基于自适应几何的量子电路的优化算法

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing is a rapidly evolving field with immense potential for scientific discovery and technological advancement. However, the development of efficient quantum circuits remains a significant challenge, demanding sophisticated optimization techniques. This paper proposes a novel optimization algorithm, termed "Adaptive Geometry Optimization" (AGO), that leverages the principles of self-adaptive geometry to dynamically adjust quantum circuit parameters, leading to improved performance. Traditional optimization methods often struggle with the complex, non-linear nature of quantum circuits, while AGO offers a new approach to circuit design and optimization. The core mechanism of AGO involves systematically reshaping the circuit's geometry using a self-adaptive process, which results in enhanced circuit fidelity and ultimately, increased quantum computational capabilities. This research explores the theoretical foundations, implementation details, and preliminary experimental results of AGO, demonstrating its potential to significantly improve the performance of quantum algorithms.

DOI: 10.5281/zenodo.22298963

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