Quantum Neural Networks: Concepts, Applications, and Challenges
It addresses the potential for quantum computing to enhance deep learning, but it is an incremental review paper rather than presenting new research.
This paper tackles the problem of integrating quantum computing with deep neural networks by explaining the background, principles, achievements, challenges, and future directions of quantum deep learning, but it does not report specific experimental results or concrete numbers.
Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and quantum computing have been separated for long time, however by discovering that quantum circuits can act like artificial neural networks, quantum deep learning research is widely adopted. This paper explains the backgrounds and basic principles of quantum deep learning and also introduces major achievements. After that, this paper discusses the challenges of quantum deep learning research in multiple perspectives. Lastly, this paper presents various future research directions and application fields of quantum deep learning.