Adaptive Quantum Self-Adaptation Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing offers the potential for exponential speedups over classical computing, but current algorithms often struggle to reach this potential due to the complexities of managing quantum states and the inherent limitations of quantum hardware. This paper introduces the Adaptive Quantum Self-Adaptation Algorithm (ASFAA), a novel quantum control strategy designed to dynamically adjust quantum operations based on the system's state. The algorithm leverages a self-adaptive mechanism to continuously refine quantum parameters, optimizing for improved performance and robustness. We present a theoretical framework for the algorithm's operation, demonstrating its ability to achieve significant efficiency gains in various quantum systems through automated parameter adjustments. The core claim of this research is that ASFAA provides a pathway to efficient quantum computation by automating the optimization of quantum gate parameters. This advancement addresses a critical challenge in quantum algorithm design and opens possibilities for more practical and scalable quantum computations.

DOI: 10.5281/zenodo.22204093

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