Modern applications of machine learning in quantum sciences [article]

Anna Dawid, Julian Arnold, Borja Requena, Alexander Gresch, Marcin Płodzień, Kaelan Donatella, Kim A. Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil (+17 others)
2022 arXiv   pre-print
In these Lecture Notes, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learning and kernel methods in supervised, unsupervised, and reinforcement learning algorithms for phase classification, representation of many-body quantum states, quantum feedback control, and quantum circuits optimization. Moreover, we introduce and discuss more specialized topics such as differentiable
more » ... ming, generative models, statistical approach to machine learning, and quantum machine learning.
arXiv:2204.04198v2 fatcat:slojwtqwfzgbfgvz3pssdkwhtm