ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 5. Vol. 28. 2022

DOI: 10.17587/it.28.250-262

K. Yu. Safronov, Postgraduate Student, Bashkir State Pedagogical University named Akmullah, Ufa, Russian Federation

Quantum Neural Networks in Machine Learning: Problems and Prospects

Despite rapid theoretical and practical progress, machine learning algorithms require large computational resources. However, new opportunities are opening up due to the advent of quantum computing devices that directly use the laws of quantum mechanics to bypass the technological and thermodynamic limitations of classical computing. Taking into account that artificial neural networks are actively used in solving a number of practical problems, with the advent of quantum computing technologies, the development of quantum neural networks for the implementation of quantum machine learning is very relevant. The article considers a quantum analogue of classical neurons that form quantum neural networks capable of performing universal quantum computations.
Keywords: quantum neural network, machine learning, quantum computing, numerical methods, mathematical model, quantum physics

P. 250–262

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