Dynamic Particle Quantum Computing: A Novel Approach to Quantum Algorithm Optimization and Expansion

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing holds immense promise for revolutionizing various fields, from drug discovery to materials science. However, the development of practical quantum algorithms is hindered by the need for sophisticated optimization and expansion techniques. This paper introduces a novel quantum computing framework, Dynamic Particle Quantum Computing (DPQC), leveraging dynamic particle models to dynamically adjust quantum algorithms, thereby optimizing their performance and expanding their applicability. We detail the framework's design, key mechanisms, and potential benefits. Our analysis demonstrates the significant advantages of DPQC over traditional approaches in optimizing and extending quantum algorithms.

DOI: 10.5281/zenodo.22187070

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