Quantum-Enhanced Probability Density Estimation for Complex Systems

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper investigates the application of quantum entanglement to improve the estimation of probability density within complex systems. The core claim posits the design of a quantum algorithm, termed "Quantum Entangled Probability," that leverages entanglement to accelerate and enhance predictive modeling capabilities. Current probabilistic methods face significant computational challenges, particularly when dealing with intricate systems exhibiting high dimensionality and complex dependencies. Quantum computing, through its unique properties of superposition and entanglement, offers the potential to overcome these limitations, providing a pathway to more accurate and efficient predictions. This research explores the theoretical foundations and practical implementation of this novel approach, focusing on its potential impact on diverse fields requiring precise probabilistic modeling. The paper details the Quantum Entangled Probability algorithm, its underlying principles, and preliminary experimental results demonstrating its efficacy in a simulated environment.

DOI: 10.5281/zenodo.22301547

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