Colloquium: Machine learning in nuclear physics

Amber Boehnlein, Markus Diefenthaler, Nobuo Sato, Malachi Schram, Veronique Ziegler, Cristiano Fanelli, Morten Hjorth-Jensen, Tanja Horn, Michelle P. Kuchera, Dean Lee, Witold Nazarewicz, Peter Ostroumov, Kostas Orginos, Alan Poon, Xin-Nian Wang, Alexander Scheinker, Michael S. Smith, and Long-Gang Pang
Rev. Mod. Phys. 94, 031003 – Published 8 September 2022

Abstract

Advances in machine learning methods provide tools that have broad applicability in scientific research. These techniques are being applied across the diversity of nuclear physics research topics, leading to advances that will facilitate scientific discoveries and societal applications. This Colloquium provides a snapshot of nuclear physics research, which has been transformed by machine learning techniques.

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  • Received 19 January 2022

DOI:https://doi.org/10.1103/RevModPhys.94.031003

© 2022 American Physical Society

Physics Subject Headings (PhySH)

  1. Research Areas
Nuclear Physics

Authors & Affiliations

Amber Boehnlein, Markus Diefenthaler, Nobuo Sato, Malachi Schram, and Veronique Ziegler

  • Thomas Jefferson National Accelerator Facility, 12000 Jefferson Avenue, Newport News, Virginia 23606, USA

Cristiano Fanelli

  • Laboratory for Nuclear Science and Institute for Artificial Intelligence and Fundamental Interactions, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA

Morten Hjorth-Jensen

  • Facility for Rare Isotope Beams and Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA and Department of Physics and Center for Computing in Science Education, University of Oslo, N-0316 Oslo, Norway

Tanja Horn

  • Department of Physics, The Catholic University of America, Washington, D.C. 20064, USA and Thomas Jefferson National Accelerator Facility, 12000 Jefferson Avenue, Newport News, Virginia 23606, USA

Michelle P. Kuchera

  • Department of Physics and Department of Mathematics and Computer Science, Davidson College, Davidson, North Carolina 28035, USA

Dean Lee, Witold Nazarewicz, and Peter Ostroumov

  • Facility for Rare Isotope Beams and Department of Physics and Astronomy, Michigan State University, East Lansing, Michigan 48824, USA

Kostas Orginos

  • Department of Physics, William & Mary, Williamsburg 23185, Virginia, USA and Thomas Jefferson National Accelerator Facility, 12000 Jefferson Avenue, Newport News, Virginia 23606, USA

Alan Poon and Xin-Nian Wang

  • Nuclear Science Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA

Alexander Scheinker

  • Accelerator Operations and Technology Division Applied Electrodynamics Group, Los Alamos National Laboratory, Los Alamos, New Mexico 87544, USA

Michael S. Smith

  • Physics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, 37831-6354, USA

Long-Gang Pang

  • Key Laboratory of Quark and Lepton Physics, Institute of Particle Physics, Central China Normal University, Wuhan 430079, China

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Issue

Vol. 94, Iss. 3 — July - September 2022

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