基于自适应量子电路的动态调整 - 拓扑信息学算法的加速器

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel dynamic adjustment algorithm for quantum circuits, leveraging self-adaptive parameter adjustment to optimize the performance of topological information theory (TIT) algorithms. Traditional quantum circuit design relies on manual parameter tuning, which is a time-consuming and error-prone process. Our algorithm dynamically adjusts circuit parameters to achieve superior performance, significantly accelerating the implementation of TIT algorithms. We demonstrate the effectiveness of this approach through a series of simulations and analysis, showcasing substantial improvements in algorithm execution time and qubit fidelity. The design incorporates a robust feedback mechanism to maintain optimal circuit characteristics throughout the optimization process. The core mechanism revolves around iteratively refining circuit parameters based on a learned objective function, providing a practical and efficient pathway for accelerating TIT algorithm development.

DOI: 10.5281/zenodo.22295727

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