Dynamic Topology-Based Quantum Entanglement-Based Optimization Based on Probability

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the application of dynamic topology-based quantum entanglement-based optimization to complex systems. Quantum entanglement, a fundamental phenomenon in quantum mechanics, offers unique capabilities for computation and optimization, particularly when combined with probabilistic algorithms. We propose a novel optimization algorithm predicated on these principles, leveraging quantum entanglement to achieve enhanced parameter control and predictive capabilities. The core mechanism centers on utilizing entangled states to represent and manipulate system parameters, enabling efficient search and solution. We demonstrate the algorithm's potential for solving complex optimization problems across various domains, driven by the inherent advantages of quantum mechanics. This work represents a significant advancement in optimization techniques, potentially offering a paradigm shift compared to classical approaches.

DOI: 10.5281/zenodo.22294328

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