Quantum Simulation-Based Probabilistic Algorithm

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel probabilistic algorithm, Quantum Simulation-Based Probabilistic Algorithm (QSPBA), leveraging the power of quantum simulation to predict complex system behavior and enhance risk assessment. Traditional probabilistic algorithms often struggle with computational complexity, particularly when dealing with intricate systems. Quantum simulation offers a paradigm shift by utilizing quantum mechanics to provide vastly improved predictive capabilities. The core mechanism of QSPBA centers around creating quantum entangled states to represent system states and facilitating probabilistic calculations, thereby increasing accuracy and efficiency compared to classical methods. We detail the algorithm's design, its theoretical foundation, and preliminary experimental results demonstrating its potential for advanced risk evaluation. The paper concludes with a discussion of future research directions and the potential impact on various fields.

DOI: 10.5281/zenodo.22296493

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