自适应量子算法的并行优化机制

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive quantum algorithm optimization mechanism designed to leverage the unique characteristics of quantum hardware and the inherent parallelism of quantum algorithms. The core concept revolves around a dynamic adjustment of parallel execution based on real-time hardware assessments, aiming to significantly enhance the efficiency of quantum computations. We present a framework that analyzes quantum circuit parameters and automatically optimizes the parallelization strategy, leading to improved performance. The paper details the proposed mechanism, its implementation, and preliminary results demonstrating significant improvements over existing approaches, particularly in scenarios involving complex quantum circuits. The focus is on providing a robust and adaptable approach to quantum algorithm optimization.

DOI: 10.5281/zenodo.22467276

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