Probability Logic and Quantum Computing: A Framework for Hidden Variable Modeling

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the application of probability logic and quantum computing to the design of a novel framework for hidden variable modeling. The core claim is that a probabilistic model, dynamically adjusted through quantum computation, can effectively simulate complex systems, providing accurate estimation and prediction of hidden variables. This framework leverages the inherent properties of quantum computing, specifically its resistance to noise, to enhance the model's precision. The study investigates the potential benefits of this approach, highlighting its advantages over traditional methods and its promise for advancing the field of hidden variable analysis.

DOI: 10.5281/zenodo.22183979

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