Quantum Entanglement and Probability Field Theory - A Computational Paradigm

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper investigates the application of quantum entanglement to probability field theory, proposing a novel computational framework predicated on the principles of quantum superposition and entanglement. We explore the potential of this approach to enhance the efficiency of probabilistic computation, specifically focusing on its implications for machine learning. The core of this work centers on the conceptualization of probability events as quantum states, leveraging entanglement to facilitate complex computations and ultimately, explore its applicability to machine learning tasks. The paper details the underlying mathematical foundations and potential benefits of this new computational paradigm, offering a significant departure from traditional probability modeling approaches.

DOI: 10.5281/zenodo.22219516

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