Title: Adaptive Quantum Feedback Loops for Algorithmic Stability

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing holds immense promise for revolutionizing numerous fields, yet the inherent instability of quantum algorithms poses a significant challenge. This paper investigates the application of adaptive quantum feedback loops to enhance algorithmic stability, addressing the problem of divergence and ensuring consistent performance across a wide range of conditions. We introduce a novel system of continuous monitoring and adjustment, leveraging the inherent dynamics of quantum systems to proactively mitigate instability. The core mechanism centers around a feedback loop that dynamically adjusts quantum parameters based on the algorithm's output, effectively correcting for deviations and promoting stability. This approach offers a potential pathway to significantly improve the reliability and predictability of quantum computations.

DOI: 10.5281/zenodo.22187202

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