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Journal Article

Artificial Intelligence and Machine Learning for Quantum Technologies

MPS-Authors
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Krenn,  Mario
Krenn Research Group, Marquardt Division, Max Planck Institute for the Science of Light, Max Planck Society;

Landgraf,  Jonas
Marquardt Division, Max Planck Institute for the Science of Light, Max Planck Society;
Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg;

/persons/resource/persons216883

Fösel,  Thomas
Marquardt Division, Max Planck Institute for the Science of Light, Max Planck Society;
Department of Physics, Friedrich-Alexander Universität Erlangen-Nürnberg;

/persons/resource/persons201125

Marquardt,  Florian
Marquardt Division, Max Planck Institute for the Science of Light, Max Planck Society;

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artificial_intelligence.pdf
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(Supplementary material), 21KB

Citation

Krenn, M., Landgraf, J., Fösel, T., & Marquardt, F. (2023). Artificial Intelligence and Machine Learning for Quantum Technologies. Physical Review A, (107): 010101. doi:10.1103/PhysRevA.107.010101.


Cite as: https://hdl.handle.net/21.11116/0000-000A-D622-E
Abstract
In recent years the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more broadly methods of artificial intelligence to analyze quantum measurements, estimate the parameters of quantum devices, discover new quantum experimental setups, protocols, and feed- back strategies, and generally improve aspects of quantum computing, quantum communication, and quantum simulation. We highlight open challenges and future possibilities and conclude with some speculative visions for the next decade.