基于量子态的自适应扰动算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive perturbation algorithm based on quantum state representation. Traditional perturbation methods often rely on manual parameter tuning, limiting their adaptability. This work proposes a quantum state-driven approach that automatically adjusts perturbation parameters based on the algorithm's output, resulting in enhanced perturbation effectiveness. We explore the application of quantum state analysis to achieve this adaptive control. The core mechanism involves encoding the input data into a quantum state and leveraging this state to dynamically adjust the perturbation parameters, providing a more robust and efficient approach to perturbing systems. The proposed algorithm demonstrates improved performance across a range of perturbation tasks, showcasing the potential of quantum state representation for adaptive control.

DOI: 10.5281/zenodo.22199164

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