Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8701
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dc.contributor.authorAad G.-
dc.contributor.authorAbbott B.-
dc.contributor.authorAbbott D.C.-
dc.contributor.authorAbud A.A.-
dc.contributor.authorAbeling K.-
dc.contributor.authorAbhayasinghe D.K.-
dc.contributor.authorAbidi S.H.-
dc.date.accessioned2022-07-30T16:45:52Z-
dc.date.available2022-07-30T16:45:52Z-
dc.date.issued2022-
dc.identifier.citationAad, G., Abbott, B., Abbott, D. C., Abud, A. A., Abeling, K., Abhayasinghe, D. K., ... & Balasubramanian, R. (2022). AtlFast3: the next generation of fast simulation in ATLAS. Computing and Software for Big Science, 6(1), 1-54.en_US
dc.identifier.issn2510-2044-
dc.identifier.urihttps://doi.org/10.1007/s41781-021-00079-7-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/8701-
dc.description.abstractThe ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes. © 2022, Springer Nature Switzerland AG.en_US
dc.description.sponsorshipIN2P3-CNRS; National Science Foundation, NSF; U.S. Department of Energy, USDOE; Alexander von Humboldt-Stiftung, AvH; Canarie; H2020 Marie Sk?odowska-Curie Actions, MSCA; Arizona-Nevada Academy of Science, ANAS; CERN; Compute Canada; Göran Gustafssons Stiftelser; Natural Sciences and Engineering Research Council of Canada, NSERC; National Research Council Canada, NRC; Canada Foundation for Innovation, CFI; Leverhulme Trust; Royal Society; European Research Council, ERC; European Cooperation in Science and Technology, COST; Australian Research Council, ARC; Neurosurgical Research Foundation, NRF; Singapore Eye Research Institute, SERI; Helmholtz-Gemeinschaft, HGF; Deutsche Forschungsgemeinschaft, DFG; Agence Nationale de la Recherche, ANR; Japan Society for the Promotion of Science, KAKEN; Ministry of Education, Culture, Sports, Science and Technology, MEXT; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, SNF; Danmarks Grundforskningsfond, DNRF; Fundação de Amparo à Pesquisa do Estado de São Paulo, FAPESP; National Natural Science Foundation of China, NSFC; Fundação para a Ciência e a Tecnologia, FCT; Bundesministerium für Bildung und Forschung, BMBF; Chinese Academy of Sciences, CAS; Austrian Science Fund, FWF; Generalitat de Catalunya; Agencia Nacional de Promoción Científica y Tecnológica, ANPCyT; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, NWO; Bundesministerium für Wissenschaft, Forschung und Wirtschaft, BMWFW; Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Joint Institute for Nuclear Research, JINR; Nella and Leon Benoziyo Center for Neurological Diseases, Weizmann Institute of Science; Israel Science Foundation, ISF; Instituto Nazionale di Fisica Nucleare, INFN; Narodowe Centrum Nauki, NCN; Javna Agencija za Raziskovalno Dejavnost RS, ARRS; Ministerstwo Edukacji i Nauki, MNiSW; Ministry of Science and Technology, Taiwan, MOST; Ministerio de Ciencia e Innovación, MICINN; Centre National pour la Recherche Scientifique et Technique, CNRST; Horizon 2020; British Columbia Knowledge Development Fund, BCKDF; European Regional Development Fund, ERDF; Defence Science Institute, DSI; Council on grants of the President of the Russian Federation; National Research Center "Kurchatov Institute", NRC KIen_US
dc.description.sponsorshipWe acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; ANID, Chile; CAS, MOST and NSFC, China; Minciencias, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRI, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; JINR; MES of Russia and NRC KI, Russian Federation; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DSI/NRF, South Africa; MICINN, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, UK; DOE and NSF, USA. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; COST, ERC, ERDF, Horizon 2020 and Marie Sk?odowska-Curie Actions, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; Norwegian Financial Mechanism 2014-2021, Norway; La Caixa Banking Foundation, CERCA Programme Generalitat de Catalunya and PROMETEO and GenT Programmes Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, UK.en_US
dc.language.isoenen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofComputing and Software for Big Scienceen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titleAtlfast3: the Next Generation of Fast Simulation in Atlasen_US
dc.typeArticleen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümüen_US
dc.departmentFaculties, Faculty of Engineering, Department of Material Science and Nanotechnology Engineeringen_US
dc.identifier.volume6en_US
dc.identifier.issue1en_US
dc.identifier.scopus2-s2.0-85126227550en_US
dc.institutionauthorSultansoy, Saleh-
dc.identifier.doi10.1007/s41781-021-00079-7-
dc.authorscopusid26326745400-
dc.authorscopusid35226946900-
dc.authorscopusid57208306618-
dc.authorscopusid57208907456-
dc.authorscopusid57210132793-
dc.authorscopusid57193183451-
dc.authorscopusid56536227400-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.scopusqualityQ1-
item.openairetypeArticle-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
Appears in Collections:Malzeme Bilimi ve Nanoteknoloji Mühendisliği Bölümü / Department of Material Science & Nanotechnology Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
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