基于自适应量子势场场的非线性优化算法

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel optimization algorithm based on an adaptive quantum field. The algorithm dynamically adjusts quantum field parameters based on environmental changes, offering enhanced scalability and flexibility compared to traditional approaches. We present a theoretical framework outlining the core mechanism and demonstrate its effectiveness through simulations and analysis. The core claim is that this adaptive algorithm can significantly improve the performance of quantum computations, particularly in complex environments. The algorithm utilizes a feedback loop to continuously refine the quantum field, leading to optimized results.

DOI: 10.5281/zenodo.22612069

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