article Open AccessTop 1% cited

Machine Learning in High Energy Physics Community White Paper

Journal of Physics Conference Series · 2018 · Vol. 1085 · pp. 022008–022008

Kim Albertsson✉(Luleå University of Technology)Piero Altoè(Nvidia (United Kingdom))Dustin Anderson(California Institute of Technology)Michael Benjamin Andrews(Carnegie Mellon University)Juan Pedro Araque Espinosa(LIP - Laboratory of Instrumentation and Experimental Particle Physics)A. Aurisano(University of Cincinnati)L. Basara(Istituto Nazionale di Fisica Nucleare, Sezione di Padova)A. J. Bevan(Universidad de Londres)Wahid Bhimji(Lawrence Berkeley National Laboratory)Daniele Bonacorsi(Istituto Nazionale di Fisica Nucleare, Sezione di Bologna)P. Calafiura(Lawrence Berkeley National Laboratory)M. Campanelli(Universidad de Londres)Louis Capps(Nvidia (United Kingdom))Federico Carminati(European Organization for Nuclear Research)Stefano Carrazza(European Organization for Nuclear Research)J. T. Childers(Argonne National Laboratory)Elias ConiavitisKyle Cranmer(New York University)Claire David(Deutsches Elektronen-Synchrotron DESY)Douglas Davis(Duke University)J. Duarte(Fermi National Accelerator Laboratory)M. Erdmann(RWTH Aachen University)Jonas Nathanael Eschle(University of Zurich)A. Farbin(The University of Texas at Arlington)M. Feickert(Southern Methodist University)N. F. Castro(LIP - Laboratory of Instrumentation and Experimental Particle Physics)C. Fitzpatrick(École Polytechnique Fédérale de Lausanne)M. Floris(European Organization for Nuclear Research)Alessandra Forti(University of Manchester)J. Garra-Tico(University of Cambridge)Jochen Gemmler(Karlsruhe Institute of Technology)Maria Girone(European Organization for Nuclear Research)P. C. F. Glaysher(Deutsches Elektronen-Synchrotron DESY)Sergei Gleyzer(University of Florida)V. V. Gligorov(Centre National de la Recherche Scientifique)T. Golling(University of Geneva)Jonas Graw(Nvidia (United Kingdom))L. Gray(Fermi National Accelerator Laboratory)Dick Greenwood(Louisiana Tech University)Thomas J. Hacker(Purdue University West Lafayette)J. Harvey(European Organization for Nuclear Research)Benedikt Hegner(European Organization for Nuclear Research)Lukas Heinrich(New York University)Ben Hooberman(University of Illinois Urbana-Champaign)Johannes Junggeburth(Max Planck Institute for Physics)M. Kagan(SLAC National Accelerator Laboratory)Meghan KaneK. Kanishchev(Istituto Nazionale di Fisica Nucleare, Sezione di Padova)Przemysław Karpiński(European Organization for Nuclear Research)Zahari Kassabov(University of Milan)Gautam Kaul(Intel (United Kingdom))D. Kçira(California Institute of Technology)Thomas M. Keck(Karlsruhe Institute of Technology)A. Klimentov(Brookhaven National Laboratory)Jim Kowalkowski(Fermi National Accelerator Laboratory)Luke Kreczko(University of Bristol)A. Kurepin(Russian Academy of Sciences)Rob Kutschke(Fermi National Accelerator Laboratory)В. Е. Кузнецов(Cornell University)N. M. Köhler(Max Planck Institute for Physics)I. Lakomov(European Organization for Nuclear Research)K. Lannon(University of Notre Dame)M. Lassnig(European Organization for Nuclear Research)A. Limosani(The University of Melbourne)Gilles Louppe(New York University)Aashrita Mangu(University of California, Berkeley)Pere Mato(European Organization for Nuclear Research)H. Meinhard(European Organization for Nuclear Research)D. MenasceL. Moneta(European Organization for Nuclear Research)S. Moortgat(Vrije Universiteit Brussel)M. Narain(John Brown University)M. S. Neubauer(University of Illinois Urbana-Champaign)H. B. Newman(California Institute of Technology)Hans Pabst(Intel (United Kingdom))Michela Paganini(Yale University)M. Paulini(Carnegie Mellon University)Gabriel Perdue(Fermi National Accelerator Laboratory)Uzziel Perez(University of Alabama)Attilio PicazioJ. Pivarski(Princeton University)H. Prosper(Florida State University)Fernanda Psihas(Indiana University)Alexander Radovic(William & Mary)Ryan Reece(University of California, Santa Cruz)Aurelius Rinkevicius(Cornell University)E. Rodrigues(University of Cincinnati)Jamal Rorie(Rice University)D. Rousseau(Université Paris-Sud)Aaron Sauers(Fermi National Accelerator Laboratory)S. Schramm(University of Geneva)Ariel Schwartzman(SLAC National Accelerator Laboratory)H. Severini(University of Oklahoma)P. Seyfert(European Organization for Nuclear Research)Filip Siroký(Masaryk University)Konstantin Skazytkin(Russian Academy of Sciences)Mike Sokoloff(University of Cincinnati)G. A. Stewart(University of Glasgow)Bob Stienen(Radboud University Nijmegen)I. E. Stockdale(Altair Engineering (United States))G. Strong(LIP - Laboratory of Instrumentation and Experimental Particle Physics)S. J. Thais(Yale University)Karen Tomko(Ohio Supercomputer Center)Eli Upfal(John Brown University)E. Usai(John Brown University)A. Ustyuzhanin(Yandex School of Data Analysis)Martin Vala(Technical University of Košice)S. Vallecorsa(Gangneung–Wonju National University)J. Vasel(Indiana University)Mauro Verzetti(University of Rochester)Xavier Vilasís-Cardona(Universitat de Barcelona)Jean-Roch Vlimant(California Institute of Technology)I. Vukotić(University of Chicago)Sean-Jiun Wang(University of Florida)G. Watts(University of Washington)Michael Williams(Massachusetts Institute of Technology)Wenjing Wu(Chinese Academy of Sciences)Stefan Wünsch(Karlsruhe Institute of Technology)Omar Zapata(Universidad de Antioquia)

View via DOI Full-text PDF

Abstract

Machine learning has been applied to several problems in particle physics\nresearch, beginning with applications to high-level physics analysis in the\n1990s and 2000s, followed by an explosion of applications in particle and event\nidentification and reconstruction in the 2010s. In this document we discuss\npromising future research and development areas for machine learning in\nparticle physics. We detail a roadmap for their implementation, software and\nhardware resource requirements, collaborative initiatives with the data science\ncommunity, academia and industry, and training the particle physics community\nin data science. The main objective of the document is to connect and motivate\nthese areas of research and development with the physics drivers of the\nHigh-Luminosity Large Hadron Collider and future neutrino experiments and\nidentify the resource needs for their implementation. Additionally we identify\nareas where collaboration with external communities will be of great benefit.\n

Particle physics theoretical and experimental studies Particle Detector Development and Performance Neutrino Physics ResearchResource (disambiguation)NeutrinoParticle physicsWhite paperPhysics educationParticle identificationEvent (particle physics)Event reconstructionIdentification (biology)Large Hadron Collider

Citations

224

FWCI

37.75

field-weighted impact

References

Percentile

100%

vs. same field & year

Citations per year

References

Greedy function approximation: A gradient boosting machine.