基于自适应的分布式优化算法的量子模拟

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel quantum simulation technique leveraging a dynamically adaptive distributed optimization algorithm. Traditional quantum simulation methods are often static, limiting efficiency and precision. Our approach dynamically adjusts quantum simulation parameters to optimize performance, resulting in significant improvements in simulation speed and accuracy. We present a framework designed to achieve this dynamic adjustment, offering a promising pathway for efficient and precise quantum system analysis. The core mechanism involves a self-optimizing quantum simulator, enhancing simulation capabilities. This work demonstrates the effectiveness of this approach through simulations of complex quantum systems.

DOI: 10.5281/zenodo.22521870

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