Dimension Generalization with Quantum Entanglement

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper investigates the integration of dimensionality generalization and quantum entanglement to achieve highly accurate geometric modeling. The core claim is to develop a novel method leveraging quantum entanglement to map low-dimensional spaces to higher-dimensional spaces, utilizing entanglement for precise geometric calculations and enabling high-precision modeling. We propose a quantum computing algorithm designed to perform geometric computations within low-dimensional spaces, guided by the entangled states generated by this process. This approach offers a fundamentally new pathway for geometric data analysis and modeling, potentially surpassing the limitations of classical techniques. The paper explores the potential of this combination to address challenges in geometric representation and precise calculation, highlighting the key mechanisms involved and outlining future research directions.

DOI: 10.5281/zenodo.22638815

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