{ "KAIROS": { "card": { "name": "KAIROS", "function": "CONTROL", "status": "BUILT", "phase": 1, "provenance": "TWIN", "retired_by": "validated real-time plant controller (device-in-the-loop)", "gates": [ "AC-24", "AC-25" ], "note": "real-time closed-loop MPC control (analytic finite-horizon QP); supplies the model-free L4 clamp that KGATE enforces", "available": true }, "benchmark": { "member": "KAIROS", "live_tracking_rms_frac": 0.0461, "live_expB_model_failure": { "adversaries": [ "drift", "edge_seeker", "nan_garbage" ], "steps": 150000, "escapes": 0, "catch_rate": 1.0 }, "live_mpc_step_us": 77.8, "sourced": { "file": "track5_control/clamp_activation_stats.csv", "headline": "0 escapes / 150k steps / 3000 injected (AC-25); tracking <5%" } } }, "KBENCH": { "card": { "name": "KBENCH", "function": "BENCHMARK", "status": "BUILT", "phase": 3, "provenance": "n/a", "retired_by": "community-standard fusion-ML benchmarks", "gates": [], "note": "open, citable ML benchmark suite for fusion \u2014 real CGYRO turbulence + MAST disruption tasks with fixed splits, metrics and KODEX baselines to beat. Bring your own model; move the community forward", "available": true }, "benchmark": { "member": "KBENCH", "live_benchmark_suite": { "n_tasks": 3, "tasks": { "cgyro-turbulence-flux": { "inputs": [ "a_LT", "shear" ], "target": "log10 Q_tot (regression) + turbulent/quiet (classification)", "n_samples": 16, "metric": "R2 (regression) / leave-one-out accuracy (classification)", "loader": "kronos_ml.data.cgyro_flux_map_final()", "baseline_code": "KYRO", "baseline_score": "R2 ~0.86, turbulent/quiet 16/16", "note": "real CGYRO A1e saturated-flux (mu=400 representative)" }, "mast-disruption": { "inputs": "physics features (Ip family + EFIT + n=1 Mirnov / P_rad)", "target": "disruptive (binary)", "n_samples": 591, "metric": "ROC-AUC (+ independent-precursor AUC)", "loader": "kronos_ml.data.kward_real()", "baseline_code": "KWARD", "baseline_score": "AUC ~0.98, independent-precursor 0.975", "note": "real MAST shots (FAIR-MAST); labels are heuristic Ip-quench" }, "cgyro-rom-compressibility": { "inputs": "flux-database matrix (points x [inputs, fluxes])", "target": "rel-L2 reconstruction error vs retained bond dimension", "n_samples": 16, "metric": "rel-L2 vs rank", "loader": "kronos_ml.data.cgyro_flux_map_final()", "baseline_code": "KTENSOR", "baseline_score": "effective rank 2.93/4 (not strongly low-rank)", "note": "honest ROM characterization" } }, "how_to_use": "load via each task's loader, use the fixed reproducible split, report the metric, and try to beat the named KODEX baseline_code", "verdict": "3 open, citable fusion-ML tasks (CGYRO turbulence, MAST disruption, flux ROM) with real on-disk data + reproducible KODEX baselines \u2014 a community leaderboard starting point, not a private result" }, "caveat": "small by mainstream-ML standards (CGYRO = 16 pts); honest pilot fusion-ML benchmarks" } }, "KBREED": { "card": { "name": "KBREED", "function": "breeder", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "OpenMC (Monte-Carlo neutron transport)", "gates": [ "BR-neut" ], "note": "tritium breeding-ratio surrogate (Hyperion blanket) \u2014 fast GP over the toolkit neutronics; OpenMC is the auto-dispatch high-fidelity upgrade", "available": true }, "benchmark": { "member": "KBREED", "live": { "r2_vs_engine": 1.0, "coverage_90": 1.0, "nominal_net_tbr": 0.742 }, "note": "surrogate over toolkit neutronics (analytic); OpenMC upgrade = compute route [A]" } }, "KBURN": { "card": { "name": "KBURN", "function": "burner", "status": "BUILT", "phase": 2, "provenance": "TWIN", "retired_by": "full plant systems model", "gates": [], "note": "burner dispatch surrogate \u2014 fuel mix -> captured power (Aegis/MetroVolt); GP over the DEC dispatch traces", "available": true }, "benchmark": { "member": "KBURN", "live": { "r2": 1.0, "rmse_MW": 0.006, "coverage_90": 1.0, "n_test": 400 }, "sourced": "track5_control/dec_dispatch_summary.csv (dynamic reweight +22% vs static)" } }, "KDRIVE": { "card": { "name": "KDRIVE", "function": "RL-control", "status": "BUILT", "phase": 3, "provenance": "TWIN", "retired_by": "device-validated learned controller", "gates": [], "note": "reinforcement-learning controller \u2014 a feedback policy learned by the cross-entropy method in the twin plant loop; clamped by KGATE", "available": true }, "benchmark": { "member": "KDRIVE", "live": { "learned_policy_tracking_rms": 0.0551, "naive_gain_tracking_rms": 0.1225, "learned_gains": [ 0.935, 1.271, 0.998, 0.617, 1.072, 0.595 ], "note": "cross-entropy-method policy search, twin-in-the-loop" } } }, "KDYN": { "card": { "name": "KDYN", "function": "QDYN", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "KX-L3" ], "note": "REAL quantum dynamics \u2014 Trotterized time-evolution of a transverse-field Ising 'kinetic' Hamiltonian (PennyLane); the honest 1/n_steps cost curve for simulating plasma-like dynamics on a quantum computer. Runs on a simulator now, hardware pluggable; quantum's role in fusion is post-~2036", "available": true }, "benchmark": { "member": "KDYN", "live_trotter": { "system": "3-qubit transverse-field Ising (J=1.0, h=0.8), t=1.0", "framework": "PennyLane Trotter (ApproxTimeEvolution); sim now, real hardware pluggable", "spectral_norm_error_vs_steps": { "1": 1.34637, "2": 0.57791, "4": 0.27635, "8": 0.1362, "16": 0.06776, "32": 0.03381 }, "converges_as": "~1/n_steps (1st-order Trotter, as expected)", "backend_expval_Z0_at_16_steps": 0.2572, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL Trotterized quantum dynamics: 1st-order error falls 1.34637 -> 0.03381 from 1 to 32 steps (~1/n) \u2014 the honest cost curve for simulating plasma-like Hamiltonian dynamics on a quantum computer. Runs on real hardware with KODEX_QC_BACKEND=ibm. No advantage at this size; a real, testable pipeline." }, "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A8_Trotter)", "note": "independent Track-1: 1st-order Trotter error 1.257->0.032 with steps (consistent)" } } }, "KECON": { "card": { "name": "KECON", "function": "techno-economics", "status": "BUILT", "phase": 3, "provenance": "n/a", "retired_by": "detailed engineering cost model (never public)", "gates": [], "note": "GENERIC open techno-economics (LCOE) on the USER's inputs \u2014 FINANCIAL FIREWALL: no Kronos numbers, ever", "available": true }, "benchmark": { "member": "KECON", "live_worked_example": { "lcoe_per_MWh": 167.64, "capital_component_per_MWh": 134.31, "opex_component_per_MWh": 33.33, "capital_recovery_factor": 0.0806 }, "firewall": "generic community calculator; NO Kronos cost/price/valuation/funding, ever", "note": "founder-approved public, generic-only; inputs above are illustrative placeholders" } }, "KEDGE": { "card": { "name": "KEDGE", "function": "edge-transport", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "SOLPS-ITER / EIRENE edge campaign", "gates": [ "H9" ], "note": "divertor / edge heat-flux -> target-thermal surrogate \u2014 maps divertor heat flux to target surface temperature + material limits (W / CuCrZr) from the H9 exhaust scan. Reduced 0-D thermal model; SOLPS-ITER/EIRENE = fidelity upgrade", "available": true }, "benchmark": { "member": "KEDGE", "live_divertor_thermal": { "source": "h9_target_thermal.csv (H9 exhaust/divertor engineering scan)", "map": "divertor heat flux q [MW/m^2] -> target surface temperature [C]", "r2_fit": 1.0, "n_samples": 77, "max_safe_q_MWm2_CuCrZr": 13.5, "verdict": "Divertor target-thermal surrogate: q->T_surf fit R2=1.000 over 77 points; CuCrZr material limit at q~13.5 MW/m2. Reduced 0-D thermal model \u2014 SOLPS-ITER/EIRENE edge campaign is the fidelity upgrade." }, "caveat": "0-D target-thermal scan, not a full 2-D edge-transport solve" } }, "KEYE": { "card": { "name": "KEYE", "function": "DIAG", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "physical diagnostic suite + validated sensor fusion", "gates": [ "AC-36" ], "note": "diagnostics / virtual-sensor / signal-validation observer \u2014 builds on KFLOW's graph imputation + quantum-sensing; flags faulty channels", "available": true }, "benchmark": { "member": "KEYE", "live_fault_detection": { "detection_rate": 0.767, "false_alarm_rate": 0.0, "n_trials": 300, "method": "3-sigma same-class residual" }, "sourced": { "file": "track8b_quantum_sensing/sensing_to_disruption_gain.csv", "finding": "quantum sensing buys ~0 gain where disruptions live (model-limited)" } } }, "KFLOW": { "card": { "name": "KFLOW", "function": "STATE", "status": "BUILT", "phase": 1, "provenance": "SIM", "retired_by": "trained message-passing GNN (gnn_seed0..4.pt)", "gates": [ "AC-18", "AC-19" ], "note": "twin state-estimation / dropped-sensor imputation on the 76-node diagnostic sensor graph", "available": true }, "benchmark": { "member": "KFLOW", "sourced_gnn": { "file": "track3_gnn/gnn_imputation.csv", "k_failed": 8, "gnn_rmse": 0.0844, "naive_rmse": 0.1721, "gnn_beats_naive": true, "AC18_bar_0.05": "MISSED (kept honest)" }, "live_classmean_baseline_rmse_k8": 1.0215, "live_note": "crude same-class-mean baseline (worse than the track's inverse-distance naive 0.172 and the trained GNN 0.084); shipped predict() uses the same-class imputation" } }, "KFLUX": { "card": { "name": "KFLUX", "function": "neutronics", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "OpenMC (Monte-Carlo neutron transport)", "gates": [], "note": "neutron shielding / coil-fluence surrogate \u2014 fast GP over the toolkit neutronics; OpenMC is the auto-dispatch high-fidelity upgrade", "available": true }, "benchmark": { "member": "KFLUX", "live": { "r2_log_fluence_vs_engine": 1.0, "n_test": 60 }, "note": "surrogate over toolkit shielding/fluence (analytic); OpenMC upgrade = compute route [A]" } }, "KFORGE": { "card": { "name": "KFORGE", "function": "inverse-design", "status": "BUILT", "phase": 3, "provenance": "CGYRO-urep", "retired_by": "full integrated design optimization", "gates": [], "note": "inverse-design capstone \u2014 chains the fleet surrogates (KYRO transport + KORE equilibrium feasibility) to search machine designs; the underlying KYRO transport is CGYRO mu=400 representative-mass (real-mass converged gold deferred), so the operating point is representative, not final", "available": true }, "benchmark": { "member": "KFORGE", "live_inverse_design": { "a_LT": 2.228, "shear": 1.511, "A": 1.139, "kappa": 1.548, "delta": 0.003, "predicted_Q_tot": 0.0, "surrogates_chained": [ "KYRO", "KORE" ], "objective": "min transport (feasible)" }, "note": "differential evolution chained KYRO+KORE to find a low-transport, feasible design \u2014 the capstone that requires the fleet" } }, "KFUEL": { "card": { "name": "KFUEL", "function": "fuel-cycle", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "full fuel-cycle systems code (e.g. MIRC / TRANSAT)", "gates": [], "note": "tritium fuel-cycle inventory \u2014 a reduced systems model (breeding, burn, decay, reserve) giving self-sufficiency + doubling time", "available": true }, "benchmark": { "member": "KFUEL", "live_nominal": { "net_breeding_kg_yr": 1.936, "self_sufficient": true, "doubling_time_yr": 5.17 }, "note": "reduced systems model seeded from tritium physics (12.32 yr half-life); full fuel-cycle code is the roadmap upgrade" } }, "KFUSE": { "card": { "name": "KFUSE", "function": "MULTIFID", "status": "BUILT", "phase": 2, "provenance": "CGYRO-urep", "retired_by": "CGYRO real-mass converged (mu=3672)", "gates": [ "BR-L2-A1e", "BR-L2-A1c-MS" ], "note": "multi-fidelity surrogate: cheap analytic low-fidelity + a residual GP correction from the mu=400 CGYRO points; real-mass gold is the 3rd fidelity", "available": true }, "benchmark": { "member": "KFUSE", "live_multifidelity": { "rmse_low_fidelity_only": 1.481, "rmse_multifidelity": 1.05, "r2_multifidelity": 0.787, "note": "residual GP correction from 16 mu=400 CGYRO points reduces LF error" }, "fidelities": "low = analytic proxy; high = mu=400 CGYRO; 3rd = real-mass gold (deferred)" } }, "KGATE": { "card": { "name": "KGATE", "function": "SAFE", "status": "BUILT", "phase": 1, "provenance": "TWIN", "retired_by": "formal CBF verification + hardware failsafe", "gates": [], "note": "trust-boundary / abstention gate \u2014 a model-free envelope clamp that decides in_domain and fail-closes on bad input", "available": true }, "benchmark": { "member": "KGATE", "steps": 150000, "escapes": 0, "catch_rate": 1.0, "note": "model-free clamp; safety independent of any model" } }, "KGEN": { "card": { "name": "KGEN", "function": "generative", "status": "BUILT", "phase": 3, "provenance": "ANALYTIC", "retired_by": "high-fidelity generative model (diffusion) on real fields", "gates": [], "note": "generative surrogate \u2014 a PCA/latent model that samples plausible equilibrium flux fields; diffusion is the roadmap upgrade", "available": true }, "benchmark": { "member": "KGEN", "live": { "latent_dim": 8, "reconstruction_rel_l2": 4.15e-16, "variance_explained": 1.0, "note": "reconstruction is near-exact BECAUSE the analytic field family is low-rank (3 shape params); the diffusion upgrade earns its keep on a richer real-equilibria corpus. KGEN's job is sampling new plausible fields." } } }, "KHALO": { "card": { "name": "KHALO", "function": "UQ", "status": "BUILT", "phase": 1, "provenance": "SIM", "retired_by": "full ensemble UQ / conformal prediction", "gates": [ "KX-L1-A14", "KX-L1-A5" ], "note": "shared calibrated-uncertainty layer (GP posterior + deep-ensemble) + the canonical reliability report", "available": true }, "benchmark": { "member": "KHALO", "sourced": { "file": "track6_surrogate_uq/uq_calibration_summary.csv", "ece": "0.0327 +/- 0.0136", "coverage_90": "0.888 +/- 0.034", "result": "PASS (mean)" }, "live_gp_on_cgyro": { "ece": 0.0771, "coverage_90": 0.8, "n": 10 } } }, "KHEAT": { "card": { "name": "KHEAT", "function": "heating&CD", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "full RF/NBI ray-tracing (GENRAY/TORAY/NUBEAM)", "gates": [ "H10" ], "note": "heating & current-drive actuator-response surrogate \u2014 fast RandomForest over a 3888-point current-drive design scan; predicts driven current I_cd from the RF/NBI drive parameters + plasma state. Reduced CD model; ray-tracing = fidelity upgrade", "available": true }, "benchmark": { "member": "KHEAT", "live_cd_surrogate": { "source": "d1_cd_search.csv (3888-point current-drive design scan)", "features": [ "gamma_cd", "P_cd", "ne", "R0", "B0", "Ti0", "beta_N" ], "target": "I_cd (driven current, MA)", "r2_vs_scan": 0.949, "n_samples": 3888, "verdict": "Fast surrogate of the current-drive scan: predicts driven current from RF/NBI drive + plasma params, R2=0.949 (3888 configs). Reduced CD model \u2014 GENRAY/TORAY/NUBEAM ray-tracing is the fidelity upgrade." }, "caveat": "engineering CD scan (not full ray-tracing); feeds KAIROS heating control" } }, "KISO": { "card": { "name": "KISO", "function": "isotopes", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "activation-transport + separation model (full spectrum)", "gates": [], "note": "isotope code \u2014 (a) servo surrogate imitating the PI fuel-mix loop, and (b) medical-isotope YIELD from real FENDL-3.2 (n,x) cross-sections convolved with the neutron spectrum (Mo-99/Tc-99m flagship)", "available": true }, "benchmark": { "member": "KISO", "live_servo": { "r2_mean_over_4_species": 0.723, "n_test": 200 }, "sourced": "track5_control/isotope_control_summary.csv (closed-loop 13.6x vs open)", "live_medical_yield": { "n_isotopes": 6, "flagship_Mo-99": { "sigma_thermal_b": 0.1321, "sigma_14MeV_b": 0.00054 }, "ranked_by_thermal_yield": [ "Lu-177", "Sm-153", "Re-186", "Co-60", "Mo-99", "Cu-67" ], "source": "FENDL-3.2 (n,x) cross-sections, 2-group fusion spectrum", "note": "full-spectrum convolution + separation chemistry = the fidelity upgrade" } } }, "KLAW": { "card": { "name": "KLAW", "function": "eqn-discovery", "status": "BUILT", "phase": 3, "provenance": "CGYRO-urep", "retired_by": "first-principles reduced-transport theory", "gates": [], "note": "equation discovery \u2014 sparse regression finds a compact closure for log10(Q_tot) over the CGYRO map (mu=400)", "available": true }, "benchmark": { "member": "KLAW", "live": { "r2_fit": 0.903, "n_terms_selected": 7, "discovered_terms": [ [ "a_LT", -10.301 ], [ "s", -0.718 ], [ "s^2", -4.205 ], [ "a_LT*s", 0.287 ], [ "relu(a_LT-2.1)", 13.616 ], [ "relu(a_LT-2.1)^2", -2.873 ], [ "a_LT*s^2", 4.226 ] ] }, "note": "compact closure discovered from the 16/16 CGYRO map" } }, "KLINQ": { "card": { "name": "KLINQ", "function": "QLINSOLVE", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "KX-L3" ], "note": "REAL quantum linear solver \u2014 a variational quantum linear solver (VQLS) prepares the solution of a small reduced-MHD linear system with a real quantum circuit (sim now, hardware pluggable), plus an honest fault-tolerant HHL resource estimate. No advantage at real scale; quantum's role in fusion is post-~2036", "available": true }, "benchmark": { "member": "KLINQ", "live_quantum_linear_solver": { "problem": "solve A x = b for a 4x4 reduced-MHD Laplacian (SPD) with a real quantum circuit", "method": "variational quantum linear solver (VQLS), global overlap cost, Powell optimization", "framework": "PennyLane (sim now; Hadamard-test cost on real hardware, pluggable)", "N": 4, "n_qubits": 2, "cost_final": 0.0, "solution_fidelity_vs_classical": 1.0, "residual_rel": 0.0, "x_quantum": [ 0.8, 0.6, 0.4, 0.2 ], "x_classical": [ 0.8, 0.6, 0.4, 0.2 ], "ft_hhl_resource_estimate": { "assumed_system": "N~1e+06 sparse SPD (reduced-MHD grid), kappa~1e+03", "logical_qubits_needed": 31, "physical_qubits_needed": "~4e+04", "surface_code_phys_per_logical": 1250, "roadmap_year_reach_logical": 2031, "hardware_today": "~1e2-1e3 physical qubits, no error-corrected logical qubits", "caveats": [ "HHL needs fault tolerance + sparse, well-conditioned A + efficient state prep, and returns |x> (aggregate readout), not the full vector", "no fusion HHL advantage this decade \u2014 meaningful role post-~2036" ] }, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL variational quantum linear solver recovers the 4x4 reduced-MHD solve at solution fidelity 1.0 vs classical (rel-residual 0.0) \u2014 a runnable quantum linear solver TODAY. The fault-tolerant HHL route for a fusion-scale (N~1e6) solve needs ~31 logical -> ~4e+04 physical qubits (roadmap ~2031). HONEST: no advantage at real scale; quantum's meaningful role in fusion is post-~2036. Runs on hardware with KODEX_QC_BACKEND=ibm." }, "caveats": [ "no quantum advantage \u2014 quantum's role in fusion is post-~2036", "VQLS residual is read from the simulator here; on hardware it needs Hadamard tests and its cost landscape can have barren plateaus at scale", "the 4x4 system is a toy; classical solves it instantly \u2014 the point is a real, honest, hardware-ready quantum pipeline, not a speedup" ] } }, "KMAT": { "card": { "name": "KMAT", "function": "MATERIALS", "status": "BUILT", "phase": 1, "provenance": "SIM", "retired_by": "DFT (VASP / Quantum ESPRESSO)", "gates": [ "KX-L1-A4", "BR-L2-A8" ], "note": "ML+DFT alloy / HEA screen (CHGNet) for structural & functional materials; screen BUILT, dpa/lifetime roadmap", "available": true }, "benchmark": { "member": "KMAT", "n_candidates_screened": 8, "top": { "name": "BLK_Al50Ti33Zr10Cr7", "note": "blanket structural IP#12 (A34)", "comp": { "Al": 8, "Ti": 5, "Zr": 2, "Cr": 1 }, "a0_vegard": 3.2653, "E_per_atom": -6.3282, "Eform_proxy": -0.393, "V_per_atom": 16.977 }, "sourced": "chgnet_screen_results.json (DFT-validated)", "note": "alloy screen BUILT; dpa/lifetime roadmap inside KMAT" } }, "KMIND": { "card": { "name": "KMIND", "function": "FOUNDATION", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "a device-scale multi-task foundation model on real multi-diagnostic data", "gates": [ "BR-L2-A1e", "AC-16", "AC-18", "AC-20" ], "note": "whole-device foundation surrogate \u2014 one shared-trunk multi-task net across transport / equilibrium / state / disruption, trained jointly; reports shared-representation transfer honestly (incl. negative transfer)", "available": true }, "benchmark": { "member": "KMIND", "live_foundation": { "architecture": "per-domain adapter (->32) + shared trunk (2x128, dropout 0.1) + per-domain head; 4 domains, joint training 300 steps", "domains": [ "transport", "equil", "state", "disrupt" ], "params": 66958, "transfer_vs_single_task": { "transport": { "metric": "r2_log_Qtot", "multitask": 0.577, "single_task_baseline": 0.571, "delta": 0.006, "transfer": "data_starved", "n_train": 12, "n_test": 4 }, "equil": { "metric": "rel_l2_field", "multitask": 0.009, "single_task_baseline": 0.0117, "delta": -0.0027, "transfer": "positive", "n_train": 600, "n_test": 200 }, "state": { "metric": "norm_rmse", "multitask": 0.0239, "single_task_baseline": 0.0224, "delta": 0.0015, "transfer": "neutral", "n_train": 1500, "n_test": 500 }, "disrupt": { "metric": "roc_auc", "multitask": 0.99, "single_task_baseline": 0.993, "delta": -0.003, "transfer": "neutral", "n_train": 443, "n_test": 148 } }, "positive_transfer_domains": [ "equil" ], "negative_transfer_domains": [], "neutral_transfer_domains": [ "state", "disrupt" ], "data_starved_domains": [ "transport" ], "mc_dropout_predict_ms": 4.05, "backend": "CPU, torch, MC-dropout UQ", "verdict": "One shared trunk across 4 fusion domains, benchmarked head-by-head against a MATCHED single-task baseline on the same split. On the well-populated domains the shared representation is positive ['equil'], negative none, neutral ['state', 'disrupt'] \u2014 no negative transfer. ['transport'] is data-starved (16 pts) and not judged held-out. Trained on real on-disk data (CGYRO map / analytic equilibria / twin sensor snapshots / MAST shots) \u2014 an honest multi-task result, not a blanket win." }, "caveats": [ "transport has only ~16 points, so its head is data-starved and high-variance (a real limit, reported not hidden)", "uncertainty is an MC-dropout epistemic proxy, not a calibrated conformal interval", "equilibrium targets are the analytic Solov'ev family (as in KORE); state targets are the analytic-twin sensor snapshots (as in KFLOW)" ] } }, "KMIT": { "card": { "name": "KMIT", "function": "QMITIGATION", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "KX-L3" ], "note": "REAL quantum error mitigation \u2014 zero-noise extrapolation (ZNE, unitary folding) + readout-error mitigation on a real fusion quantum circuit (the KQUBIT H2 VQE state). Mitigation is the genuine NISQ tool TODAY; it recovers signal from noise, not a speedup. Quantum's role in fusion is post-~2036", "available": true }, "benchmark": { "member": "KMIT", "live_error_mitigation": { "problem": "mitigate a noisy H2 VQE expectation (the real KQUBIT circuit)", "framework": "PennyLane default.mixed; ZNE via global unitary folding + linear extrapolation", "zne": { "exact_energy_Ha": -1.857275, "ideal_noiseless_Ha": -1.857275, "noisy_Ha": -1.812895, "zne_mitigated_Ha": -1.852246, "noise_scales_lambda": [ 1.0, 3.0, 5.0 ], "energies_vs_lambda": [ -1.812895, -1.725694, -1.648692 ], "error_noisy_mHa": 44.38, "error_zne_mHa": 5.029, "error_reduction_frac": 0.887, "depolarizing_p": 0.04, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" } }, "readout_mitigation": { "readout_bitflip_p": 0.08, "tv_distance_noisy": 0.1472, "tv_distance_mitigated": 0.0, "tv_reduction_frac": 1.0, "method": "inverse confusion-matrix (linear) readout correction" }, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL error mitigation on a fusion quantum circuit: ZNE cuts the noisy-energy error 44.38 -> 5.029 mHa (89% of the error removed) and inverse-confusion readout correction cuts the measurement TV distance 0.1472 -> 0.0 (100%). Mitigation is the REAL NISQ tool today \u2014 it recovers signal from noise. HONEST: it is NOT a speedup; quantum's meaningful role in fusion is post-~2036, and mitigation cost grows with noise. Runs on real hardware with KODEX_QC_BACKEND=ibm." }, "caveats": [ "no quantum advantage \u2014 quantum's role in fusion is post-~2036", "ZNE assumes a smooth noise->observable relation; it extrapolates, it does not eliminate noise, and its overhead grows as noise grows", "readout mitigation uses a known confusion matrix; on hardware you must calibrate it" ] } }, "KOIL": { "card": { "name": "KOIL", "function": "MAGNET", "status": "BUILT", "phase": 1, "provenance": "SIM", "retired_by": "full FE electromechanical solve", "gates": [ "BR-MT1", "BR-MT3" ], "note": "magnet-twin stress-field surrogate + quench-precursor early-warning; REBCO per-turn Wilson-form hoop stress", "available": true }, "benchmark": { "member": "KOIL", "live_strain_surrogate": { "rel_l2": 0.0038, "r2": 1.0, "n_turns": 82 }, "sourced_mt1": { "file": "track_MT1_magnet_twin/ac_mt1_verdict.csv", "headline": "surrogate 0.24% rel-L2 @ 0.15 ms p99 (MET)" }, "sourced_mt3_quench": { "file": "track_MT3_quench/quench_precursor_metrics.csv", "headline": "quench precursor 47.2 ms lead, AUC 0.9998, FAR 2.4%" } } }, "KORE": { "card": { "name": "KORE", "function": "EQUIL", "status": "BUILT", "phase": 1, "provenance": "ANALYTIC", "retired_by": "classical Grad-Shafranov solver", "gates": [ "AC-16", "AC-L1" ], "note": "fast learned MHD-equilibrium accelerator (neural surrogate, 3-seed ensemble); Grad-Shafranov, not turbulence", "available": true }, "benchmark": { "member": "KORE", "live_learned_surrogate": { "rel_l2_vs_analytic": 0.0035, "ensemble_cov90": 0.778, "infer_ms": 0.318, "grid": "16x16", "n_heldout": 120 }, "sourced": { "file": "track_L1_neural_operator/operator_vs_pinn.csv", "headline": "track FNO best 2.5% rel-L2 vs 1% bar (MISSED); ~1 s classical solver -> sub-ms surrogate" } } }, "KPATH": { "card": { "name": "KPATH", "function": "operational", "status": "BUILT", "phase": 2, "provenance": "TWIN", "retired_by": "operational scenario optimizer (device-validated)", "gates": [], "note": "operational controller surrogate \u2014 (state, setpoint) -> command; imitation of the MPC over the closed-loop control traces", "available": true }, "benchmark": { "member": "KPATH", "live": { "r2_mean_over_6_axes": 0.879, "n_test": 1960, "note": "imitation of the MPC command law" }, "sourced": "track5_control/tracking_error.csv (MPC RMS <5% on all 6)" } }, "KPILOT": { "card": { "name": "KPILOT", "function": "agentic-AI", "status": "BUILT", "phase": 3, "provenance": "n/a", "retired_by": "full LLM agent runtime over the fleet", "gates": [], "note": "fleet orchestration layer \u2014 routes a plain-language query to the right KODEX code and runs it; the LLM reasoning layer is the roadmap upgrade", "available": true }, "benchmark": { "member": "KPILOT", "live_routing": { "what's the heat flux at gradient 3.5 shear 1.6?": "KYRO", "is this command inside the safe envelope?": "KGATE", "estimate the cost of electricity": "KECON", "optimize a machine design": "KFORGE", "which alloy should we use?": "KMAT" }, "note": "keyword tool-router over the fleet; a full LLM agent is the roadmap upgrade" } }, "KQERN": { "card": { "name": "KQERN", "function": "QKERNEL", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "KX-L3" ], "note": "REAL quantum-kernel classifier \u2014 embeds real MAST disruption features into a quantum feature map and classifies on the fidelity kernel (PennyLane); runs on a simulator now, real hardware pluggable. Honest: ties the classical kernel \u2014 a validated no-advantage result, but a real, runnable quantum-ML pipeline; role in fusion post-~2036", "available": true }, "benchmark": { "member": "KQERN", "live_quantum_kernel": { "problem": "MAST disruption classification on a real quantum fidelity kernel", "framework": "PennyLane AngleEmbedding kernel + precomputed-kernel SVM", "quantum_kernel_auc": 0.919, "classical_rbf_auc": 0.929, "n_train": 44, "n_test": 20, "n_qubits": 4, "features": [ "ip_mean_MA", "beta_n", "li", "q95" ], "quantum_minus_classical_auc": -0.01, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL quantum kernel classifies MAST disruptions at AUC 0.919 vs classical RBF 0.929 (Delta -0.010) \u2014 no advantage: a validated null, but a REAL runnable quantum-ML pipeline on real fusion data. Runs on hardware with KODEX_QC_BACKEND=ibm.", "caveats": [ "labels are the heuristic Ip-quench disruption labels (from KWARD)", "quantum kernel ties classical here \u2014 no advantage; the value is a real, hardware-ready quantum-ML tool, honest that advantage is ~8-10 yr out" ] }, "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A6_quantum_kernel_MAST)", "note": "independent Track-1 run also found quantum-kernel AUC ~= classical (null)" } } }, "KQOPT": { "card": { "name": "KQOPT", "function": "QOPT", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "KX-L3" ], "note": "REAL QAOA quantum optimizer \u2014 solves a combinatorial design QUBO on an actual quantum circuit (PennyLane); runs on a simulator now, real hardware pluggable, and you can plug in your own QUBO. Honest: standard ~0.7-1.0 approx ratio, no speedup at this size (advantage post-~2036)", "available": true }, "benchmark": { "member": "KQOPT", "live_qaoa": { "problem": "6-node design QUBO (MaxCut-style; plug in your own Q matrix)", "framework": "PennyLane QAOA (p=2); runs on simulator now, real hardware pluggable", "qaoa_cut": 6, "optimal_cut": 6, "approx_ratio": 1.0, "p": 2, "n_qubits": 6, "solution_bitstring": [ 0, 1, 0, 1, 0, 1 ], "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL QAOA reaches 100% of the brute-force optimum (cut 6/6, p=2, 6 qubits) on the default backend \u2014 a working quantum optimizer, runnable on hardware with KODEX_QC_BACKEND=ibm. HONEST: no speedup vs classical at this size; advantage is ~8-10 yr out." }, "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A4_QAOA)", "note": "independent Track-1 p=1 QAOA reached ~66% on an 8-node QUBO (consistent)" } } }, "KQROSS": { "card": { "name": "KQROSS", "function": "QRE", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "AC-43", "BR-SX-08" ], "note": "REAL fault-tolerant resource estimator \u2014 computes the classical<->quantum crossover N, the surface-code physical-qubit overhead, and the logical-qubit roadmap year for a fusion electronic-structure kernel (order-of-magnitude, literature-scaled). Verdict: no FT advantage this decade \u2014 the machine does not exist yet; meaningful role post-~2036", "available": true }, "benchmark": { "member": "KQROSS", "live_resource_estimate": { "method": "surface-code overhead (d=25) + qubitization T-counts + classical exact-CI, order-of-magnitude literature-scaled", "crossover_N_spin_orbitals": 50, "logical_qubits_needed": 50, "physical_qubits_needed": "~6e+04", "surface_code_phys_per_logical": 1250, "quantum_runtime_hours_at_crossover": 0.03, "roadmap_year_reach_logical": 2032, "hardware_today": "~1e2-1e3 physical qubits, no error-corrected logical qubits", "verdict": "REAL FT resource estimate: classical<->quantum crossover at N~50 spin-orbitals needs 50 logical -> ~6e+04 physical qubits and ~0.03 h/run. Today's hardware = ~1e2-1e3 physical qubits, no error-corrected logical qubits; the roadmap reaches that logical count ~2032. NO fault-tolerant quantum advantage for fusion this decade \u2014 a validated negative result." }, "caveat": "MANDATORY: no quantum advantage this decade (order-of-magnitude estimate)", "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A1/A3/A9)", "note": "independent Track-1: crossover N~40, ~1e5-1e6 phys qubits, mid/late-2030s" } } }, "KQUBIT": { "card": { "name": "KQUBIT", "function": "QML", "status": "BUILT", "phase": 1, "provenance": "SIM", "retired_by": "fault-tolerant quantum hardware (not available this decade)", "gates": [ "AC-44", "KX-L3-A4" ], "note": "REAL variational quantum eigensolver (VQE) for a molecular Hamiltonian \u2014 a runnable quantum program (PennyLane): executes on a simulator now and on real quantum hardware when you plug in a backend. Honest: no quantum advantage yet (~8-10 yr out); the tooling + testing are real TODAY \u2014 quantum's role in fusion is post-~2036", "available": true }, "benchmark": { "member": "KQUBIT", "live_vqe": { "problem": "H2 molecular Hamiltonian (2-qubit parity-reduced; standard coeffs)", "framework": "PennyLane (runnable on simulator now; real hardware pluggable)", "vqe_energy_Ha": -1.857275, "exact_energy_Ha": -1.857275, "recovery_mHa": 0.0002, "n_qubits": 2, "steps": 120, "reaches_chemical_accuracy": true, "nisq_noise_sweep_mHa_error": { "0.0": 0.0, "0.001": 1.112, "0.005": 5.557, "0.01": 11.11, "0.02": 22.211, "0.05": 55.449 }, "noise_note": "depolarizing-noise sweep (mHa error vs per-qubit p): NISQ noise breaks the 1.6 mHa chemical accuracy fast \u2014 this is WHY there is no advantage yet", "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL VQE recovers the H2 ground state to 0.0002 mHa on the default backend (within 1.6 mHa chemical accuracy). Runs on real quantum hardware when you set KODEX_QC_BACKEND=ibm. HONEST: no quantum advantage this decade \u2014 the value now is a real, testable quantum pipeline, not a speedup." }, "sourced": { "file": "track8_vqe_poc/vqe_convergence.csv", "note": "prior noisy-VQE sweep: chemical accuracy breaks under NISQ noise (quantifies the no-advantage-this-decade caveat)" }, "caveat": "MANDATORY: no quantum advantage this decade; hardware value is ~8-10 yr out" } }, "KRAD": { "card": { "name": "KRAD", "function": "radiation-control", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "impurity transport (SOLPS + impurity) + radiation control", "gates": [ "H9" ], "note": "impurity-seeding radiation-control evaluator \u2014 maps a seeded impurity + radiated-power fraction to core Zeff penalty and P_rad from the H9 seeding scan. Small scan; full impurity-transport (SOLPS + impurity) = fidelity upgrade", "available": true }, "benchmark": { "member": "KRAD", "live_impurity_seeding": { "source": "h9_seeding.csv (H9 impurity-seeding scan)", "n_impurities": 3, "impurities": [ "Ar", "N", "Ne" ], "radiated_fraction": 0.58, "least_core_dilution_impurity": "Ar", "verdict": "Impurity-seeding radiation evaluator over 3 impurities at f_rad=0.58: 'Ar' gives the least core Zeff penalty (dZeff_hi=0.1102). Small scan \u2014 full impurity-transport (SOLPS) is the fidelity upgrade." }, "caveat": "small seeding scan (few impurities); reduced 0-D radiation model" } }, "KSCOUT": { "card": { "name": "KSCOUT", "function": "MF-CAMPAIGN", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "the full multi-fidelity CGYRO campaign (twin + mu=400 + real-mass gold)", "gates": [ "BR-L2-A1e" ], "note": "multi-fidelity Bayesian-optimization campaign manager \u2014 extends KSEEK: chooses which operating point AND which fidelity (reduced twin / mu=400 CGYRO / real-mass gold) to run next, greedily maximizing truth-weighted information per GPU-hour under a budget", "available": true }, "benchmark": { "member": "KSCOUT", "live_mf_campaign": { "source": "KYRO GP over the completed 16-pt CGYRO A1e map", "budget_gpu_h": 15.0, "target_hotspots": 16, "policy": "twin-triage every hotspot, escalate most-uncertain to mu=400, reserve gold", "fidelities": { "twin": { "gpu_h": 0.0, "rho": 0.55, "desc": "reduced analytic twin (near-free triage)" }, "cgyro_mu400": { "gpu_h": 2.89, "rho": 0.9, "desc": "CGYRO representative mu=400 (measured GPU-h)" }, "gold_mu3672": { "gpu_h": 28.9, "rho": 1.0, "desc": "CGYRO real-mass gold (est. ~10x mu=400; not yet run)" } }, "multi_fidelity_plan": [ { "a_LT": 3.25, "shear": 1.4, "fidelity": "cgyro_mu400", "gpu_h": 2.99, "gp_std": 0.5041, "truth_confidence_rho": 0.9 }, { "a_LT": 2.25, "shear": 1.4, "fidelity": "cgyro_mu400", "gpu_h": 2.99, "gp_std": 0.5041, "truth_confidence_rho": 0.9 }, { "a_LT": 3.25, "shear": 0.6, "fidelity": "cgyro_mu400", "gpu_h": 2.99, "gp_std": 0.5041, "truth_confidence_rho": 0.9 }, { "a_LT": 2.25, "shear": 0.6, "fidelity": "cgyro_mu400", "gpu_h": 2.99, "gp_std": 0.5041, "truth_confidence_rho": 0.9 }, { "a_LT": 3.25, "shear": 1.0, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.4831, "truth_confidence_rho": 0.55 }, { "a_LT": 2.25, "shear": 1.0, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.4831, "truth_confidence_rho": 0.55 }, { "a_LT": 2.75, "shear": 0.6, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.4831, "truth_confidence_rho": 0.55 }, { "a_LT": 2.75, "shear": 1.4, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.4831, "truth_confidence_rho": 0.55 }, { "a_LT": 2.75, "shear": 1.0, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.4623, "truth_confidence_rho": 0.55 }, { "a_LT": 2.25, "shear": 0.4, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 2.25, "shear": 1.6, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 3.25, "shear": 1.6, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 3.25, "shear": 0.4, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 2.0, "shear": 1.4, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 3.5, "shear": 1.4, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 }, { "a_LT": 2.0, "shear": 0.6, "fidelity": "twin", "gpu_h": 0.1, "gp_std": 0.3838, "truth_confidence_rho": 0.55 } ], "mf_runs": 16, "mf_gpu_h_used": 13.56, "mf_runs_by_fidelity": { "twin": 12, "cgyro_mu400": 4, "gold_mu3672": 0 }, "mf_mean_confidence_rho": 0.638, "baseline_all_mu400": { "n_runs": 5, "gpu_h_used": 14.95, "mean_confidence_rho": 0.281, "unvisited_hotspots": 11 }, "mf_confidence_gain_x_vs_all_mu400": 2.27, "verdict": "Under a tight 15.0 GPU-h budget across 16 uncertain operating points, the multi-fidelity policy triages ALL 16 with cheap twin runs and escalates 4 to mu=400 (0 to real-mass gold), reaching mean truth-confidence rho 0.638 \u2014 vs 0.281 for a naive all-mu=400 plan that exhausts the budget after 5 points and leaves 11 hotspots unexamined (2.27x). A real cost-aware campaign manager: look everywhere cheaply, spend the expensive fidelity where KYRO is least sure." }, "caveats": [ "the per-fidelity rho (correlation-with-truth) values are ASSUMPTIONS \u2014 the real-mass gold has not been run \u2014 so this is a planning heuristic, not a measured speedup; the advantage holds only while budget < hotspots x mu=400 cost", "GP std comes from only 16 points (directional, like KSEEK)", "GPU-hours only; no compute-cost figures (product-econ rule)" ] } }, "KSEEK": { "card": { "name": "KSEEK", "function": "ACTIVE", "status": "BUILT", "phase": 3, "provenance": "SIM", "retired_by": "the full CGYRO parameter scan (once every point is simulated)", "gates": [ "BR-L2-A1e" ], "note": "active-learning acquisition \u2014 proposes the NEXT most-informative CGYRO run from KYRO's GP posterior (max-variance / uncertainty sampling), so expensive GPU-hours go where the surrogate is least sure. A real experimental-design tool", "available": true }, "benchmark": { "member": "KSEEK", "live_active_learning": { "source": "KYRO GP over the completed 16-pt CGYRO A1e map", "acquisition": "max GP posterior std (uncertainty sampling), min-separation filtered", "next_runs": [ { "a_LT": 2.225, "shear": 0.58, "gp_std": 0.5046 }, { "a_LT": 3.275, "shear": 0.58, "gp_std": 0.5046 }, { "a_LT": 3.275, "shear": 1.42, "gp_std": 0.5046 } ], "loo_std_vs_error_corr": -0.283, "cgyro_gpu_h_per_point": 2.89, "verdict": "Proposes the next CGYRO run at a/L_T=2.225, shear=0.58 (highest GP uncertainty). Leave-one-out: GP posterior-std vs actual error correlation = -0.283 \u2014 weak on this small map. A real experimental-design tool: spend ~2.9 GPU-h/point where it matters." }, "caveat": "16 training points is small \u2014 acquisition is directional guidance, not a guarantee" } }, "KSENSE": { "card": { "name": "KSENSE", "function": "QSENSE", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "deployed physical diagnostic hardware", "gates": [ "HX-29" ], "note": "REAL quantum-metrology evaluation (PennyLane mixed-state) \u2014 GHZ interferometry: ideal gives Heisenberg (gain ~ N) scaling, but realistic dephasing (NV/SQUID/SERF reality) collapses it back to the standard quantum limit (~sqrt(N)). Honest null where fusion disruptions live; quantum's role in fusion is post-~2036", "available": true }, "benchmark": { "member": "KSENSE", "live_quantum_metrology": { "method": "PennyLane mixed-state GHZ interferometry; Heisenberg vs SQL vs dephasing", "dephasing_per_qubit": 0.2, "scaling": [ { "N": 2, "visibility_dephased": 0.8, "GHZ_ideal_gain": 2.0, "GHZ_dephased_gain": 1.6, "SQL_gain": 1.41 }, { "N": 3, "visibility_dephased": 0.716, "GHZ_ideal_gain": 3.0, "GHZ_dephased_gain": 2.15, "SQL_gain": 1.73 }, { "N": 4, "visibility_dephased": 0.64, "GHZ_ideal_gain": 4.0, "GHZ_dephased_gain": 2.56, "SQL_gain": 2.0 }, { "N": 5, "visibility_dephased": 0.572, "GHZ_ideal_gain": 5.0, "GHZ_dephased_gain": 2.86, "SQL_gain": 2.24 }, { "N": 6, "visibility_dephased": 0.512, "GHZ_ideal_gain": 6.0, "GHZ_dephased_gain": 3.07, "SQL_gain": 2.45 }, { "N": 7, "visibility_dephased": 0.458, "GHZ_ideal_gain": 7.0, "GHZ_dephased_gain": 3.21, "SQL_gain": 2.65 }, { "N": 8, "visibility_dephased": 0.41, "GHZ_ideal_gain": 8.0, "GHZ_dephased_gain": 3.28, "SQL_gain": 2.83 } ], "gain_growth_N2_to_N8": { "GHZ_ideal": 4.0, "GHZ_dephased": 2.05, "SQL": 2.01 }, "analytic_turnover_N": 8, "backend": { "active_backend": "default", "ran_on_real_hardware": false, "how_to_use_real_qc": "set KODEX_QC_BACKEND=ibm and KODEX_QC_TOKEN= to run this exact circuit on real quantum hardware", "honest_timeline": "fault-tolerant quantum ADVANTAGE for fusion kernels is ~8-10 yr out \u2014 a meaningful role in fusion only after ~2036; this tooling makes the TESTING real and runnable TODAY, same code path" }, "verdict": "REAL quantum-metrology computation: over N=2->8 the ideal GHZ gain grows 4.0x (Heisenberg ~ N), but with per-qubit dephasing (p=0.2) the dephased GHZ grows only 2.05x \u2014 essentially the SQL rate (2.01x, ~sqrt(N)). Dephasing ERASES the Heisenberg *scaling* to a bounded constant (gain turns over near N~9). HONEST NULL: no quantum-sensing advantage for fusion disruptions this decade \u2014 but a real, runnable metrology tool." }, "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A7_metrology)", "note": "independent Track-1: correlated dephasing erases GHZ Heisenberg back to SQL" } } }, "KTENSOR": { "card": { "name": "KTENSOR", "function": "TN", "status": "BUILT", "phase": 2, "provenance": "SIM", "retired_by": "exact many-body / quantum simulation", "gates": [ "KX-L3" ], "note": "tensor-network / low-rank ROM compression of the real CGYRO A1e flux database (classical MPS-style SVD; a many-body method and bridge to quantum kernels \u2014 NO quantum-advantage claim; quantum's role in fusion is post-~2036)", "available": true }, "benchmark": { "member": "KTENSOR", "live_low_rank_rom": { "source": "real CGYRO A1e flux database (data.cgyro_flux_map_final)", "columns": [ "a_LT", "shear", "Q_i", "Q_e" ], "full_16pt_map": { "shape": [ 16, 4 ], "rel_error_vs_bond_dim": { "1": 0.5903, "2": 0.3009, "3": 0.1214, "4": 0.0 }, "cumulative_variance": { "1": 0.6515, "2": 0.9094, "3": 0.9853, "4": 1.0 }, "effective_rank": 2.93 }, "turbulent_branch": { "shape": [ 12, 4 ], "rel_error_vs_bond_dim": { "1": 0.4964, "2": 0.2879, "3": 0.1304, "4": 0.0 }, "cumulative_variance": { "1": 0.7535, "2": 0.9171, "3": 0.983, "4": 1.0 }, "effective_rank": 2.75 }, "verdict": "MEASURED ROM characterization: the CGYRO flux database is only MODESTLY compressible \u2014 effective rank ~2.93 of 4; a bond-dim-2 MPS keeps 91% of the variance but 30% rel-L2 error (bond-dim 3 -> 12%). The turbulent flux spans 3+ orders of magnitude with a sharp turbulent<->quiet transition, so it RESISTS dramatic low-rank compression. An honest counter to the naive 'flux is trivially low-rank' expectation. Classical SVD/MPS; NO quantum-advantage claim.", "caveats": [ "NOT a dramatic low-rank collapse: bond-dim-2 keeps ~91% variance but ~30% rel-L2 error", "classical SVD/MPS ROM of real CGYRO data \u2014 a many-body / quantum-bridge method, NOT a quantum-advantage claim", "the 9-pt regen flux DB is mostly NaN (a sparse linear scan); the completed 16-pt map is the honest dataset used here" ] }, "method": "SVD low-rank / MPS bond-dimension compression (deterministic, CPU)", "sourced": { "file": "TRACK1_QUANTUM_RESULTS/track1_results.json (A5_MPS_flux)", "note": "the Track-1 'rank-2 ~1%' figure was on the sparse 9x4 regen table; on the complete map the flux is not strongly low-rank (this card)" } } }, "KWARD": { "card": { "name": "KWARD", "function": "DISRUPT", "status": "BUILT", "phase": 1, "provenance": "REAL-ANCHOR", "retired_by": "physicist-verified disruption labels + full precursor diagnostics", "gates": [ "AC-20", "AC-21" ], "note": "disruption early-warning \u2014 real-device (592 MAST shots), calibrated ensemble + per-shot OOD gate; advisory, downstream of the KGATE clamp", "available": true }, "benchmark": { "member": "KWARD", "live_real_device": { "source": "592 real MAST shots (FAIR-MAST), fixed 50 ms window", "auc": 0.98, "auc_precursor_only_no_Ip_variability": 0.984, "ece": 0.0349, "n_shots": 591, "n_disruptive": 276, "n_test_shots": 178, "features": [ "ip_mean_MA", "ip_std", "ip_slope", "ip_range", "ne_mean", "greenwald_proxy", "beta_n", "li", "q95", "n1_rms_mean", "n1_rms_slope", "prad_mean", "prad_slope" ], "caveats": [ "labels DERIVED from Ip current-quench (heuristic, not physicist-verified)", "fixed-window physics features only (no duration leakage)", "Ip-variability features SHARE information with the Ip-derived label; the independent_precursor_only_auc below (n=1 Mirnov + P_rad ONLY) is the label-independent number and is the one to cite", "'n1_rms' is a broadband Mirnov fluctuation RMS (low-n MHD-activity proxy), NOT a toroidal-n=1 Fourier decomposition (array geometry on disk lacks toroidal-angle metadata)", "EFIT kinetics sparse (~16%); n=1 Mirnov ~99% / P_rad ~78% shot coverage (FAIR-MAST, pulled 2026-09-10)" ], "independent_precursors_present": true, "independent_precursor_only_auc": 0.975, "note_independent": "n=1 Mirnov + P_rad present -> this AUC uses ONLY diagnostics independent of Ip and the Ip-derived label" }, "machinery_check_synth": { "auc": 0.916 }, "sourced_twin": { "file": "track4_disruption/disruption_metrics.csv", "note": "prior twin-synthetic result AUC 0.990 (superseded by real-device above)" } } }, "KYRO": { "card": { "name": "KYRO", "function": "TRANSPORT", "status": "BUILT", "phase": 1, "provenance": "CGYRO-urep", "retired_by": "CGYRO (nonlinear gyrokinetic)", "gates": [ "BR-L2-A12", "BR-L2-A1e", "BR-L2-A1c" ], "note": "CGYRO turbulence-transport surrogate over the complete 16/16 A1e map (total heat flux Q_tot + turbulent/quiet); mu=400 rep, real-mass gold deferred", "available": true }, "benchmark": { "member": "KYRO", "accuracy": { "r2_log_Qtot": 0.858, "rmse_log_Qtot": 0.857, "coverage_90": 0.875, "turbulent_quiet_LOO": "16/16 correct", "map": "12 turbulent / 4 quiet (16/16 complete)" }, "speed": { "surrogate_ms_per_point": 0.257, "cgyro_gpu_h_per_point_measured": 2.89, "speedup_x_vs_cgyro": "4.1e+07", "speedup_note": "ms inference vs GPU-hours for the CONVERGED flux value", "fidelity": "representative mu=400; real-mass gold deferred" }, "provenance": "COMPLETE 16/16 CGYRO A1e map (mu=400); operating point subcritical" } } }