TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhys.14.4.079
TI  - Machine learning and LHC event generation
PY  - 2023/04/21
UR  - https://scipost.org/SciPostPhys.14.4.079
JF  - SciPost Physics
JA  - SciPost Phys.
VL  - 14
IS  - 4
SP  - 079
A1  - Butter, Anja
AU  - Plehn, Tilman
AU  - Schumann, Steffen
AU  - Badger, Simon
AU  - Caron, Sascha
AU  - Cranmer, Kyle
AU  - Di Bello, Francesco Armando
AU  - Dreyer, Etienne
AU  - Forte, Stefano
AU  - Ganguly, Sanmay
AU  - Gonçalves, Dorival
AU  - Gross, Eilam
AU  - Heimel, Theo
AU  - Heinrich, Gudrun
AU  - Heinrich, Lukas
AU  - Held, Alexander
AU  - Höche, Stefan
AU  - Howard, Jessica N.
AU  - Ilten, Philip
AU  - Isaacson, Joshua
AU  - Janßen, Timo
AU  - Jones, Stephen
AU  - Kado, Marumi
AU  - Kagan, Michael
AU  - Kasieczka, Gregor
AU  - Kling, Felix
AU  - Kraml, Sabine
AU  - Krause, Claudius
AU  - Krauss, Frank
AU  - Kröninger, Kevin
AU  - Barman, Rahool Kumar
AU  - Luchmann, Michel
AU  - Magerya, Vitaly
AU  - Maître, Daniel
AU  - Malaescu, Bogdan
AU  - Maltoni, Fabio
AU  - Martini, Till
AU  - Mattelaer, Olivier
AU  - Nachman, Benjamin
AU  - Pitz, Sebastian
AU  - Rojo, Juan
AU  - Schwartz, Matthew
AU  - Shih, David
AU  - Siegert, Frank
AU  - Stegeman, Roy
AU  - Stienen, Bob
AU  - Thaler, Jesse
AU  - Verheyen, Rob
AU  - Whiteson, Daniel
AU  - Winterhalder, Ramon
AU  - Zupan, Jure
AB  - First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation. This review illustrates a wide range of applications of modern machine learning to event generation and simulation-based inference, including conceptional developments driven by the specific requirements of particle physics. New ideas and tools developed at the interface of particle physics and machine learning will improve the speed and precision of forward simulations, handle the complexity of collision data, and enhance inference as an inverse simulation problem.
ER  -

@Article{10.21468/SciPostPhys.14.4.079,
	title={{Machine learning and LHC event generation}},
	author={Anja Butter and Tilman Plehn and Steffen Schumann and Simon Badger and Sascha Caron and Kyle Cranmer and Francesco Armando Di Bello and Etienne Dreyer and Stefano Forte and Sanmay Ganguly and Dorival Gonçalves and Eilam Gross and Theo Heimel and Gudrun Heinrich and Lukas Heinrich and Alexander Held and Stefan Höche and Jessica N. Howard and Philip Ilten and Joshua Isaacson and Timo Janßen and Stephen Jones and Marumi Kado and Michael Kagan and Gregor Kasieczka and Felix Kling and Sabine Kraml and Claudius Krause and Frank Krauss and Kevin Kröninger and Rahool Kumar Barman and Michel Luchmann and Vitaly Magerya and Daniel Maitre and Bogdan Malaescu and Fabio Maltoni and Till Martini and Olivier Mattelaer and Benjamin Nachman and Sebastian Pitz and Juan Rojo and Matthew Schwartz and David Shih and Frank Siegert and Roy Stegeman and Bob Stienen and Jesse Thaler and Rob Verheyen and Daniel Whiteson and Ramon Winterhalder and Jure Zupan},
	journal={SciPost Phys.},
	volume={14},
	pages={079},
	year={2023},
	publisher={SciPost},
	doi={10.21468/SciPostPhys.14.4.079},
	url={https://scipost.org/10.21468/SciPostPhys.14.4.079},
}

Cited by 33

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Authors / Affiliations: mappings to Contributors and Organizations

• ^{1 2} Anja Butter,
• ² Tilman Plehn,
• ³ Steffen Schumann,
• ⁴ Simon Badger,
• ^{5 6} Sascha Caron,
• ⁷ Kyle Cranmer,
• ⁸ Francesco Armando Di Bello,
• ⁹ Etienne Dreyer,
• ¹⁰ Stefano Forte,
• ¹¹ Sanmay Ganguly,
• ¹² Dorival Gonçalves,
• ⁹ Eilam Gross,
• ² Theo Heimel,
• ¹³ Gudrun Heinrich,
• ¹⁴ Lukas Heinrich,
• ⁷ Alexander Held,
• ¹⁵ Stefan Höche,
• ¹⁶ Jessica N. Howard,
• ¹⁷ Philip Ilten,
• ¹⁵ Joshua Isaacson,
• ³ Timo Janßen,
• ¹⁸ Stephen Jones,
• ^{8 19} Marumi Kado,
• ²⁰ Michael Kagan,
• ²¹ Gregor Kasieczka,
• ²² Felix Kling,
• ²³ Sabine Kraml,
• ²⁴ Claudius Krause,
• ¹⁸ Frank Krauss,
• ²⁵ Kevin Kröninger,
• ¹² Rahool Kumar Barman,
• ² Michel Luchmann,
• ¹³ Vitaly Magerya,
• ¹⁸ Daniel Maître,
• ¹ Bogdan Malaescu,
• ^{26 27} Fabio Maltoni,
• ²⁸ Till Martini,
• ²⁶ Olivier Mattelaer,
• ^{29 30} Benjamin Nachman,
• ² Sebastian Pitz,
• ^{6 31} Juan Rojo,
• ³² Matthew Schwartz,
• ²³ David Shih,
• ³³ Frank Siegert,
• ¹⁰ Roy Stegeman,
• ⁵ Bob Stienen,
• ³⁴ Jesse Thaler,
• ³⁵ Rob Verheyen,
• ¹⁶ Daniel Whiteson,
• ²⁶ Ramon Winterhalder,
• ¹⁷ Jure Zupan

• ¹ Sorbonne Université / Sorbonne University
• ² Heidelberger Institut für Theoretische Studien / Heidelberg Institute for Theoretical Studies [HITS]
• ³ Georg-August-Universität Göttingen / University of Göttingen [GAU]
• ⁴ Università degli Studi di Torino / University of Turin [UNITO]
• ⁵ Radboud Universiteit Nijmegen / Radboud University Nijmegen [RUN]
• ⁶ Nationaal instituut voor Subatomaire Fysica / National Institute for Subatomic Physics [NIKHEF]
• ⁷ New York University [NYU]
• ⁸ Sapienza – Università di Roma / Sapienza University of Rome
• ⁹ Weizmann Institute of Science
• ¹⁰ Università degli Studi di Milano / University of Milan [UNIMI]
• ¹¹ 東京大学 / University of Tokyo [UT]
• ¹² Oklahoma State University [OSU]
• ¹³ Karlsruher Institut für Technologie / Karlsruhe Institute of Technology [KIT]
• ¹⁴ Technische Universität München / Technical University of Munich [TUM]
• ¹⁵ Fermi National Accelerator Laboratory [Fermilab]
• ¹⁶ University of California, Irvine [UCI]
• ¹⁷ University of Cincinnati [UC]
• ¹⁸ Durham University
• ¹⁹ Université Paris-Saclay / University of Paris-Saclay
• ²⁰ SLAC National Accelerator Laboratory [SLAC]
• ²¹ Universität Hamburg / University of Hamburg [UH]
• ²² Deutsches Elektronen-Synchrotron / Deutsche Elektronen-Synchrotron DESY [DESY]
• ²³ Centre National de la Recherche Scientifique / French National Centre for Scientific Research [CNRS]
• ²⁴ Rutgers University [RU]
• ²⁵ Technische Universität Dortmund / TU Dortmund University [TU Dortmund]
• ²⁶ Université catholique de Louvain [UCL]
• ²⁷ Università di Bologna / University of Bologna [UNIBO]
• ²⁸ Humboldt-Universität zu Berlin / Humboldt University of Berlin [HU]
• ²⁹ Lawrence Berkeley National Laboratory [LBNL]
• ³⁰ University of California, Berkeley [UCBL]
• ³¹ Vrije Universiteit Amsterdam / VU University Amsterdam [VU]
• ³² Harvard University
• ³³ Technische Universität Dresden / Dresden University of Technology [TUD]
• ³⁴ Massachusetts Institute of Technology [MIT]
• ³⁵ University College London [UCL]