基于动态量子势的自适应量子算法

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper presents a novel quantum algorithm based on dynamically adjusted quantum potentials. Traditional quantum algorithms often rely on static quantum states, limiting their efficiency. This work introduces a self-adaptive quantum algorithm that dynamically adjusts the quantum potential based on input data, resulting in enhanced algorithm performance. The core mechanism involves a system of quantum operators that iteratively modify the potential energy landscape to optimize the quantum algorithm's convergence and solution quality. We rigorously analyze the algorithm's performance through simulations and demonstrate its effectiveness in a variety of quantum algorithms. The results suggest a significant improvement in the efficiency of several key quantum algorithms, establishing a promising approach for enhancing quantum computation.

DOI: 10.5281/zenodo.22254294

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