基于贝叶斯网络量子计算的概率推理算法

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel probabilistic reasoning algorithm based on Bayesian networks for quantum computation. Quantum computation, while promising, often struggles with complex probabilistic inference, limiting the potential of quantum algorithms. This research explores a new approach that leverages the power of Bayesian networks to enhance quantum computation's reasoning capabilities. We propose a method that integrates quantum computation with Bayesian network inference, aiming to improve the accuracy and efficiency of probabilistic reasoning. The core mechanism centers around constructing and applying Bayesian networks to represent and reason about the state space of a quantum system, facilitating the exploration of multiple possible outcomes and guiding the algorithm towards optimal solutions. This work presents a framework for improving quantum algorithms through enhanced probabilistic inference, particularly relevant for complex problems requiring nuanced reasoning. The research will also examine the potential benefits and challenges of this approach.

DOI: 10.5281/zenodo.22266248

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