Dynamic Quantum Adaptive Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel Dynamic Quantum Adaptive Algorithm (DQA) designed to enhance the efficiency and effectiveness of quantum algorithms through dynamic adjustment of algorithm parameters. Traditional quantum algorithms often rely on static parameter settings, limiting their potential for optimal performance. DQA leverages the inherent quantum system state to dynamically adjust these parameters, allowing for adaptive optimization of the algorithm's behavior. We present a detailed explanation of the algorithm's core mechanism, including the state representation, parameter adjustment strategy, and resulting performance improvements across a range of quantum benchmark problems. The paper concludes with a discussion of the potential implications of this approach for the design and implementation of quantum algorithms.

DOI: 10.5281/zenodo.22263541

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