Machine Learning in Quantum Sciences - Hardcover

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; Rodrigo A. Vargas-Hernández; Alba Cervera-Lierta; Juan Carrasquilla; Vedran Dunjko; Marylou Gabrié; Patrick Huembeli; Evert Van Nieuwenburg; Filippo Vicentini; Lei Wang; Sebastian J. Wetzel; Giuseppe Carleo; Eliška Greplová; Roman Krems , Florian Marquardt , Michał Tomza , Maciej Lewenstein , Alexandre Dauphin

Hardcover

ISBN 10: 1009504932 ISBN 13: 9781009504935

Publisher: Cambridge University Press, 2025

Synopsis

Provides a comprehensive introduction to the key concepts of machine learning and explores its applications in the quantum sciences.

About this title

About the Authors

Anna Dawid is a research fellow at the Flatiron Institute, New York, with the Ph.D. in quantum physics awarded by the University of Warsaw and ICFO, Barcelona. Her research spans interpretable machine learning for scientific discovery, quantum simulations, and foundations of deep learning.

Alexandre Dauphin is VP quantum simulation at PASQAL, a neutral-atom quantum computing company. During his career, he has worked on a broad range of topics going from quantum simulation of many-body phases of matter to ML applied to physics and QML. He received the NJP early career award 2019, has been a member of the editorial board of NJP since 2020, and a member of ELLIS since 2021.

Julian Arnold is a theoretical physicist working at the interface between the quantum sciences, information theory, and machine learning. His research includes the design of methods for the automated detection of phase transitions and the application of differentiable programming to solve inverse design problems in quantum many-body physics.

Borja Requena develops machine learning algorithms for scientific applications. His contributions span multiple fields, from quantum to statistical and biophysics. Additionally, Borja has worked in high-tech companies such as Xanadu Quantum Technologies or Telefonica R&D, and he has been high ranked in machine learning and quantum computing competitions.

Alexander Gresch (Ph.D. Student at the universities of Düsseldorf and Hamburg) is a theoretical physicist specializing in mathematical and machine learning methods in the context of quantum technologies. This includes, in particular, the efficient and accurate read-out of hybrid quantum algorithms and the role of quantum data for machine learning.

Edition details

• Publisher: Cambridge University Press
• Publication date: 2025
• Language: English
• ISBN 10: 1009504932
• ISBN 13: 9781009504935
• Binding: Hardcover
• Number of pages: 330