自适应量子势场优化算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing offers tremendous potential, but realizing this potential requires careful design of quantum systems, particularly their quantum states. Current approaches to quantum state design often rely on static optimization strategies, which struggle to effectively address the inherent complexities of quantum systems. This paper introduces a novel self-adaptive quantum field optimization algorithm, designed to dynamically adjust quantum field parameters to enhance quantum computation performance. We propose a mechanism that continuously refines the quantum field based on the system's dynamics, achieving a more tailored and effective optimization process. The core claim of this research is that this algorithm can significantly improve the performance of quantum computations by optimizing quantum field parameters through a self-adaptive process. The paper details the algorithm's design, validation through simulations, and potential future directions.

DOI: 10.5281/zenodo.22289760

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