基于自适应的量子态的超导量子计算

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the potential of a novel quantum computing paradigm based on dynamically adjusted superconducting quantum states. Traditional quantum computation often relies on static parameter settings, limiting scalability and stability. We propose a method utilizing self-adaptive quantum state parameters to dynamically adjust these parameters, thereby enhancing the system's performance. This approach offers a significant improvement in resource utilization and stability compared to conventional methods. The core mechanism centers around a feedback loop that continuously optimizes the quantum state based on observed performance metrics. We present a theoretical framework and preliminary experimental validation demonstrating the effectiveness of this dynamic adjustment strategy in achieving enhanced qubit coherence and reduced error rates. The results suggest a substantial advancement in the practical implementation of quantum computing.

DOI: 10.5281/zenodo.22183393

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