Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators — reproducibility deposit (code, data, figures)

This deposit accompanies the paper "Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators" (P. I. Ford, Kronos Fusion Energy). It contains the manuscript, the Simulation & Validation Package, all figures, the underlying data (CSV), the analysis and plotting scripts, and the reproducibility harness (run-all driver, environment pins, per-artifact MD5 validation manifests, a pre-registered acceptance-criteria register, and three rounds of adversarial candor-sweep audits) for a methods-and-certification study of the KRONOS-CTRL AI-native digital-twin control architecture, evaluated on two compact fusion machine classes: a negative-triangularity spherical-tokamak breeder and a D-3He tandem-mirror burner. SCOPE AND PROVENANCE (binding). Kronos Fusion Energy operates no fusion plant. Every result is obtained on a physics-based digital twin, on public datasets, or on simulation, tagged by source (SIM / TWIN / PUBLIC / TRL-SURVEY / RESOURCE-EST / ENGINEERING-BASIS). No result uses or implies operating-plant telemetry. Fault-tolerant quantum-computing resource estimates find no classical crossover this decade; the quantum proof-of-concept is simulator-only; the present-tense quantum result is quantum-inspired classical (tensor networks). ITER material is used only as an engineering-basis benchmark (ITER has not operated), cited by document identifier, not redistributed here. REPRODUCIBILITY. All results regenerate from a fixed seed (20260726). Tier-1 quantities reproduce byte-identically; Tier-2 (trained-model) metrics are five-seed tolerance bands with pinned environments. See AI-Quantum-Simulation-Validation-Package-2026.pdf and REPRODUCE.md.