基于动态量子势场的自适应拓扑优化算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel algorithm for quantum system optimization based on dynamic quantum fields. Traditional optimization methods often struggle with complex systems exhibiting dynamic behavior, requiring significant computational resources and potentially leading to instability. Our proposed algorithm leverages the inherent dynamism of quantum fields to dynamically adjust the field distribution, thereby enhancing the stability and performance of quantum systems. The core mechanism involves continuous monitoring of the quantum field's state and applying a feedback loop to optimize the field distribution. This adaptive approach significantly reduces the computational burden and improves the robustness of the optimization process. We demonstrate the effectiveness of this algorithm through simulations and preliminary experiments, showcasing its ability to optimize complex quantum systems with improved stability and reduced computational cost.

DOI: 10.5281/zenodo.22195377

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