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Paper 1

SNG-Based Real-Time Plasma Control System: From Operator Calculus to Hardware Implementation

Durhan Yazir

Year: 2026
Journal: Zenodo (CERN European Organization for Nuclear Research)
DOI: 10.5281/zenodo.18988234
arXiv: -

Controlling a fusion plasma is like trying to balance a spinning top inside a hurricane—while the top is millions of degrees hot and the hurricane is magnetic. Instabilities can tear the plasma apart in milliseconds, ending the reaction. For decades, we've been flying blind, reacting too slowly. Now, imagine giving the tokamak a brain—a super-fast co-processor that senses what's happening and reacts in microseconds, not milliseconds. This brain doesn't just follow pre-programmed rules; it understands the plasma through four simple mathematical operators derived from Spectral Nod Theory. What are these operators? Think of them as instincts: · One senses turbulence and dampens it before it grows. · One watches the density and gently resets it if it gets too high, preventing a collapse. · One skips the Coulomb barrier—the fundamental obstacle to fusion—by leveraging collective plasma effects to boost reactivity by up to 3.4×. · One detects instabilities like ELMs and reverses them in microseconds. We've designed a complete hardware-software system to bring these instincts to life. On the hardware side, an FPGA-based co-processor (like a specialized graphics card) sits alongside the tokamak's existing control computer, processing sensor data in under microseconds—fast enough to catch instabilities before they destroy the plasma. On the software side, a "digital twin" simulates the entire tokamak, allowing us to optimize the operators offline and even predict future behavior during experiments. The system is designed to plug into existing tokamaks like China's EAST and America's DIII-D, giving them an "upgrade kit" that could dramatically improve performance. We've estimated resource requirements, validated against current technology (FPGA-based machine learning already runs at 4.4 microseconds on DIII-D), and laid out a phased deployment roadmap. This isn't just theory—it's a blueprint for building the world's first quantum-inspired plasma operating system. The operators that dance at the Planck scale may soon dance through silicon, bringing us one step closer to practical fusion energy.

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Paper 2

Synergy between Charge Transfer and Spatial Descriptors in Determining the Band Gap of hP4-Na: An Interpretable Machine Learning Approach.

Zhang L, Wei Y, Yan X, Yang B

Year: 2026
Journal: Inorganic chemistry
DOI: 10.1021/acs.inorgchem.6c00324
arXiv: -

Electrides are a class of materials whose highly localized electrons in the lattice interstices exhibit anion-like behavior, known as interstitial quasi-atoms (ISQs). Nonmetallic electrides are promising for extreme-environment optical and sensing applications due to their pressure-retained band gaps and tunable electronic structures, yet the microscopic mechanisms governing their band gap remain unclear. Using the high-pressure phase hP4-Na, this study reveals these mechanisms through first-principles calculations under pressure and strain, combined with machine learning. Interpretability analysis identifies charge transfer () and electron spatial distribution () as dominant factors modulating the band gap. Through symbolic regression, we derive a concise analytical formula based solely on five electronic-structure descriptors, achieving excellent predictive accuracy ( > 0.98) against first-principles results. This directly confirms the electronic structure as the physical origin of the band gap in hP4-Na. Unlike previous studies focused on electron localization function, we show that is a key descriptor linking seemingly disparate properties like insulating behavior and superconductivity. Our study provides a microscopic understanding and a quantitative predictive framework for hP4-Na's electronic behavior under complex stress, establishing a foundation for rational design of high-pressure electrides.

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