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Quantum Feedback Loop for Non-Linear Dynamical Systems

Jincheng Zhang

Published Sep 3, 2026• 0 citations
Publisher

Abstract

Quantum feedback loops offer a promising avenue for enhancing the stability and response time of non-linear dynamical systems. This paper investigates the application of quantum error correction to create a dynamically adjusting feedback mechanism that optimizes the system's state. We explore a novel quantum algorithm designed to iteratively refine the system's parameters, mitigating the effects of inherent noise and enhancing robustness. The core claim is that this approach will outperform traditional control strategies in the context of complex, non-linear systems. We present a theoretical framework and preliminary experimental results demonstrating the potential of this quantum-enhanced control method.

DOI
10.5281/zenodo.22278669

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Quantum feedback loops offer a promising avenue for enhancing the stability and response time of non-linear dynamical systems. This paper investigates the application of quantum error correction to create a dynamically adjusting feedback mechanism that optimizes the system's state. We explore a novel quantum algorithm designed to iteratively refine the system's parameters, mitigating the effects of inherent noise and enhancing robustness. The core claim is that this approach will outperform traditional control strategies in the context of complex, non-linear systems. We present a theoretical framework and preliminary experimental results demonstrating the potential of this quantum-enhanced control method.
This paper presents a novel adaptive quantum control algorithm incorporating a feedback mechanism to enhance the robustness and precision of quantum system manipulation. The core claim is to design an algorithm that dynamically adjusts control signals based on real-time feedback from the quantum system's state. The proposed mechanism leverages quantum measurements and optimization algorithms to continuously refine control parameters. This approach addresses limitations inherent in traditional quantum control methods by mitigating the effects of noise and uncertainty, ultimately leading to improved control accuracy. The algorithm's architecture and theoretical framework are thoroughly outlined, demonstrating its potential for achieving highly accurate control over complex quantum systems. The implementation details and performance analysis provide a strong foundation for future research and development in adaptive quantum control.
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