Quantum Topology: A Randomness-Driven Optimization Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum topology, a fascinating field of theoretical physics, has recently gained significant attention for its potential to revolutionize computational methods. This paper explores the application of quantum topology to the design of an optimization algorithm, leveraging the inherent randomness within topological systems to enhance the quality of optimization results. We propose a novel approach that utilizes quantum properties to guide the search process, mitigating the limitations of traditional optimization algorithms. The core claim centers around the development of an algorithm that, through the introduction of random influence, achieves a higher degree of optimization quality. This work investigates the potential of quantum topology to enhance optimization, specifically focusing on the challenges faced by classical optimization algorithms in complex systems. The paper details the core mechanism, highlighting how the random nature of quantum topology is leveraged to create a more robust and efficient optimization process.

DOI: 10.5281/zenodo.22204554

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