Correlation Field Theory with Adaptive Scales

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Correlation Field Theory (CFT) provides a framework for understanding the statistical properties of physical systems, particularly in areas like quantum mechanics and statistical mechanics. However, traditional CFT often struggles with scaling issues, particularly when dealing with systems exhibiting intricate geometry. This paper introduces a novel approach, termed Correlation Field Theory with Adaptive Scales, designed to overcome these challenges by dynamically adjusting the correlation field's strength based on the system's geometry. We propose a mechanism that iteratively refines the correlation field's parameters to better represent the system's underlying structure, addressing scale invariance and enabling a more accurate description of complex phenomena. The paper details the theoretical foundation, mathematical formulation, and experimental validation of this approach, demonstrating its effectiveness in analyzing specific examples involving non-uniform geometries.

DOI: 10.5281/zenodo.22191156

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