Quantum-Inspired Thermal Equilibrium: Integration of Collective Dynamics into Real-Time Stabilization of Magnetically Confined Fusion Plasmas — Extended Edition with Adversarial Stress Benchmark on TORAX 1.4

2026-06-07 — Adversarial control-theory stress benchmark of the QITE multi-agent plasma controller on the native Google DeepMind TORAX 1.4 step-level API (Citrin et al., 2024) under the deliberately exaggerated IterHybrid-XHARD disturbance cascade. The benchmark imposes seven simultaneously active stochastic disturbance processes on the ITER Hybrid scenario at 12 MA / 5.3 T (Polevoi 2005, van Mulders 2021), each calibrated above its real-ITER analogue by between one and two orders of magnitude: ELM crashes every 5 s with a 15 % radiation spike, NBI dropouts at 20 % per control tick, ECRH dropouts at 15 % per tick, Z_eff random walk with σ = 0.15 s⁻¹, gas-puff flow noise five times nominal, actuator command noise σ = 5 %, actuator slew rates halved relative to the ITER emergency-mode envelope (Snipes 2017 §5 Tab 3). Over 300 reproducible episodes (3 policies × 100 actuator-noise seeds), the deterministic five-agent QITE controller — implementing the ITER PCS Tier-1 hierarchy (Ip, NBI, ECRH, gas puff) plus the Tier-2 Disruption Mitigation System via the Mavrin impurity-radiation proxy (Lehnen 2015 §4, Hollmann 2015) — delivers 88 / 100 disruption-free episodes at the physically-correct Hybrid operating point Q_fus = 7.94 ± 1.26 in H-mode confinement (H98 = 2.13 ± 0.40), absorbing 90.5 ± 20.7 stacked adversarial events per episode. The open-loop reference 'survives' 100 / 100 only by saturating in L-mode at Q = 3.60 ± 0.00 (H98 = 0.80 ± 0.00); the uniform-random baseline disrupts in 100 / 100 attempts at Q = 23.32 ± 13.55. A Welch two-sample t-test on Q_mean of survivors yields p = 1.06 × 10⁻⁹⁸ against the open-loop reference, and Fisher exact on survival counts yields p < 10⁻³⁰ against the random baseline — the QITE distribution is statistically separated from every baseline at p < 10⁻¹³. Operating-point trajectories sit with substantial safety margin both below the Troyon no-wall β_N limit (β_N max = 1.41 ± 0.09 vs 3.0 hard limit) and above the sawtooth + 2/1 NTM lock threshold on q_min (La Haye 2006); the architectural advantage is shown to come from the Tier-1 + Tier-2 actuator hierarchy and the shared emergent collective field, not from threshold tuning specific to the adversarial scenario — the controller configuration is the off-the-shelf five-agent QITE emergency-mode setup with the cited per-actuator lambda mapping, applied without modification. The complete adversarial-benchmark deposit — 300 per-tick CSV logs of all episodes, configuration and run metadata, aggregate statistics, headline statistical tests, nine reproduced figures, and full disturbance-cascade and scenario specification — is published openly under CC-BY-4.0 / CC0; only the QITE Core SDK itself remains proprietary, and no engine internals are required to reproduce any reported number from the included CSV logs. Full technical specification of the 9-page benchmark paper.

External validation of the QITE multi-agent plasma controller against the third-party Google DeepMind TORAX simulator (Citrin et al., 2024) via the gymtorax 1.0.0 reinforcement-learning wrapper (Mouchamps et al., 2026). Over 30 reproducible episodes on gymtorax/IterHybrid-v0 (3 policies × 10 seeds, ITER-hardware-realistic actuator noise σ = 0.5 % per Hemsworth 2017, Henderson 2020, Mitchell 2008) the QITE policy delivers a mean end-of-scenario fusion gain of Q = 8.57 ± 6.34, against Q = 7.69 ± 0.03 for the open-loop IterHybridAgent reference and Q = 2.22 ± 0.79 for a uniform-random baseline — +11.5 % above the reference at simultaneously 36 % larger Troyon-limit margin (β_N = 1.25 vs 1.94) and factor 2.7 larger sawtooth-onset margin (q_min = 1.70 vs 0.625). No disruptions occurred for any policy across the 30 episodes. The QITE engines sustained 4.21 × 10⁹ decisions per second across 5.285 × 10¹¹ total decisions in 445 seconds wall time. A previously unobserved bimodal operating-point behaviour of the closed-loop QITE controller is documented and discussed. The complete external-validation deposit — application source, per-step CSV logs of all 30 episodes, aggregate statistics, and tick-by-tick replay animations — is published openly under MIT / CC-BY-4.0 / CC0; only the QITE Core SDK itself remains proprietary. Full technical specification of the 22-page companion paper

Interdisciplinary treatise on the mathematical, physical, and information-theoretic foundations of the QITE formalism and its application to the real-time stabilization of magnetically confined fusion plasmas. 258 pages, 20 chapters, 4 appendices. Topics: spectral theory, Lyapunov stability, Grad–Shafranov equilibrium, MHD stability theory, neoclassical and anomalous transport, disruption avoidance, zero-allocation C++17 implementation, CUDA parallelization, ITER baseline simulation with 1,536 coupled QITE engines on a 128×192 grid. Validation against the IPB98(y,2) scaling law, the Greenwald density limit, and experimental data (JET, DIII-D). German patent applications Az. 10 2025 003 906.9 and Az. 10 2025 004 891.2.

The deposit additionally includes the executable reference implementation tokamak_sim in two prebuilt variants — tokamak_sim.exe (CPU, MSVC x64) and tokamak_sim_cuda.exe (CUDA 13.1, GPU-accelerated 1,536-engine sensor swarm at ~10⁹ QITE decisions per second) — together with full source (C++17 + CUDA), CMake/MSVC build scripts, and a 22-page companion paper (Simulation.pdf) extending the main treatise. The simulation environment couples the deterministic plasma physics layer (Bosch–Hale D-T reactivity, Modified Rutherford NTM dynamics, peeling-ballooning ELMs, Putterich impurity radiation, Sauter bootstrap current, Connor–Hastie runaway model) to a three-tier control hierarchy: a 1,536-engine QITE sensor swarm (treatise §7.2), a six-engine actuator-agent layer (NBI, ECRH, ICRH, gas-puffing, vertical PF coils, shattered-pellet injection — companion §3) governing all physical actuators autonomously through their individual coherence dynamics, and a parallel six-mechanism stochastic perturbation channel (ELM Poisson process, NTM onset roulette, Brownian vertical drift, NBI source glitches, sensor noise, locked-mode onset — companion §4) reproducing the operationally relevant statistical character of a real tokamak plasma. Empirical validation over a 390 s flat-top run (default seed 0xC0FFEE, severity σ=1.0, all stochastic mechanisms active, no operator interventions) reproduces the steady-state envelope of treatise §11.10 essentially exactly: disruption risk 26.7 % ± 4.7 %, no excursion above 32 %, zero terminal disruptions, mean fusion power 488 MW (within 2.4 % of the ITER design point of 500 MW), β_N=1.73, and a saturated (2,1)-NTM amplitude of 0.201, consistent with stochastically driven flat-top operation. Full bit-identical replication is supported through fixed-seed semantics and the run metadata persisted in every CSV log header.