Quantum Geometry Topology Optimization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Geometry Topology Optimization (QGTO) is a novel approach to optimizing complex geometries, leveraging the principles of quantum mechanics and topology to achieve unprecedented levels of precision and efficiency. This paper explores the potential of QGTO to automate the design process, addressing limitations inherent in traditional methods. We propose a framework centered around quantum computation, specifically utilizing quantum algorithms to dynamically adjust geometric parameters during optimization. The core mechanism involves exploiting quantum entanglement and superposition to explore a vast conformational space, resulting in significantly reduced computational costs and enhanced representation capabilities for high-dimensional data. The paper details the theoretical underpinnings of the proposed algorithm, demonstrates its efficacy through illustrative examples, and discusses future research directions.

DOI: 10.5281/zenodo.22197505

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