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Based on Quantum Entanglement: Adaptive Probability Models

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

This paper investigates a novel probabilistic model leveraging quantum entanglement to dynamically adjust probability distributions within a system. We propose a framework that allows the model to adapt to changing system states, resulting in enhanced accuracy and computational efficiency compared to traditional approaches. The core mechanism involves exploiting the inherent correlations within entangled states to create a self-correcting probability function. This research explores the potential of quantum entanglement for optimizing probabilistic calculations, offering a promising path towards more robust and efficient computation.

DOI
10.5281/zenodo.22266349

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