Welcome to Francis Academic Press

Academic Journal of Computing & Information Science, 2023, 6(12); doi: 10.25236/AJCIS.2023.061214.

Quantum Machine Learning: Past, Present, and Future


Tianle Yan

Corresponding Author:
Tianle Yan

Liberty High School, Renton, WA, USA, 98059


In recent decades, classical machine learning (CML) has seen rapid development, allowing computers to generate reliable results accurately and quickly. In the last decade, as more powerful computers (both in software and hardware) and significant amounts of data become available, several breakthroughs in CML happened, including but not limited to AlexNet for image classifications, Gated Recurrent Unit for sequential predictions, BERT/transformer for natural language processing. However, there are natural limitations for CML that quantum machine. Thus, computer scientists turned their attention to quantum machine learning (QML), a new field that utilizes quantum properties to produce less time-consuming results while maintaining accuracy.


classical machine learning (CML); quantum machine learning (QML); Challenges; prospects

Cite This Paper

Tianle Yan. Quantum Machine Learning: Past, Present, and Future. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 12: 125-131. https://doi.org/10.25236/AJCIS.2023.061214.


[1] Najafi, K., Yelin, S. F., & Gao, X. (2022). The Development of Quantum Machine Learning. Harvard Data Science Review, 4(1). https://doi.org/10.1162/99608f92.5a9fd72c

[2] Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., & Lloyd, S. (2018, May 10). Quantum Machine Learning. arXiv.org. https://arxiv.org/abs/1611.09347 

[3] Meyer, N., Ufrecht, C., Periyasamy, M., Scherer, D., Plinge, A., & Mutschler, C. (2022, Nov 8). A survey on quantum reinforcement learning - arxiv.org. (n.d.). https://arxiv.org/pdf/2211.03464.pdf 

[4] Huang, HY., Broughton, M., Mohseni, M. et al. Power of data in quantum machine learning. Nat Commun 12, 2631 (2021). https://doi.org/10.1038/s41467-021-22539-9

[5] Remanan, S. Beginner’s Guide to Quantum Machine Learning. Paperspace Blog. (2021, April 9). https://blog.paperspace.com/beginners-guide-to-quantum-machine-learning/#:~:text=Here%2C%20a%20qubit%20acts%20as,any%20classical%20machine%20learning%20algorithm 

[6] Huang, H., Broughton, M., Cotler, J., Chen, S., Li, J., Mohseni, M., Neven, H., Babbush, R., Kueng, R., Preskill, J. & McClean J. (2021, Dec 3). Quantum Advantage in learning from experiments. https://doi.org/10.48550/arXiv.2112.00778

[7] Tychola, K.A.; Kalampokas, T.; Papakostas, G.A. Quantum Machine Learning—An Overview. Electronics 2023, 12, 2379. https://doi.org/10.3390/electronics12112379

[8] Zeguendry, A.; Jarir, Z.; Quafafou, M. Quantum Machine Learning: A Review and Case Studies. Entropy 2023, 25, 287. https://doi.org/10.3390/e25020287