基于量子算法的超参数优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper explores the potential of quantum computing to revolutionize the field of hyperparameter optimization. Traditional hyperparameter optimization methods often struggle with the complexity of the search space and the limitations of classical computation. We propose a novel quantum algorithm specifically designed to accelerate and improve this process. The core mechanism involves leveraging quantum superposition and entanglement to efficiently explore the parameter space and identify optimal hyperparameter configurations. We analyze the advantages and challenges of employing quantum computing for hyperparameter optimization, presenting a preliminary investigation demonstrating potential improvements in efficiency and solution quality compared to classical approaches. The paper concludes with a discussion of future research directions and potential applications in diverse scientific domains.

DOI: 10.5281/zenodo.22183776

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