Adaptive Quantum Feedback Control Algorithm

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper presents an Adaptive Quantum Feedback Control Algorithm (AQFCA) designed to achieve high-precision control of quantum systems. The core of the algorithm lies in utilizing quantum measurements to generate feedback signals, which are then employed to dynamically adjust the parameters of the quantum system. This approach leverages the principles of reinforcement learning to optimize the control strategy, addressing the inherent precision challenges associated with traditional quantum feedback control. The AQFCA offers a novel solution for enhancing the accuracy and reliability of quantum control, thereby providing a crucial foundation for the practical application of quantum technologies. The algorithm's implementation involves a closed-loop system where a measurement of the quantum state is continuously fed back, and the control parameters are adjusted based on this feedback. The use of reinforcement learning allows the system to adapt to the specific characteristics of the quantum system, further improving control accuracy.

DOI: 10.5281/zenodo.22268426

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