Information Entropy Based Quantum Entanglement Geometry Adaptation

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel information-theoretic approach to geometry optimization, leveraging the principles of quantum entanglement to dynamically adjust geometric structures. We propose a model centered around quantifying information entropy as a guiding force for shaping data storage and processing efficiency. The core mechanism involves utilizing quantum entanglement to subtly influence the geometry, resulting in enhanced computational capabilities. The research explores the potential for this technique to improve data management and accelerate complex calculations. This work presents a framework for quantifying and manipulating geometric relationships through the inherent properties of quantum entanglement, ultimately aiming to achieve more efficient data processing and computation.

DOI: 10.5281/zenodo.22289377

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