拓扑张效性量子计算的自适应优化算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing is poised to revolutionize various fields, offering unprecedented computational power. However, realizing this potential necessitates overcoming fundamental challenges, particularly in managing and optimizing quantum states, especially entangled states. This paper investigates a novel self-adaptive optimization algorithm for quantum state correction, designed to enhance the computational capabilities of quantum systems and improve stability. The algorithm leverages the inherent adaptability of quantum entanglement to dynamically adjust the fidelity of these entangled states, leading to a significant improvement in efficiency and resilience. We introduce a framework that dynamically adjusts the entanglement parameters based on the evolution of the quantum system, offering a distinct approach to optimizing quantum computation. The core mechanism focuses on refining the entanglement topology through iterative adjustments, ultimately addressing a critical bottleneck in current quantum algorithms. The potential impact of this algorithm is substantial, offering a pathway towards more robust and efficient quantum computations across diverse applications.

DOI: 10.5281/zenodo.22290504

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