Probability Logic and Quantum Computing: A Collaborative Optimization Algorithm

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the synergistic potential of probability logic and quantum computing for advanced optimization. We propose a novel optimization algorithm, leveraging the strengths of both paradigms – probability logic for uncertainty management and quantum computing for accelerated computation – to address complex systems optimization challenges across diverse fields. The core mechanism centers around a hybrid approach combining probabilistic reasoning with quantum simulations, specifically designed to mitigate the limitations of traditional optimization techniques. We demonstrate the algorithm's efficacy through illustrative examples in machine learning, materials science, and financial modeling, highlighting its capacity to achieve superior performance compared to conventional methods. The paper concludes with a discussion of the implications of this research for the future of optimization across various disciplines.

DOI: 10.5281/zenodo.22292470

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