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SCPN Fusion Core: Tokamak Plasma Physics Simulation and Neuro-Symbolic Control Suite

Abstract

A comprehensive tokamak plasma physics simulation and control suite with 54 Python modules, 10 Rust crates, 26 simulation modes, and a neuro-symbolic Petri net to stochastic neuron compiler. Features Grad-Shafranov equilibrium, MHD stability, transport, RF heating, neutronics, disruption prediction, and the MVR-0.96 compact reactor optimizer with optional SC-NeuroCore SNN integration.

Part of the SCPN (Self-Consistent Phenomenological Network) research framework by ANULUM. Published on Zenodo and Academia.edu.

Keywords

fusion, Grad-Shafranov, plasma physics, MHD, digital twin, spiking neural networks, neuro-symbolic, reactor design, tokamak, SCPN

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average