基于动态自律性结构的量子计算的几何优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of dynamic self-organization principles to quantum computation, proposing a novel geometric optimization framework. Traditional quantum algorithms often struggle with complex geometries, necessitating sophisticated optimization techniques. This work introduces a framework leveraging self-organization to efficiently explore and optimize geometric structures, ultimately achieving global optimization. The core mechanism centers around the inherent ability of self-organization to generate diverse solutions and adapt to changing conditions, offering a pathway toward more robust and efficient quantum algorithms. We demonstrate the effectiveness of this approach through a series of illustrative examples, showcasing its potential to address challenges in quantum circuit design and optimization.

DOI: 10.5281/zenodo.22192400

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