Quantum Geometry Mapping: A Dynamic Optimization Approach

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Geometry Mapping (QGM) presents a novel approach to geometric optimization utilizing quantum entanglement and topological structures. This work introduces a dynamic optimization method predicated on the properties of quantum entanglement, aiming to enhance the efficiency and robustness of geometric transformations. The core mechanism involves the creation of entangled quantum mappings, which are then iteratively refined through a process of quantum state manipulation, ultimately leading to optimized geometric configurations. The proposed method offers a potential paradigm shift in geometric optimization, leveraging the unique capabilities of quantum mechanics to achieve superior results compared to classical optimization techniques. This paper provides a comprehensive theoretical foundation, detailing the underlying principles and mathematical framework of QGM, and presents preliminary experimental results demonstrating its effectiveness.

DOI: 10.5281/zenodo.22195773

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