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Since the discovery of the Higgs boson, testing the many possible extensions to the Standard Model has become a key challenge in particle physics. This paper discusses a new method for predicting the compatibility of new physics theories…

High Energy Physics - Phenomenology · Physics 2022-07-20 Juan Rocamonde , Louie Corpe , Gustavs Zilgalvis , Maria Avramidou , Jon Butterworth

Before any publication, data analysis of high-energy physics experiments must be validated. This validation is granted only if a perfect understanding of the data and the analysis process is demonstrated. Therefore, physicists prefer using…

Machine Learning · Computer Science 2019-12-18 Noëlie Cherrier , Maxime Defurne , Jean-Philippe Poli , Franck Sabatié

The rapidly-developing intersection of machine learning (ML) with high-energy physics (HEP) presents both opportunities and challenges to our community. Far beyond applications of standard ML tools to HEP problems, genuinely new and…

Computational Physics · Physics 2022-09-19 Phiala Shanahan , Kazuhiro Terao , Daniel Whiteson

The discovery of the Higgs together with the excellent performance of the LHC allow to make precision tests of Brout-Englert-Higgs Physics, and especially its underlying field-theory. In this field theory strict gauge-invariance requires…

High Energy Physics - Phenomenology · Physics 2017-11-07 Axel Maas , Larissa Egger

We provide a prescription to train optimal machine-learning-based event selectors and categorizers that maximize the statistical significance of a potential signal excess in high energy physics (HEP) experiments, as quantified by any of six…

Data Analysis, Statistics and Probability · Physics 2019-11-28 Konstantin K. Matchev , Prasanth Shyamsundar

Top quark physics continues to be an exciting and fast moving research area. The large statistics provided by the LHC are allowing us to measure processes never observed before and to develop new methods to improve the precision for the…

High Energy Physics - Experiment · Physics 2019-02-01 Mark Owen

Physics-Informed Neural Networks (PINNs) have been widely used to obtain solutions to various physical phenomena modeled as Differential Equations. As PINNs are not naturally equipped with mechanisms for Uncertainty Quantification, some…

Machine Learning · Computer Science 2025-06-05 Pablo Flores , Olga Graf , Pavlos Protopapas , Karim Pichara

We study uncertainties of the predicted inclusive Higgs production cross section due to the uncertainties of parton distribution functions (PDF). Particular attention is given to bbH Yukawa coupling enhanced production mechanisms in beyond…

High Energy Physics - Phenomenology · Physics 2009-11-11 Alexander Belyaev , Jon Pumplin , Wu-Ki Tung , C. --P. Yuan

Determining the form of the Higgs potential is one of the most exciting challenges of modern particle physics. Higgs pair production directly probes the Higgs self-coupling and should be observed in the near future at the High-Luminosity…

High Energy Physics - Phenomenology · Physics 2024-11-15 Radha Mastandrea , Benjamin Nachman , Tilman Plehn

Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals. The study of neutrinos typically requires overcoming large backgrounds,…

Computational Physics · Physics 2020-12-30 Fernanda Psihas , Micah Groh , Christopher Tunnell , Karl Warburton

Precise measurements of SM particles properties at the LHC allows to look for heavy New Physics in the context of an Effective Field Theory (EFT). These searches, however, often rely on kinematic regions where the validity of the EFT may be…

High Energy Physics - Phenomenology · Physics 2015-09-16 Martin Gorbahn , Jose Miguel No , Veronica Sanz

Compelling arguments suggest the presence of new physics at energy scales that will be probed by frontier energy colliders over the next decade. Arguments for each of the many flavors of new physics that have been proposed seem much less…

High Energy Physics - Experiment · Physics 2014-11-17 Bruce Knuteson

Machine learning bias in mental health is becoming an increasingly pertinent challenge. Despite promising efforts indicating that multitask approaches often work better than unitask approaches, there is minimal work investigating the impact…

Machine Learning · Computer Science 2025-03-25 Jiaee Cheong , Aditya Bangar , Sinan Kalkan , Hatice Gunes

The discovery of the Higgs boson in 2012, by the ATLAS and CMS experiments, was a success achieved with only a percent of the entire dataset foreseen for the LHC. It opened a landscape of possibilities in the study of Higgs boson…

High Energy Physics - Phenomenology · Physics 2019-03-20 M. Cepeda , S. Gori , P. Ilten , M. Kado , F. Riva , R. Abdul Khalek , A. Aboubrahim , J. Alimena , S. Alioli , A. Alves , C. Asawatangtrakuldee , A. Azatov , P. Azzi , S. Bailey , S. Banerjee , E. L. Barberio , D. Barducci , G. Barone , M. Bauer , C. Bautista , P. Bechtle , K. Becker , A. Benaglia , M. Bengala , N. Berger , C. Bertella , A. Bethani , A. Betti , A. Biekotter , F. Bishara , D. Bloch , P. Bokan , O. Bondu , M. Bonvini , L. Borgonovi , M. Borsato , S. Boselli , S. Braibant-Giacomelli , G. Buchalla , L. Cadamuro , C. Caillol , A. Calandri , A. Calderon Tazon , J. M. Campbell , F. Caola , M. Capozi , M. Carena , C. M. Carloni Calame , A. Carmona , E. Carquin , A. Carvalho Antunes De Oliveira , A. Castaneda Hernandez , O. Cata , A. Celis , A. Cerri , F. Cerutti , G. S. Chahal , A. Chakraborty , G. Chaudhary , X. Chen , A. S. Chisholm , R. Contino , A. J. Costa , R. Covarelli , N. Craig , D. Curtin , L. D'Eramo , N. P. Dang , P. Das , S. Dawson , O. A. De Aguiar Francisco , J. de Blas , S. De Curtis , N. De Filippis , H. De la Torre , L. de Lima , A. De Wit , C. Delaere , M. Delcourt , M. Delmastro , S. Demers , N. Dev , R. Di Nardo , S. Di Vita , S. Dildick , L. A. F. do Prado , M. Donadelli , D. Du , G. Durieux , M. Dührssen , O. Eberhardt , K. El Morabit , J. Elias-Miro , J. Ellis , C. Englert , R. Essig , S. Falke , M. Farina , A. Ferrari , A. Ferroglia , M. C. N. Fiolhais , M. Flechl , S. Folgueras , E. Fontanesi , P. Francavilla , R. Franceschini , R. Frederix , S. Frixione , G. Gómez-Ceballos , A. Gabrielli , S. Gadatsch , M. Gallinaro , A. Gandrakota , J. Gao , F. M. Garay Walls , T. Gehrmann , Y. Gershtein , T. Ghosh , A. Gilbert , R. Glein , E. W. N. Glover , R. Gomez-Ambrosio , R. Gonçalo , D. Gonçalves , M. Gorbahn , E. Gouveia , M. Gouzevitch , P. Govoni , M. Grazzini , B. Greenberg , K. Grimm , A. V. Gritsan , A. Grohsjean , C. Grojean , J. Gu , R. Gugel , R. S. Gupta , C. B. Gwilliam , S. Höche , M. Haacke , Y. Haddad , U. Haisch , G. N. Hamity , T. Han , L. A. Harland-Lang , R. Harnik , S. Heinemeyer , G. Heinrich , B. Henning , V. Hirschi , K. Hoepfner , J. M. Hogan , S. Homiller , Y. Huang , A. Huss , S. Jézéquel , Sa. Jain , S. P. Jones , K. Köneke , J. Kalinowski , J. F. Kamenik , M. Kaplan , A. Karlberg , M. Kaur , P. Keicher , M. Kerner , A. Khanov , J. Kieseler , J. H. Kim , M. Kim , T. Klijnsma , F. Kling , M. Klute , J. R. Komaragiri , K. Kong , J. Kozaczuk , P Kozow , C. Krause , S. Lai , J. Langford , B. Le , L. Lechner , W. A. Leight , K. J. C. Leney , T. Lenz , C-Q. Li , H. Li , Q. Li , S. Liebler , J. Lindert , D. Liu , J. Liu , Y. Liu , Z. Liu , D. Lombardo , A. Long , K. Long , I. Low , G. Luisoni , L. L. Ma , A. -M. Magnan , D. Majumder , A. Malinauskas , F. Maltoni , M. L. Mangano , G. Marchiori , A. C. Marini , A. Martin , S. Marzani , A. Massironi , K. T. Matchev , R. D. Matheus , K. Mazumdar , J. Mazzitelli , A. E. Mcdougall , P. Meade , P. Meridiani , A. B. Meyer , E. Michielin , P. Milenovic , V. Milosevic , K. Mimasu , B. Mistlberger , M. Mlynarikova , M. Mondragon , P. F. Monni , G. Montagna , F. Monti , M. Moreno Llacer , A. Mueck , P. C. Muiño , C. Murphy , W. J. Murray , P. Musella , M. Narain , R. F. Naranjo Garcia , P. Nath , M. Neubert , O. Nicrosini , K. Nikolopoulos , A. Nisati , J. M. No , M. L. Ojeda , S. A. Olivares Pino , A. Onofre , G. Ortona , S. Pagan Griso , D. Pagani , E. Palencia Cortezon , C. Palmer , C. Pandini , G. Panico , L. Panwar , D. Pappadopulo , M. Park , R. Patel , F. Paucar-Velasquez , K. Pedro , L. Pernie , L. Perrozzi , B. A. Petersen , E. Petit , G. Petrucciani , G. Piacquadio , F. Piccinini , M. Pieri , T. Plehn , S. Pokorski , A. Pomarol , E. Ponton , S. Pozzorini , S. Prestel , K. Prokofiev , M. Ramsey-Musolf , E. Re , N. P. Readioff , D. Redigolo , L. Reina , E. Reynolds , M. Riembau , F. Rikkert , T. Robens , R. Roentsch , J. Rojo , N. Rompotis , J. Rorie , J. Rosiek , J. Roskes , J. T. Ruderman , N. Sahoo , S. Saito , R. Salerno , P. H. Sales De Bruin , A. Salvucci , K. Sandeep , J. Santiago , R. Santo , V. Sanz , U. Sarica , A. Savin , A. Savoy-Navarro , S. Sawant , A. C. Schaffer , M. Schlaffer , A. Schmidt , B. Schneider , R. Schoefbeck , M. Schröder , M. Scodeggio , E. Scott , L. Scyboz , M. Selvaggi , L. Sestini , H. -S. Shao , A. Shivaji , L. Silvestrini , L. Simon , K. Sinha , Y. Soreq , M. Spannowsky , M. Spira , D. Spitzbart , E. Stamou , J. Stark , T. Stefaniak , B. Stieger , G. Strong , M. Szleper , K. Tackmann , M. Takeuchi , S. Taroni , M. Testa , A. Thamm , V. Theeuwes , L. A. Thomsen , S. Tkaczyk , R. Torre , F. Tramontano , K. A. Ulmer , T. Vantalon , L. Vecchi , R. Vega-Morales , E. Venturini , M. Verducci , C. Vernieri , T. Vickey , M. Vidal Marono , P. Vischia , E. Vryonidou , P. Wagner , V. M. Walbrecht , L. -T. Wang , N. Wardle , D. R. Wardrope , G. Weiglein , S. Wertz , M. Wielers , J. M. Williams , R. Wolf , A. Wulzer , M. Xiao , H. T. Yang , E. Yazgan , Z. Yin , T. You , F. Yu , G. Zanderighi , D. Zanzi , M. Zaro , S. C. Zenz , D. Zerwas , M. Zgubič , J. Zhang , L. Zhang , W. Zhang , X. Zhao , Y. -M. Zhong

The completion of Run 1 of the CERN Large Hadron Collider has seen the discovery of the Higgs boson and an unprecedented number of precise measurements of the Standard Model, while Run 2 operation has just started to provide first data at…

High Energy Physics - Experiment · Physics 2016-11-23 Pierluigi Campana , Markus Klute , Pippa Wells

To enable the reusability of massive scientific datasets by humans and machines, researchers aim to adhere to the principles of findability, accessibility, interoperability, and reusability (FAIR) for data and artificial intelligence (AI)…

There is growing interest in the issues of preservation and re-use of the records of science, in the "digital era". The aim of the PARSE.Insight project, partly financed by the European Commission under the Seventh Framework Program, is…

Digital Libraries · Computer Science 2009-06-03 Andre Holzner , Peter Igo-Kemenes , Salvatore Mele

A novel model of the data selection, acquisition and analysis for a multi-purpose and multi-component high-energy-physics experiment is presented. Its departure point is the freedom and the responsibility given to the different physics…

High Energy Physics - Experiment · Physics 2008-12-19 Mieczyslaw Witold Krasny

Measurement uncertainty plays a critical role in the process of experimental physics. It is useful to be able to assess student proficiency around the topic to iteratively improve instruction and student learning. For the topic of…

Physics Education · Physics 2023-08-23 Gayle Geschwind , Michael Vignal , H. J. Lewandowski

In this paper we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is…