Dynamic Topology Structures Based on Probability: A Quantum Algorithm for Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

The design of quantum algorithms presents significant challenges due to their inherent complexity and sensitivity to initial conditions. This research explores the application of dynamic topology, a novel approach leveraging the properties of topological structures, to optimize quantum algorithm parameters. We propose a framework that dynamically adjusts quantum state parameters based on probabilistic feedback, aiming to significantly enhance the efficiency and accuracy of quantum computations. This work introduces a new algorithm, 'Quantum Flux,' which utilizes a dynamically evolving topology to guide the exploration of parameter space, resulting in a more robust and adaptable quantum algorithm. The core mechanism focuses on iteratively refining quantum states through probabilistic adjustments, minimizing the impact of noise and maximizing the likelihood of finding optimal solutions. This paper provides a detailed explanation of the Quantum Flux algorithm, its mathematical foundations, and preliminary experimental results demonstrating its effectiveness in a specific quantum simulation task.

DOI: 10.5281/zenodo.22289317

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