自适应量子算法的参数调整策略

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper presents a novel approach to quantum algorithm optimization utilizing an adaptive parameter adjustment strategy. Traditional parameter optimization methods often rely on fixed settings, lacking the flexibility to dynamically respond to the algorithm's evolution during execution. This work introduces a dynamically adjusting parameter scheme designed to automatically refine quantum circuit parameters, leading to improved algorithm performance and stability. The core mechanism involves a feedback loop that monitors the algorithm's progress and adjusts parameters based on observed outcomes. We demonstrate the effectiveness of this approach through a series of simulations and analyses, showcasing significant enhancements in convergence speed and fidelity compared to existing static optimization methods. The proposed strategy offers a promising pathway towards more efficient quantum computation.

DOI: 10.5281/zenodo.22517220

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