The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.
Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators
Authors: Ford, P. I.
Summary
A layered digital-twin control architecture holding three technology-readiness tiers apart. A control-barrier safety clamp gives a provable zero-escape guarantee on the reduced-order operating envelope; quantum sensing is near-term diagnostics; quantum computation is an offline calibration tier with no resource crossover this decade. Every result is on a physics-based twin, on public data, or in simulation. New version (2.0).
Canonical records
- Zenodo (canonical DOI): https://doi.org/10.5281/zenodo.22132484
- Figshare DOI: https://doi.org/10.6084/m9.figshare.33361314
- Publisher: Kronos Fusion Energy — 2026 Physics De-Risking series
What's in this repository
*_Editorial_2026.pdf— the editorial edition of the paper.*_reproducibility_bundle.zip— the reproducibility bundle: toolkit source, the per-gate runs the paper cites, and a student pack (concept notes, tutorial, glossary,reproduce.ipynb,requirements.txt).
Reproduce
unzip *_reproducibility_bundle.zip -d bundle && cd bundle
pip install -r requirements.txt
jupyter notebook reproduce.ipynb
Scope
Physics and engineering only; no economics. Every quantity traces to a documented gate in the KRONOS de-risking register. Honest gates are stated in the paper.
- Downloads last month
- 19