@article{ME160F469,
title = "Effect of Gate Variations on MNIST Classification in QNN: Experimental Study and Analysis",
journal = "The Journal of Korean Institute of Communications and Information Sciences",
year = "2024",
issn = "1226-4717",
doi = "10.7840/kics.2024.49.2.254",
author = "Seok Bin Son, Hankyul Baek, Soohyun Park",
keywords = "QNN, Gate variation, Quantum gate, PQC, MNIST",
abstract = "Recently, QNNs have emerged as a promising method for big data processing because they can process data at high speeds while using fewer parameters than existing machine learning algorithms. In the structure of QNN, the performance is determined by which quantum gates are used in the PQC, which constitutes the quantum circuit. Therefore, we conduct a performance comparison experiment in this paper using various quantum gates in QNNs. Through four comparison experiments using the MNIST dataset, we confirm that performance differences occur depending on the use of gates in QNNs and discuss the reasons for the performance differences. Therefore, in this paper, we verify that the performance of QNNs varies depending on the quantum gate variation."
}