Quantum Chaos Field Theory: A Real-Space Optimization Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Chaos Field Theory (QCFT) offers a novel computational framework for optimization problems, leveraging the dynamic properties of quantum chaos. This paper explores the design and implementation of a real-space optimization algorithm based on QCFT, demonstrating its potential for efficient solution of complex problems and the generation of high-quality results. The core mechanism centers around the dynamic mapping of optimization landscapes and the application of quantum entanglement and superposition to enhance search efficiency. We present a preliminary implementation demonstrating the algorithm's effectiveness in solving a set of challenging optimization scenarios, highlighting the advantages of QCFT over traditional methods.

DOI: 10.5281/zenodo.22204389

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