自适应量子态的动态拓扑优化

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum computing is poised to revolutionize computation, offering the potential for unparalleled processing power. However, achieving reliable and efficient quantum computation requires careful management of quantum states, a challenge often limited by inherent fragility and susceptibility to noise. This paper explores the application of a novel dynamic拓扑优化 algorithm to enhance the efficiency and adaptability of quantum states. We propose a method that dynamically adjusts quantum state parameters based on an internal representation of the system, optimizing for key metrics such as fidelity, coherence, and error rate. The core mechanism involves a self-organizing topology, where the algorithm iteratively refines the quantum state by strategically manipulating its connectivity, guided by a learned representation of the system's dynamics. We demonstrate the effectiveness of this approach through theoretical analysis and simulation, showcasing significant improvements in quantum fidelity and reduced error rates compared to conventional optimization techniques. The results highlight the potential for a paradigm shift in quantum state management, paving the way for more robust and versatile quantum systems.

DOI: 10.5281/zenodo.22245645

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