基于量子拓扑的自适应量子计算量子子图优化

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum computing is a rapidly advancing field with the potential to revolutionize various industries through its unique computational capabilities. However, achieving high-performance quantum algorithms requires careful optimization of quantum circuits, particularly the design of quantum state vectors, which is currently a significant bottleneck. This paper introduces a novel approach to quantum state vector optimization leveraging the principles of quantum topology. We propose a method that dynamically adjusts the quantum state by exploiting the inherent topological properties of the quantum system, resulting in improved accuracy and efficiency in various quantum computing tasks. The core mechanism centers around constructing and manipulating quantum states through a carefully orchestrated topological transformation, offering a fundamentally different perspective on optimization compared to existing methods. This work demonstrates the effectiveness of this approach through theoretical analysis and preliminary experimental validation, showcasing its potential to significantly enhance quantum computation.

DOI: 10.5281/zenodo.22270608

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