基于自适应的量子模拟算法

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum simulation is a crucial technique for simulating quantum systems, offering the potential to unlock new scientific discoveries and technological advancements. Traditional quantum simulation methods often rely on fixed parameters, limiting their accuracy and efficiency. This paper introduces a novel approach to quantum simulation – a dynamically adaptive quantum simulator – designed to overcome these limitations by dynamically adjusting simulation parameters based on the input data's quantum characteristics. We propose a new algorithm that incorporates self-tuning mechanisms to enhance the fidelity of quantum simulations. The core mechanism involves a feedback loop that continuously optimizes simulation parameters to minimize errors and maximize accuracy. This work demonstrates the effectiveness of the proposed algorithm through a series of quantitative analyses and illustrative examples, showcasing its improved performance compared to existing methods. The core claim is that this algorithm enables more precise and efficient quantum simulations by leveraging dynamic parameter adjustments.

DOI: 10.5281/zenodo.22265310

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