Adaptive Quantum Circuit

Jincheng Zhang

Published Sep 6, 2026• 0 citations

Abstract

Quantum circuit design presents a significant challenge due to the inherent complexity of quantum systems. Traditional methods rely heavily on expert knowledge and often struggle to efficiently explore the vast design space. This paper introduces an adaptive quantum circuit, a novel approach that leverages machine learning to dynamically adjust circuit parameters and structure based on input data characteristics, ultimately improving circuit performance and efficiency. The core mechanism centers around a machine learning model trained to learn and optimize circuit design through data analysis. This research explores the potential of this technique to overcome limitations of conventional circuit design and pave the way for more efficient and adaptable quantum systems. The study focuses on the implementation of a specific adaptive circuit design for a simplified quantum system, demonstrating its effectiveness through quantitative analysis.

DOI: 10.5281/zenodo.22498118

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