpn_control/core/momentum_transport.py	Momentum transport claims must declare NBI torque, collisional damping, viscous momentum diffusion, rotation-profile boundary conditions, angular-momentum units, and the coupling boundary to the integrated transport solver.	tokamak toroidal momentum transport references; repository NBI torque and rotation-profile contract	SI newton metres, kg m^2/s^2, rad/s, metres, seconds, density in m^-3, and momentum diffusivity in m^2/s.	tests/test_momentum_transport.py; tests/test_momentum_integration.py	validation_gap	#49
src/scpn_control/core/neural_equilibrium.py	Neural equilibrium pretraining may use bounded synthetic Solovev-like equilibria, but fine-tuning and public predictive claims require fail-closed claim evidence tied to the same weight checksum and comparison against identical P-EFIT or documented public reference equilibria for psi, pressure, q-profile, LCFS boundary, and magnetic-axis position.	EFIT/P-EFIT equilibrium reconstruction workflow; Repository neural equilibrium model contract; Bounded Solovev-like synthetic equilibrium pretraining contract	SI magnetic flux, pressure, metre-scale geometry, and dimensionless q-profile arrays on declared grids.	tests/test_neural_equilibrium.py synthetic pretraining, reproducibility, JAX-compatible weight, fail-closed claim evidence, checksum matching, and real-EFIT admission tests; tests/test_jax_neural_equilibrium.py synthetic-pretrained weight loading through JAX inference; validation/benchmark_neural_equilibrium_pretraining.py deterministic synthetic pretraining and claim-admission benchmark; validation/validate_neural_equilibrium_reference.py strict digest-bound P-EFIT/reference artefact gate with report schema, payload digest, artefact file digest, portable paths, duplicate reference-set rejection, and blocked public-claim state; validation/convert_mast_efm_neural_equilibrium_reference.py converts public MAST EFM measured-shot Zarr campaigns into checksum-bound reference-candidate arrays while preserving strict predictive-claim blockage pending exact-model predictions and metric admission; validation/evaluate_mast_efm_neural_equilibrium.py evaluates current neural-equilibrium weights against converted public MAST EFM reference-candidate arrays with exact profile_r/profile_z grids, writes prediction artefacts, reports flux masked RMSE plus derived magnetic-axis and LCFS residuals, and preserves fail-closed predictive-claim blockage	external_dependency_blocked	#50
src/scpn_control/core/neural_transport.py	Neural transport claims must declare input feature normalisation, QLKNN weight provenance, prediction targets, fallback critical-gradient thresholds, bounded density-channel particle diffusivity, bounded profile closure provenance, local benchmark errors, strict reference-artifact admission, weight checksum matching, uncertainty output, out-of-domain handling, and cross-validation against reference transport cases.	QuaLiKiz neural network transport surrogate references; repository QLKNN weight and metric contract	Inputs and outputs use declared transport feature units, diffusivity in m^2/s or declared normalisation, fluxes in SI or gyro-Bohm units with conversion metadata.	tests/test_neural_transport.py density-gradient and shear-dependent fallback particle diffusivity; tests/test_neural_transport_core.py profile fallback particle-channel checks, bounded closure provenance, fallback gating, fail-closed claim evidence, and checksum-matched reference admission checks; tests/test_qlknn_transport.py; validation/benchmark_neural_transport_claims.py deterministic local claim-admission benchmark; validation/validate_neural_transport_reference.py strict digest-bound QuaLiKiz/reference artifact gate	external_dependency_blocked	#50
src/scpn_control/core/neural_turbulence.py	Neural turbulence claims must declare QLKNNSurrogate inputs, finite strictly ordered physical profile grids, feature scaling, banana-regime electron collisionality, bounded analytic quasilinear target variables, fallback behaviour, uncertainty handling, local analytic-target benchmark errors, strict reference-artifact admission, exact weight checksum matching, and cross-validation boundary against gyrokinetic or quasilinear turbulence references.	QLKNN turbulence surrogate references; repository neural turbulence surrogate contract	Feature and target units follow the declared turbulence surrogate schema; diffusivities, growth rates, and fluxes require explicit SI or normalised-unit metadata.	tests/test_neural_turbulence.py collisionality scaling, analytic target, training, save-load, denormalisation, fail-closed claim evidence, and checksum-matched reference admission checks; validation/benchmark_neural_turbulence_claims.py deterministic local claim-admission benchmark; validation/validate_neural_turbulence_reference.py strict GK-campaign/reference artifact gate	validation_gap	#50
src/scpn_control/core/gk_nonlinear.py	Five-dimensional delta-f flux-tube Vlasov evolution with E cross B bracket, ballooning connection, kinetic electrons, and Sugama collision terms.	Dimits et al. 2000 Cyclone Base Case; Sugama et al. 2006 collision operator	Gyro-Bohm-normalised heat flux and chi_i with explicit R/L_Ti, rho_s, c_s, and reference gradient normalisation.	ROADMAP.md v0.18.0 open revalidation item; docs/joss_paper.md nonlinear GK validation limitation; validation/gk_nonlinear_cyclone.py saturation-evidence assessor	validation_gap	#47
src/scpn_control/core/orbit_following.py	Orbit-following claims must declare guiding-centre equations, magnetic moment handling, finite pitch-angle bounds, banana-orbit width scaling, collision or loss assumptions, ensemble sampling, valid magnetic-geometry bounds, geometry/particle/collision/loss-boundary provenance, and matched banana-width and loss-fraction reference tolerances before external orbit-code or measured fast-ion claims.	Cordey 1981 orbit-width estimate; tokamak guiding-centre orbit references	SI metres, seconds, tesla, electronvolts, kg, coulombs, pitch angle in radians on [0, pi], and ensemble probabilities dimensionless.	tests/test_orbit_following.py verifies guiding-centre domain checks, classifier boundaries, Stix slowing-down, banana-width scaling, first-orbit-loss scaling, ensemble counts, and fail-closed orbit-following claim evidence admission; validation/benchmark_orbit_following_claims.py publishes deterministic bounded synthetic claim evidence with explicit external-code claim exclusion; validation/reports/orbit_following_claims.json records bounded geometry, particle, collision, loss-boundary, banana-width, first-orbit-loss, and ensemble-count evidence; validation/validate_orbit_reference.py strict orbit reference artefact gate	validation_gap	#49
src/scpn_control/control/realtime_efit.py	Real-time equilibrium reconstruction claims must declare the fixed-boundary Grad-Shafranov solve, polynomial p-prime and FF-prime source profiles, diagnostic response interpolation, Rogowski current reconstruction, macroscopic-shape extraction assumptions, diagnostic provenance, matched-reference source, psi/Ip/q95/beta_pol/li tolerances, and facility-claim admission status.	Lao et al. 1985 EFIT equilibrium reconstruction; Strait et al. 2019 real-time EFIT workflow references; Repository GEQDSK and magnetic-diagnostic validation contracts	SI metres, webers per radian, tesla, amperes, pascals per weber, FF-prime units, and dimensionless q95, beta_pol, li, elongation, and triangularity.	tests/test_realtime_efit.py fixed-boundary solve and diagnostic reconstruction checks; tests/test_kinetic_efit.py kinetic EFIT integration checks; tests/test_validate_real_shots_equilibrium.py GEQDSK source residual checks; tests/test_realtime_efit.py claim-evidence provenance, matched-reference admission, and invalid-reference checks; validation/benchmark_efit_lite_claims.py bounded synthetic EFIT-lite claim-admission benchmark; validation/reports/efit_lite_claims.json bounded synthetic EFIT-lite claim report	bounded_model	#48
src/scpn_control/core/gyrokinetic_transport.py	Reduced gyrokinetic transport claims must declare the dispersion relation, instability branch classification, quasilinear heat-flux closure, critical-gradient threshold, saturation rule, positive integer mode-count domain, tokamak geometry ordering, and mapping from local GK outputs to transport coefficients.	Cyclone Base Case gyrokinetic benchmark; quasilinear gyrokinetic transport closure references	Growth rates and frequencies in declared normalised units, gradients dimensionless or m^-1 with explicit convention, rho and epsilon dimensionless, geometry in metres, heat flux in gyro-Bohm or SI units with conversion metadata.	tests/test_gyrokinetic_transport.py dispersion branches, quasilinear fluxes, saturation monotonicity and boundedness, profile evaluation, and invalid-domain checks; tests/test_gk_benchmark_linear.py	validation_gap	#47
src/scpn_control/control/gym_tokamak_env.py	0D/1D control plants must declare reduced-state equations, conservation assumptions, and controller-validity bounds before being used for hardware or facility claims.	Wesson 2011 tokamak transport references; Repository Gymnasium plant and digital-twin contracts	Declared plasma current, temperature, density, confinement, and actuator units per state vector field.	README.md validation limitation; docs/use_cases.md synthetic disruption prediction status; tests/test_gym_tokamak_env.py reduced-order plant bounds and action-contract checks	bounded_model	#51
src/scpn_control/control/rwm_feedback.py	RWM feedback claims must declare the no-wall and ideal-wall beta limits, resistive-wall L/R time, optional wall-plasma gap correction, rotation-stabilisation term, active proportional or derivative feedback coupling, controller latency, coil coupling, sensor/coil topology, ideal-kink exclusion boundary, reference source, closed-loop growth-rate tolerance, and facility-claim admission status.	Bondeson and Ward 1994 resistive-wall-mode growth-rate model; Fitzpatrick 2001 rotation-stabilisation contribution; Strait et al. 2003 wall-plasma gap correction; Garofalo et al. 2002 active feedback experiments	Normalised beta dimensionless, wall time in seconds, toroidal rotation in rad/s, wall and plasma radii in metres, feedback gain dimensionless per declared coil coupling, growth rate in s^-1.	tests/test_rwm_feedback.py growth-rate, rotation, wall-geometry, feedback, ideal-kink, and required-gain checks; tests/test_rwm_feedback.py claim-evidence provenance, external tolerance admission, and invalid-domain checks; validation/benchmark_rwm_claims.py bounded local RWM claim-admission benchmark; validation/reports/rwm_claims.json bounded local RWM claim report	bounded_model	#51
src/scpn_control/core/tearing_mode_coupling.py	Sawtooth-to-NTM seeding claims must declare sawtooth crash trigger, seed-island generation, rational-surface coupling, phase and amplitude assumptions, bounded bootstrap-current fraction, NTM coupling path, and exclusion of full nonlinear MHD crash dynamics.	sawtooth crash and NTM seeding references; repository tearing-mode coupling contract	Time in seconds, island width in metres, q dimensionless, rho dimensionless, phase in radians, local bootstrap-current fraction within [0, 1], and amplitude units declared per coupling signal.	tests/test_tearing_mode_coupling.py; tests/test_integrated_scenario.py	validation_gap	#49
src/scpn_control/control/tokamak_digital_twin.py	Digital-twin claims must declare the 2D poloidal grid, q-profile topology update, rational-surface island mask, finite-difference diffusion, radiation-loss scaling with density and effective charge, actuator latency, RNG seed, IDS export assumptions, external simulator artifact provenance, and bounded online model-update parameters.	Repository digital-twin runtime contract; Wesson 2011 radiation-loss reference; TRANSP integrated modelling evidence contract; TSC time-dependent simulation evidence contract; Bayesian optimisation for bounded model calibration	Declared normalised grid indices, keV, m^-3, dimensionless q-profile values, actuator-lag summary units, RNG seed metadata, and IDS-compatible pulse history fields.	tests/test_tokamak_digital_twin.py deterministic twin checks; tests/test_digital_twin_physics.py physics-path checks; tests/test_digital_twin_online_update.py external artifact, loss, Bayesian-update, and deterministic benchmark checks; tests/test_digital_twin_reference_validation.py strict digital-twin artifact gate including TRANSP and TSC; validation/benchmark_digital_twin_online_update.py deterministic bounded online-update benchmark; validation/validate_digital_twin_reference.py strict reference-artifact gate	bounded_model	#51
src/scpn_control/core/integrated_transport_solver.py	Integrated transport claims must declare the axis-to-edge radial grid, heat and particle diffusion equations, neoclassical closure, bootstrap-current fit, source deposition terms, boundary conditions, timestep limits, and coupling contracts to pedestal and gyrokinetic closures.	Chang-Hinton neoclassical transport model; Sauter et al. 1999 bootstrap-current fits; repository integrated transport solver contract	SI metres, seconds, m^-3, eV, W/m^3, m^2/s, amperes per square metre, and dimensionless profile coordinates with explicit axis-to-edge normalisation metadata.	tests/test_integrated_transport_solver.py; tests/test_transport_energy_conservation.py; tests/test_transport_neoclassical_guards.py	validation_gap	#49
src/scpn_control/control/volt_second_manager.py	Volt-second management claims must declare inductive flux, resistive loop-voltage integration, Ejima startup flux, bootstrap-current correction, flat-top duration estimate, ramp and ramp-down decomposition, flux-budget margin assumptions, finite positive machine constants, nonnegative current and voltage domains, positive timesteps, and strictly ordered bootstrap-profile grids.	Wesson 2011 tokamak loop-voltage and flux-balance equations; Ejima et al. 1982 startup flux coefficient; ITER Physics Basis 1999 flat-top flux-budget references; Repository fail-closed volt-second claim-admission contract	SI webers, volt-seconds, henries, ohms, amperes, mega-amperes, seconds, metres, normalised profile radius, and dimensionless Ejima coefficient.	tests/test_volt_second_manager.py flux budget, scenario analysis, bootstrap-profile, domain-boundary, and claim-admission checks; validation/validate_volt_second_reference.py strict volt-second reference artifact gate; validation/benchmark_volt_second_claims.py bounded claim-admission benchmark	bounded_model	#51

Components

DIII-D experimental replay

• Fidelity status: reference_validated
• Module path: validation/reference_data/diiid
• Full-fidelity public claim: allowed
• External validation tracker: none
• Covered source paths: 0
• Required actions:
• Keep GEQDSK and disruption-shot reference manifests covered by checksum verification
• Use the MDSplus acquisition spec path for new facility artefacts instead of synthetic fixtures

DT burn control and alpha-heating model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/burn_controller.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Attach strict documented public, integrated-transport benchmark, or measured burn replay artifacts before reactor-control claims
• Replace the burn-fraction approximation with a calibrated slowing-down and ash-removal model before facility extrapolation

ELM crash and RMP suppression approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/elm_model.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate ELM frequency, crash depth, pedestal profile drops, RMP suppression windows, and peak heat flux against measured H-mode campaign or published ELM cases
• Persist schema-versioned pre-crash, post-crash, event-catalog, and RMP artifact URIs with SHA-256 digests, pedestal rho grids, event windows, Type-I energy-fraction bounds, metrics, tolerances, and canonical payload digests with every ELM validation artefact
• Keep full-fidelity ELM/RMP claims blocked until measured or documented public reference artifacts pass the strict admission gate

EPED pedestal and peeling-ballooning approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/eped_pedestal.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate pedestal height and width against published EPED benchmark points or measured pedestal databases
• Record bootstrap-current, beta-limit, and shaping inputs for every pedestal validation artefact
• Keep full-fidelity EPED pedestal claims blocked until measured pedestal-database or documented public reference artifacts pass the strict admission gate

Grad-Shafranov fusion-kernel numerical contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/fusion_kernel.py
• Full-fidelity public claim: blocked
• External validation tracker: #48 — Equilibrium and reconstruction reference artefacts
• Covered source paths: 1
• Required actions:
• Validate reconstructed equilibria against EFIT, GEQDSK, or published fixed-boundary benchmark cases
• Preserve residual norms, convergence metadata, and Rust/Python parity evidence for every validation artefact

JAX gyrokinetic numerical parity guard

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/jax_gk_solver.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Run backend parity over CBC, kinetic-electron TEM, and stable-mode cases with pinned tolerances
• Keep CPU/GPU backend parity evidence current for every release and continue blocking quantitative GK claims until external-code validation artefacts are supplied

Kuramoto-Sakaguchi phase synchronisation runtime

• Fidelity status: bounded_model
• Module path: src/scpn_control/phase/kuramoto.py
• Full-fidelity public claim: blocked
• External validation tracker: #53 — Hardware, HDL, CODAC/EPICS, and runtime deployment evidence
• Covered source paths: 1
• Required actions:
• Validate synchronisation and stability metrics against published Kuramoto-Sakaguchi benchmark cases before broader phase-control claims
• Generate current deployment-target Rust/Python parity and timestep-convergence evidence with validation/benchmark_kuramoto_runtime_evidence.py before deployment-target phase claims

MARFE radiation-condensation density-limit contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/marfe.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate onset temperatures and density limits against measured or published MARFE cases
• Add impurity-specific radiation tables or documented provenance for each supported impurity species
• Keep full-fidelity MARFE density-limit claims blocked until measured MARFE campaign or documented public reference artifacts pass the strict admission gate

Miller local-equilibrium geometry and field-pitch contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gk_geometry.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Compare metric coefficients and field-pitch factors against an independent Miller-geometry reference implementation or external equilibrium-code evidence
• Keep immutable schema-versioned evidence covering circular, shaped, and high-shear local equilibria

NTM island evolution and control approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/ntm_dynamics.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate island growth and suppression against measured or published NTM benchmark cases
• Persist q-profile, rational-surface, seed-island, and ECCD alignment metadata with each validation case
• Keep full-fidelity NTM forecasting and suppression claims blocked until measured NTM campaign or documented public reference artifacts pass the strict admission gate

RZIP rigid vertical stability model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/rzip_model.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Calibrate vertical_inertia_kg against a documented plasma inertia or facility parameter source before facility claims
• Validate vertical growth rates against a reference RZIP, CREATE-L/NL, TSC, or measured vertical-displacement benchmark

SCPN FPGA fixed-point export boundary

• Fidelity status: bounded_model
• Module path: src/scpn_control/scpn/fpga_export.py
• Full-fidelity public claim: blocked
• External validation tracker: #53 — Hardware, HDL, CODAC/EPICS, and runtime deployment evidence
• Covered source paths: 1
• Required actions:
• Run generated HDL through real Vivado, Quartus, or Yosys synthesis before hardware readiness claims
• Persist resource utilisation, timing closure, and bit-accurate simulator evidence for every supported target family

SCPN formal Petri-net verification contract

• Fidelity status: bounded_model
• Module path: src/scpn_control/scpn/formal_verification.py
• Full-fidelity public claim: blocked
• External validation tracker: #53 — Hardware, HDL, CODAC/EPICS, and runtime deployment evidence
• Covered source paths: 1
• Required actions:
• Persist formal verification reports with every safety-critical compiled controller artifact
• Validate certification packages with an external safety-case review before hardware-control claims
• Promote optional SMT-backed proof obligations only after solver-specific proof artifacts are persisted
• Require schema-versioned Z3 report payload digests to match safety-critical proof manifests before artifact admission
• Resolve typed readiness artifact URIs under an explicit artifact root and validate target-hardware timing reports through the E2E latency evidence gate before promotion readiness.
• Require qualified HIL replay, HDL export, CODAC/EPICS runtime, and WebSocket runtime evidence artifacts before controller safety-case promotion readiness.
• Admit safety-critical .scpnctl artifacts only through the bounded formal-verification manifest gate
• Bind admitted proof manifests to the exact canonical artifact payload digest and declared report digest
• Bind promoted controller safety-case bundles to the same controller artifact digest across formal proof, differentiable-transport, and digital-twin update evidence
• Persist controller safety-case bundles with schema-versioned integrity manifests before replay admission
• Keep controller safety-case readiness blocked until external physics validation, target-hardware timing, qualified runtime/hardware evidence, and independent safety-review digests are all present
• Prefer typed readiness artifacts with safe relative URIs, producers, timestamps, and kind-specific SHA-256 digests over anonymous promotion digests
• Persist controller safety-case readiness decisions with schema-versioned integrity manifests before promotion replay
• Publish optional Z3 bounded-model-checking artifacts with every SMT-backed proof obligation
• Treat missing z3-solver as blocked SMT evidence, not as a successful proof

VMEC-lite stellarator equilibrium approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/vmec_lite.py
• Full-fidelity public claim: blocked
• External validation tracker: #48 — Equilibrium and reconstruction reference artefacts
• Covered source paths: 1
• Required actions:
• Validate surface geometry and rotational-transform outputs against VMEC or published stellarator benchmark equilibria before full VMEC claims
• Persist Fourier truncation, field periods, pressure profile, iota profile, current assumption, sampled major-radius bounds, residual tolerance, reference errors, and admission status for every promoted VMEC-lite claim

advanced SOC turbulence learning controller

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/advanced_soc_fusion_learning.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Replace sandpile turbulence proxy with gyrokinetic or measured turbulence evidence before transport-control claims
• Validate Q-learning policy behaviour against replayed plasma-control objectives before control-readiness claims

auxiliary current-drive deposition and efficiency model

• Fidelity status: bounded_model
• Module path: src/scpn_control/core/current_drive.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Attach strict ray-tracing, Fokker-Planck, measured deposition, or documented public artifacts before external current-drive claims
• Persist source power, deposition kernel, rho grid, density and temperature profiles, launch geometry, and efficiency coefficients for every promoted current-drive claim

blob transport and scrape-off-layer approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/blob_transport.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate blob velocity and spreading against measured probe-campaign or published SOL filament cases
• Persist schema-versioned reference, profile, and detector artifact URIs with SHA-256 digests, SOL unit contracts, separatrix-to-wall coordinates, detector event domains, blob-size domains, magnetic-geometry metadata, metrics, tolerances, and canonical payload digests with each validation artefact
• Keep full-fidelity SOL blob-transport claims blocked until measured or documented public reference artifacts pass the strict admission gate

bounded analytical approximations in physics modules

• Fidelity status: bounded_model
• Module path: src/scpn_control/core
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 0
• Required actions:
• Keep this parent entry as a non-source guardrail for future core approximation markers
• Require every new core approximation marker to land with a source-specific traceability entry and validation evidence

bounded control plant approximations

• Fidelity status: bounded_model
• Module path: src/scpn_control/control
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 0
• Required actions:
• Keep this parent entry as a non-source guardrail for future reduced-order control plant markers
• Require every new control plant marker to land with a controller-specific traceability entry and replay or higher-fidelity evidence

bounded phase and spiking runtime approximations

• Fidelity status: bounded_model
• Module path: src/scpn_control
• Full-fidelity public claim: blocked
• External validation tracker: #53 — Hardware, HDL, CODAC/EPICS, and runtime deployment evidence
• Covered source paths: 0
• Required actions:
• Keep this parent entry as a non-source guardrail for future phase, spiking, and replay runtime markers
• Require every new runtime marker to land with a source-specific traceability entry plus hardware-target or replay-fixture evidence

bounded static structured-singular-value control analysis

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/mu_synthesis.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Attach strict documented public, external mu-toolbox, or measured control replay artifacts before validated robust-control claims
• Wire a validated frequency-dependent H-infinity synthesis backend before making full D-K synthesis claims
• Persist benchmark plants, frequency grids, D-scale fits, mu upper/lower bounds, and canonical evidence payload digests for every promoted controller claim

checkpoint state serialisation boundary contract

• Fidelity status: bounded_model
• Module path: src/scpn_control/core/checkpoint.py
• Full-fidelity public claim: blocked
• External validation tracker: #53 — Hardware, HDL, CODAC/EPICS, and runtime deployment evidence
• Covered source paths: 1
• Required actions:
• Version checkpoint schemas before long-running production campaigns depend on replay compatibility
• Add migration fixtures for every future checkpoint schema change

density control and particle-source model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/density_controller.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Validate Greenwald fraction and particle inventory changes against measured discharge, external particle-balance, or facility replay references before facility-calibrated claims
• Persist geometry, transport profiles, actuator limits, diagnostic source, timestep/CFL state, source integrals, particle inventory deltas, reference tolerances, and claim-admission status with every promoted density-control claim

differentiable transport facade contract

• Fidelity status: bounded_model
• Module path: src/scpn_control/core/differentiable_transport.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Wire each remaining legacy transport surface through an equivalent differentiable path before claiming end-to-end transport autodiff
• Validate differentiable transport profiles and equilibrium-weighted gradients against measured discharges or published integrated-modelling benchmarks
• Persist backend, dtype, runtime-provenance, radial-grid, boundary-condition, rollout-length, equilibrium-grid, flux-weighting, gradient-tolerance, gradient-audit digest, and replay-drift metadata for controller-tuning campaigns
• Replace bounded reduced-gyrokinetic and JAX GK stiffness closures with externally validated GK transport coefficients before quantitative transport-control claims
• Bind promoted differentiable-transport evidence to the safety-critical controller proof artifact digest when used in a controller safety case

digital twin online model updating

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/digital_twin_online_update.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Provide validated TRANSP, TSC, measured-discharge, or documented public-reference artifacts before measured replay claims
• Validate online update trajectories against replayed or measured discharge histories before deployment use
• Persist simulator artifact hashes, units, case ids, strictly increasing time bases, observation digests, prior digests, result digests, finite loss-history minima, parameter-domain admission, and baseline-improvement evidence for every promoted update campaign
• Bind promoted online-update evidence to the safety-critical controller proof artifact digest when used in a controller safety case

direct free-boundary tracking controller

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/free_boundary_tracking.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Attach strict documented public, measured-replay, or external equilibrium benchmark artifacts before facility-control claims
• Attach actuator, latency, and sensor-calibration evidence for the target device before deployment claims

disruption mitigation contract layer

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/disruption_contracts.py
• Full-fidelity public claim: blocked
• External validation tracker: #52 — Disruption, halo-current, and mitigation benchmark artefacts
• Covered source paths: 1
• Required actions:
• Replace synthetic disruption signals with measured labelled disruption windows before predictive claims
• Validate mitigation-cocktail, halo, runaway, and TBR couplings against experimental or benchmark artefacts

disruption sequence phase-ordering contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/disruption_sequence.py
• Full-fidelity public claim: blocked
• External validation tracker: #52 — Disruption, halo-current, and mitigation benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate phase timing, post-quench temperature, and mitigation branches against labelled measured disruption windows
• Persist shot identifiers, phase labels, thermal-quench duration, radiation-time assumption, timing tolerances, and mitigation metadata for sequence validation

external gyrokinetic interfaces

• Fidelity status: external_dependency_blocked
• Module path: src/scpn_control/core/gk_interface.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Run each interface against a real executable or documented public reference output
• Persist schema-versioned artifacts with safe deck/raw-output/parsed-output URIs and SHA-256 digests
• Promote parser fixtures from mock subprocesses to immutable external-code artefacts sealed by canonical payload digests

federated disruption prediction

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/federated_disruption.py
• Full-fidelity public claim: blocked
• External validation tracker: #52 — Disruption, halo-current, and mitigation benchmark artefacts
• Covered source paths: 1
• Required actions:
• Supply measured multi-facility disruption shot databases with immutable provenance manifests before claiming cross-facility predictive validation
• Run the same federation and differential-privacy contracts against those measured facility datasets before deployment claims

full-chain uncertainty quantification contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/uncertainty.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Calibrate uncertainty priors against measured or published scenario ensembles before predictive facility-UQ claims
• Persist random seeds, distribution parameters, sample counts, percentile ordering, finite-output checks, convergence diagnostics, sensitivity metrics, reference tolerances, and claim-admission status with every UQ artefact

geometry-neutral stellarator replay fixture

• Fidelity status: bounded_model
• Module path: src/scpn_control/scpn/geometry_neutral_replay.py
• Full-fidelity public claim: blocked
• External validation tracker: #48 — Equilibrium and reconstruction reference artefacts
• Covered source paths: 1
• Required actions:
• Replace synthetic W7-X-like replay inputs with measured or benchmark stellarator field-line artefacts before device-control claims
• Generate schema-versioned replay evidence for every promoted replay and keep measured or benchmark device claims blocked until external artefact digests and non-synthetic magnetic provenance are supplied

gyrokinetic OOD detector distribution-bound contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gk_ood_detector.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Calibrate thresholds against real or published GK campaign ensembles
• Keep strict schema-versioned calibration evidence with Mahalanobis-metric provenance, false-positive, false-negative, and OOD-recall acceptance criteria for deployment gating

gyrokinetic online learner stability contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gk_online_learner.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Validate learner updates on immutable gyrokinetic campaign artefacts with held-out distribution-shift cases
• Persist model weights, rollback decisions, validation metrics, OOD thresholds, and source provenance for every online update

gyrokinetic species and collision bounded-operator contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gk_species.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Validate bounded test-particle collision coefficients against a published gyrokinetic or Fokker-Planck reference case before facility claims
• Add field-particle momentum-conservation and full multispecies collision-operator evidence before claiming quantitative collisional damping

halo current and runaway electron disruption model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/halo_re_physics.py
• Full-fidelity public claim: blocked
• External validation tracker: #52 — Disruption, halo-current, and mitigation benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate halo current and runaway-current envelopes against measured disruption databases before mitigation claims
• Attach wall-contact geometry and impurity-radiation evidence before extrapolating beyond the declared ensemble domain
• Persist ensemble seed, run count, halo/runaway P95 metrics, toroidal-peaking-factor summary, reference source, tolerances, errors, and admission status before promoted mitigation claims

ideal-MHD stability metric approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/stability_mhd.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Compare stability metrics against an independent MHD stability code or published benchmark profiles
• Store profile grids, interpolation choices, and unstable-region metadata with each stability validation artefact

integrated scenario coupling contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/integrated_scenario.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate coupled scenario trajectories against measured discharges or published integrated-modelling benchmarks
• Persist module-by-module state exchange, timestep, and convergence metadata with every scenario artefact

kinetic EFIT pressure and q-profile coupling

• Fidelity status: bounded_model
• Module path: src/scpn_control/core/kinetic_efit.py
• Full-fidelity public claim: blocked
• External validation tracker: #48 — Equilibrium and reconstruction reference artefacts
• Covered source paths: 1
• Required actions:
• Validate kinetic pressure, q-profile, and anisotropy residuals against matched EFIT or P-EFIT reference equilibria before facility claims
• Persist diagnostic source, interpolation geometry, fast-ion model provenance, MSE calibration, uncertainty, reference tolerances, and claim-admission status for every promoted kinetic-equilibrium claim

linear gyrokinetic cross-code agreement

• Fidelity status: external_dependency_blocked
• Module path: src/scpn_control/core/gk_eigenvalue.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Install or provide real external GK binaries
• Run native-vs-external benchmark cases and store parser artefact evidence
• Persist SHA-256 digests for external input decks, external outputs, native inputs, and canonical comparison reports before full-fidelity GK claims

momentum transport and torque-balance approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/momentum_transport.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate torque deposition and rotation evolution against measured or published NBI momentum cases
• Add acceptance artefacts for low-torque, high-torque, and sign-changing rotation profiles

neural equilibrium cross-validation

• Fidelity status: external_dependency_blocked
• Module path: src/scpn_control/core/neural_equilibrium.py
• Full-fidelity public claim: blocked
• External validation tracker: #50 — Neural surrogate validation artefacts
• Covered source paths: 1
• Required actions:
• Acquire matched P-EFIT reference equilibria or an openly redistributable equivalent
• Persist schema-versioned reference and prediction artefact URIs with SHA-256 digests, exact weight checksum, grid shape, target schema, unit contracts, and declared psi/pressure/q-profile/boundary/axis tolerances
• Keep predictive equilibrium claims blocked until immutable reference artefacts are sealed by canonical payload digests and validate the exact surrogate weight checksum

neural transport surrogate validation contract

• Fidelity status: external_dependency_blocked
• Module path: src/scpn_control/core/neural_transport.py
• Full-fidelity public claim: blocked
• External validation tracker: #50 — Neural surrogate validation artefacts
• Covered source paths: 1
• Required actions:
• Acquire or generate immutable reference QLKNN or transport benchmark cases for cross-validation
• Persist schema-versioned reference and prediction artifact URIs with SHA-256 digests, exact weight checksum, QLKNN-10D feature schema, target schema, uncertainty metadata, OOD decisions, reference metrics, tolerances, and admission status with every surrogate evaluation
• Gate quantitative QuaLiKiz, QLKNN, or documented-reference transport claims on strict reference artifacts sealed by canonical payload digests and matched to the exact neural weight checksum

neural turbulence surrogate validation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/neural_turbulence.py
• Full-fidelity public claim: blocked
• External validation tracker: #50 — Neural surrogate validation artefacts
• Covered source paths: 1
• Required actions:
• Validate surrogate outputs against immutable gyrokinetic or QuaLiKiz turbulence benchmark cases
• Persist feature schema, weight checksum, local Q_i/Q_e/Gamma_e errors, critical-gradient accuracy, reference source, tolerances, and claim-admission status before quantitative turbulence claims
• Gate quantitative gyrokinetic, QuaLiKiz, or documented-reference turbulence claims on strict reference artifacts that match the exact neural weight checksum

nonlinear gyrokinetic heat-flux saturation

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gk_nonlinear.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Run a long enough nonlinear CBC campaign to saturated chi_i
• Compare saturated heat flux against published or real cross-code reference data

orbit-following guiding-centre approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/orbit_following.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate orbit widths and loss fractions against an independent orbit-following code or published benchmark cases before external orbit-code claims
• Persist particle species, pitch, energy, geometry, ensemble seed or counts, collision model, wall/loss boundary, reference tolerances, and claim-admission status with each validation artefact

real-time EFIT-lite equilibrium reconstruction

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/realtime_efit.py
• Full-fidelity public claim: blocked
• External validation tracker: #48 — Equilibrium and reconstruction reference artefacts
• Covered source paths: 1
• Required actions:
• Validate reconstructed psi, Ip, q95, beta_pol, and li against matched EFIT or P-EFIT equilibria before facility claims
• Replace synthetic diagnostic-response evidence with measured flux-loop, B-probe, and Rogowski artefacts when facility data are available

reduced gyrokinetic transport closure contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/gyrokinetic_transport.py
• Full-fidelity public claim: blocked
• External validation tracker: #47 — External gyrokinetic validation artefacts
• Covered source paths: 1
• Required actions:
• Compare predicted growth rates and transport coefficients with external GK or published quasilinear benchmark cases
• Store branch classification and saturation metadata for every transport-closure validation case

reduced-order plant and control environments

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/gym_tokamak_env.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Separate reduced-order training claims from facility-control claims in generated reports
• Add plant-model validity bounds and cross-checks against higher-fidelity replay cases

resistive-wall-mode feedback model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/rwm_feedback.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Validate beta-window, rotation, and feedback-gain predictions against measured RWM shots or external MHD stability references before facility-control claims
• Persist wall geometry, rotation profile, coil coupling, sensor geometry, controller latency, and beta-limit provenance for every promoted RWM claim

sawtooth-to-NTM seeding approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/tearing_mode_coupling.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate seed-island amplitudes and NTM triggering windows against measured or published sawtooth-triggered NTM cases
• Persist pre-crash q-profile, crash amplitude, rational-surface, and coupling metadata with each validation case

tokamak digital twin topology and diffusion model

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/tokamak_digital_twin.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Provide validated TRANSP, TSC, measured-discharge, or documented public-reference artifacts before measured replay claims
• Replace normalised 2D diffusion dynamics with equilibrium and transport-calibrated state evolution before facility twin claims
• Validate online update trajectories against replayed or measured discharge histories before deployment use

transport solver neoclassical and source-term approximation contract

• Fidelity status: validation_gap
• Module path: src/scpn_control/core/integrated_transport_solver.py
• Full-fidelity public claim: blocked
• External validation tracker: #49 — Transport, edge, MHD, and scenario benchmark artefacts
• Covered source paths: 1
• Required actions:
• Validate radial transport profiles against a measured discharge or published integrated-modelling benchmark
• Persist source deposition, boundary condition, and convergence metadata with every transport validation artefact

volt-second budget and flux-consumption manager

• Fidelity status: bounded_model
• Module path: src/scpn_control/control/volt_second_manager.py
• Full-fidelity public claim: blocked
• External validation tracker: #51 — Plasma-control and facility replay artefacts
• Covered source paths: 1
• Required actions:
• Attach strict documented public, measured loop-voltage replay, or external scenario benchmark artifacts before scenario-duration claims
• Replace bootstrap-current proxy with neoclassical or transport-solver evidence before facility extrapolation