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1.
Quantum Machine Learning in High Energy Physics / Guan, Wen (Wisconsin U., Madison) ; Perdue, Gabriel (Fermilab) ; Pesah, Arthur (Denmark, Tech. U.) ; Schuld, Maria (KwaZulu Natal U.) ; Terashi, Koji (Tokyo U., ICEPP) ; Vallecorsa, Sofia (CERN) ; Vlimant, Jean-Roch (Caltech)
Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early 1980s as way to perform computations that would not be tractable with a classical computer. [...]
arXiv:2005.08582; FERMILAB-PUB-20-184-QIS.- 2021 - 25 p. - Published in : Mach. Learn. Sci. Tech. 2 (2021) 011003 Fulltext: 2005.08582 - PDF; b1da2989be2d655c50926006379da448 - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server
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2.
Software and Computing for Small HEP Experiments / FASER Collaboration
This white paper briefly summarized key conclusions of the recent US Community Study on the Future of Particle Physics (Snowmass 2021) workshop on Software and Computing for Small High Energy Physics Experiments..
arXiv:2203.07645 ; FERMILAB-CONF-22-138. - 11.
Fermilab Library Server - eConf - Fulltext - Fulltext
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3.
Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors / Exa.TrkX Collaboration
Pattern recognition problems in high energy physics are notably different from traditional machine learning applications in computer vision. [...]
arXiv:2003.11603 ; FERMILAB-CONF-20-163-PPD-QIS-SCD. - 6 p.
Fermilab Library Server (fulltext available) - Fulltext - Fulltext
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4.
Machine Learning in High Energy Physics Community White Paper / Albertsson, Kim (Lulea U.) ; Altoe, Piero (NVIDIA, Santa Clara) ; Anderson, Dustin (Caltech) ; Anderson, John ; Andrews, Michael (Carnegie Mellon U.) ; Araque Espinosa, Juan Pedro (LIP, Lisbon) ; Aurisano, Adam (Cincinnati U.) ; Basara, Laurent (INFN, Padua ; Padua U.) ; Bevan, Adrian (University Coll. London) ; Bhimji, Wahid (LBL, Berkeley) et al.
Machine learning has been applied to several problems in particle physics research, beginning with applications to high-level physics analysis in the 1990s and 2000s, followed by an explosion of applications in particle and event identification and reconstruction in the 2010s. In this document we discuss promising future research and development areas for machine learning in particle physics. [...]
arXiv:1807.02876; FERMILAB-PUB-18-318-CD-DI-PPD.- 2018-10-18 - 27 p. - Published in : J. Phys.: Conf. Ser. 1085 (2018) 022008 Fulltext: 1807.02876 - PDF; Albertsson_2018_J._Phys.__Conf._Ser._1085_022008 - PDF; fulltext1681439 - PDF; fermilab-pub-18-318-cd-di-ppd - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server (fulltext available)
In : 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, Seattle, WA, USA, 21 - 25 Aug 2017, pp.022008
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5.
A Roadmap for HEP Software and Computing R&D for the 2020s / HEP Software Foundation Collaboration
Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. [...]
arXiv:1712.06982; HSF-CWP-2017-01; HSF-CWP-2017-001; FERMILAB-PUB-17-607-CD.- 2019-03-20 - 49 p. - Published in : Comput. Softw. Big Sci. 3 (2019) 7 Fulltext: 1712.06982 - PDF; fermilab-pub-17-607-cd - PDF; Fulltext from Publisher: PDF; Preprint: PDF; External link: Fermilab Library Server (fulltext available)
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6.
A Software Toolkit to Study Systematic Uncertainties of the Physics Models of the Geant4 Simulation Package / Genser, Krzysztof (Fermilab) ; Hatcher, Robert (Fermilab) ; Perdue, Gabriel (Fermilab) ; Wenzel, Hans (Fermilab) ; Yarba, Julia (Fermilab) ; Kelsey, Michael (SLAC) ; Wright, Dennis H (SLAC) /Geant4
The Geant4 toolkit is used to model interactions between particles and matter. Geant4 employs a set of validated physics models that span a wide range of interaction energies. [...]
FERMILAB-CONF-16-526-CD.- SISSA, 2016 - 4 p. - Published in : PoS ICHEP2016 (2016) 878 Fulltext: fermilab-conf-16-526-cd - PDF; PoS(ICHEP2016)878 - PDF; External link: FERMILABCONF
In : 38th International Conference on High Energy Physics, Chicago, IL, USA, 03 - 10 Aug 2016, pp.878
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