Axiomatic Forcing via Φ-Network Dynamics (Φ-ND): A Deterministic Control Architecture for Extreme-Scale Magnetohydrodynamics
Abstract
The pursuit of net-positive fusion energy via magnetic confinement represents the absolute limit of contemporary cyber-physical control theory. In next-generation burning plasma experiments (e.g., ITER), managing chaotic, non-linear H-mode plasma disruptions is gated by computational and hardware latencies inherent in classical reactive control paradigms. Furthermore, the integration of Large Language Models (LLMs) into extreme-scale physics is currently bottlenecked by probabilistic hallucinations when dealing with partial differential equations. This paper introduces "Axiomatic Forcing," a proprietary cognitive protocol that constrains LLMs using the discrete quantum-geometric topology of the Φ-Network Dynamics (Φ-ND) framework. To prove the efficacy of this human-AI symbiosis, the constrained LLM synthesized a mathematically flawless, AVX-512 optimized High-Order WENO5-Z sub-grid closure scheme that intrinsicly resolves the Navier-Stokes singularity without resorting to trivial algebraic flux limiters. Additionally, this paper exposes the inescapable diagnostic-actuation latency choke in current Tokamak Plasma Control Systems (PCS) and proposes Topological Predictive Control (TPC) to achieve real-time, feed-forward phase-locking of magnetic coils. The open-source C++ kernel is provided herein; the cognitive forcing protocol remains proprietary.
Related
- GEOMETRIC ARCHITECTURE OF WAVE HOMEOSTASIS: AXIOMATIC TRANSLATION OF THE MCEC MODEL INTO DYNAMICAL SYSTEMS THEORY
- The Toroidal Axiomatic Model of the Human Body: A Bioenergetic Architecture Based on Tesla's Mathematics (3-6-9) and the Sacred Geometry of the Vacuum
- The Minimum Viable Reality Four-Tuple: A Postulate Architecture for Deterministic Timelines
- The Ultimate Fate of AI and Its Forcing Mechanism: A Deduction Based on the Isomorphic Mapping of Cosmic Architecture
- The Network Emergent Architecture (N.E.A.) — An Axiomatic Derivation of the Standard Model and Classical Gravitation: Executive Whitepaper & Master Consensus
BibTeX
@misc{jordan2026axiomatic,
title = {{Axiomatic Forcing via Φ-Network Dynamics (Φ-ND): A Deterministic Control Architecture for Extreme-Scale Magnetohydrodynamics}},
author = {Ferenc Jordan},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23567691},
url = {https://zenodo.org/records/23567691},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Axiomatic Forcing via Φ-Network Dynamics (Φ-ND): A Deterministic Control Architecture for Extreme-Scale Magnetohydrodynamics
AU - Ferenc Jordan
PY - 2026
DA - 2026/10/22
PB - Zenodo
DO - 10.5281/zenodo.23567691
UR - https://zenodo.org/records/23567691
AB - The pursuit of net-positive fusion energy via magnetic confinement represents the absolute limit of contemporary cyber-physical control theory. In next-generation burning plasma experiments (e.g., ITER), managing chaotic, non-linear H-mode plasma disruptions is gated by computational and hardware latencies inherent in classical reactive control paradigms. Furthermore, the integration of Large Language Models (LLMs) into extreme-scale physics is currently bottlenecked by probabilistic hallucinations when dealing with partial differential equations. This paper introduces "Axiomatic Forcing," a proprietary cognitive protocol that constrains LLMs using the discrete quantum-geometric topology of the Φ-Network Dynamics (Φ-ND) framework. To prove the efficacy of this human-AI symbiosis, the constrained LLM synthesized a mathematically flawless, AVX-512 optimized High-Order WENO5-Z sub-grid closure scheme that intrinsicly resolves the Navier-Stokes singularity without resorting to trivial algebraic flux limiters. Additionally, this paper exposes the inescapable diagnostic-actuation latency choke in current Tokamak Plasma Control Systems (PCS) and proposes Topological Predictive Control (TPC) to achieve real-time, feed-forward phase-locking of magnetic coils. The open-source C++ kernel is provided herein; the cognitive forcing protocol remains proprietary.
ER -