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Quantum machine learning for chemistry and physics

Journal Article · Mon Aug 01 00:00:00 EDT 2022 · Chemical Society Reviews

DOI:https://doi.org/10.1039/D2CS00203E· OSTI ID:1876644

^[1]; ^[2]; Selvarajan, Raja ^[2]; ^[3]; ^[1]; Gupta, Rishabh ^[1]; Singh, Vinit ^[1]; ^[4]

Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA, Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA
Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA, Department of Physics and Astronomy, Purdue University, West Lafayette, IN-47907, USA
Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA, Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN-47907, USA
Department of Chemistry, Purdue University, West Lafayette, IN-47907, USA, Purdue Quantum Science and Engineering Institute, Purdue University, West Lafayette, Indiana 47907, USA, Department of Physics and Astronomy, Purdue University, West Lafayette, IN-47907, USA, Elmore Family School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN-47907, USA

Quantum variants of machine learning algorithms are discussed with emphasis on methodology, learning techniques and applications in broad and distinct domains of chemical physics.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: NONE; SC0019215

OSTI ID:: 1876644

Alternate ID(s):: OSTI ID: 1978876

Journal Information:: Chemical Society Reviews, Journal Name: Chemical Society Reviews Journal Issue: 15 Vol. 51; ISSN 0306-0012; ISSN CSRVBR

Publisher:: Royal Society of Chemistry (RSC)Copyright Statement

Country of Publication:: United Kingdom

Language:: English

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