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Quantum Chaos Optimization Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

Quantum Chaos Optimization Algorithm (QCOA) is a novel optimization algorithm inspired by quantum chaos theory, designed to automatically discover optimal solutions for complex systems. This algorithm leverages the inherent properties of quantum chaos, specifically its self-alignment and stochastic nature, to efficiently navigate intricate problem spaces and identify optimal configurations. The core mechanism centers around a dynamically adjusted quantum state representation, enabling the algorithm to explore a vast solution space with enhanced adaptability and reduced computational cost compared to traditional optimization techniques. The proposed algorithm demonstrates significant potential across diverse fields, including machine learning, circuit design, and materials science, offering a fundamentally new approach to problem-solving. This paper will detail the theoretical underpinnings of the QCOA, its implementation, and preliminary results demonstrating its effectiveness in challenging scenarios.

DOI
10.5281/zenodo.22266417

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