Quantum Chaos Optimization and Simulation

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper explores the application of quantum chaos theory to optimization and simulation, focusing on the development of a novel non-linear geometric optimization framework. We introduce a "Quantum Chaos Geometry Optimization" (QCGO) approach, leveraging the inherent non-linear properties of chaotic systems to enhance the efficiency of optimization algorithms. The core mechanism involves mapping geometric structures onto a quantum chaotic state space, facilitating adaptive optimization and potential quantum computation benefits. This research presents a conceptual framework and preliminary results demonstrating the potential for quantum chaos to improve geometric optimization procedures. The paper concludes with a discussion of the challenges and future directions of this research.

DOI: 10.5281/zenodo.22489307

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