Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators

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).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-27
DOI
https://doi.org/10.5281/zenodo.21842370
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators

Priyanca Ford
Zenodo (CERN European Organization for Nuclear Research)
Model Reduction and Neural Networks
article

Physics-Informed AI and Quantum Technologies for Certifiable Real-Time Control of Compact Fusion Generators

Priyanca Ford
article en

Abstract

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).

Zenodo (CERN European Organization for Nuclear Research)
Fusion for Energy (ES)
Industry, innovation and infrastructure
Openalex Percentile: Top 17%
Model Reduction and Neural Networks
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