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Superconducting Qubits Quantum Error Correction Fault Tolerance Quantum Compilation Routing Architecture Quantum Machine Learning

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

OpenAlex
Authors: Durhan Yazir

Year

2026

Paper ID

29986

Status

Preprint

Abstract Read

~2 min

Abstract Words

313

Citations

0

Abstract

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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External citation index: OpenAlex citation signal • updated 2026-03-16 09:43:20

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