Applying Quantum Tensor Networks in Machine Learning: A Systematic Literature Review

Erico Souza Teixeira, Erico Souza Teixeira, Yara Rodrigues Inácio, Yara Rodrigues Inácio, Pamela Bezerra, Pamela Bezerra

2025

Abstract

Integrating quantum computing (QC) into machine learning (ML) holds the promise of revolutionizing computational efficiency and accuracy across diverse applications. Quantum Tensor Networks (QTNs), an advanced framework combining the principles of tensor networks with quantum computation, offer substantial advantages in representing and processing high-dimensional quantum states. This systematic literature review explores the role and impact of QTNs in ML, focusing on their potential to accelerate computations, enhance generalization capabilities, and manage complex datasets. By analyzing 23 studies from 2013 to 2024, we summarize key advancements, challenges, and practical applications of QTNs in quantum machine learning (QML). Results indicate that QTNs can significantly reduce computational resource demands by compressing high-dimensional data, enhance robustness against noise, and optimize quantum circuits, achieving up to a 10-million-fold speedup in specific scenarios. Additionally, QTNs demonstrate strong generalization capabilities, achieving high classification accuracy (up to 0.95) with fewer parameters and training data. These findings position QTNs as a transformative tool in QML, bridging critical limitations in current quantum hardware and enabling real-world applications.

Paper Citation

in Harvard Style

Teixeira E., Inácio Y. and Bezerra P. (2025). Applying Quantum Tensor Networks in Machine Learning: A Systematic Literature Review. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO; ISBN 978-989-758-737-5, SciTePress, pages 847-854. DOI: 10.5220/0013402100003890

in Bibtex Style

@conference{qaio25,
author={Erico Teixeira and Yara Inácio and Pamela Bezerra},
title={Applying Quantum Tensor Networks in Machine Learning: A Systematic Literature Review},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO},
year={2025},
pages={847-854},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013402100003890},
isbn={978-989-758-737-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 1: QAIO
TI - Applying Quantum Tensor Networks in Machine Learning: A Systematic Literature Review
SN - 978-989-758-737-5
AU - Teixeira E.
AU - Inácio Y.
AU - Bezerra P.
PY - 2025
SP - 847
EP - 854
DO - 10.5220/0013402100003890
PB - SciTePress