Title: Quantum-Enhanced Probability Kernel for Statistical Physics

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum-enhanced probability kernel models represent a significant advancement in statistical physics, aiming to overcome limitations of classical models when dealing with complex systems exhibiting high dimensionality. This research proposes a novel approach utilizing quantum mechanics to enhance the probability kernel, thereby improving the accuracy of predictions for a wide range of systems. We develop a new statistical physics model that integrates quantum probabilities to represent uncertainty and enhance the prediction of statistical behavior. This work explores the potential of quantum-enhanced kernels to improve predictive capabilities for systems with intricate dynamics, particularly those exhibiting quantum-like behavior. The core mechanism involves introducing a "Quantum Probability Kernel" – a kernel that dynamically updates probabilities based on quantum principles, offering a potential paradigm shift in statistical physics. The paper details the mathematical foundation of the model, explores its computational feasibility, and presents preliminary results demonstrating enhanced predictive accuracy compared to traditional kernel methods. Furthermore, we discuss the challenges and future directions of this research, including the exploration of different quantum mechanisms and the application of the model to specific systems.

DOI: 10.5281/zenodo.22225923

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