Analysis of a hybrid quantum network for classification tasks

IET Quantum Communication

article

Gerhard Hellstern¹ 

[1] Department of Business Economics and Centre of Digital Innovations, Cooperative State University Baden-Württemberg

关键词: finance;    machine learning;    MNIST;    quantum computing;    regularisation;    tensorflow;    pattern classification;    learning (artificial intelligence);    quantum communication;   

DOI  :  10.1049/qtc2.12017

学科分类：环境科学（综合）

来源: Wiley

【 摘 要 】

In the era of noisy intermediate scaled quantum computers, one of the possible applications to search for an advantage of quantum computing is machine learning. Here, we report about an analysis, where a hybrid quantum-classical network is applied to classify non-trivial datasets (finance and MNIST data). In comparison to a pure classical network, we find an advantage when looking at several performance measures. As in classical machine learning, problems around overfitting the dataset arise. Therefore, we explore different possibilities to regularise the network.

【 授权许可】

CC BY|CC BY-ND|CC BY-NC|CC BY-NC-ND