基于自适应的量子态控制的拓扑网络优化

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel approach to quantum state control leveraging adaptive quantum state manipulation for improved quantum information transmission and processing. Traditional methods often require manual design, limiting flexibility and potentially hindering performance. Our proposed framework employs a self-adjusting quantum state control strategy, allowing the system to dynamically optimize the quantum state within a specified network topology. We demonstrate the efficacy of this method through a series of simulations and analyses, showcasing significant improvements in quantum entanglement generation and fidelity compared to existing optimization techniques. The core mechanism focuses on a continuous feedback loop that adjusts the quantum state based on measured outcomes, enabling automated parameter tuning. This results in a more robust and adaptable quantum network, ultimately leading to enhanced quantum information transfer and processing capabilities.

DOI: 10.5281/zenodo.22585651

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