基于量子态的计算几何优化

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper presents a novel approach to optimization using quantum computation, specifically focusing on geometric optimization. The core concept revolves around transforming optimization problems into quantum states, leveraging quantum entanglement and quantum computing's unique properties to achieve enhanced efficiency. We explore a method for mapping complex geometric structures to a quantum state space, utilizing quantum entanglement as a key enabling mechanism. The potential benefits include the ability to tackle optimization problems previously intractable with classical algorithms, offering a fundamentally new perspective on geometric problem-solving. The research investigates the feasibility of this approach through theoretical analysis and initial simulations, highlighting the advantages and challenges associated with implementing this quantum optimization strategy.

DOI: 10.5281/zenodo.22222423

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