基于动态自适应的量子纠缠计算的自适应自适应矩阵

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum entanglement, a cornerstone of quantum mechanics, holds immense potential for transformative technologies, including quantum computing and quantum communication. However, achieving practical quantum computation necessitates the development of robust and adaptable quantum algorithms. This paper explores a novel approach to quantum entanglement computation, focusing on a dynamic self-adaptive matrix based framework. We introduce a method that dynamically adjusts the entanglement state based on input data's geometric characteristics, thereby enhancing computational accuracy. This approach overcomes limitations of static parameterization, offering a more flexible and potentially more efficient solution for complex quantum calculations. The core mechanism involves an optimization loop to refine the entanglement configuration, ultimately improving the fidelity of the computation. This work represents a significant advancement in the design of quantum algorithms, specifically targeting the challenges of adaptive quantum computation.

DOI: 10.5281/zenodo.22201661

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