基于量子拓扑的自适应优化器

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive optimization algorithm based on quantum topology. Traditional optimization algorithms are often static, failing to adequately address complex systems. We propose a system leveraging quantum entanglement, termed "拓扑脉冲"(拓扑脉冲), to dynamically adjust optimization parameters. This mechanism allows the algorithm to adapt to the underlying quantum topology of the problem space, significantly enhancing optimization efficiency and robustness. The proposed method offers a fundamentally different approach to optimization, potentially surpassing the limitations of conventional techniques. This work presents a preliminary investigation into the potential of quantum topology in optimization.

DOI: 10.5281/zenodo.22295238

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