Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/69382
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Onofre, A. | por |
dc.contributor.author | Castro, Nuno Filipe | por |
dc.contributor.author | ATLAS Collaboration | por |
dc.date.accessioned | 2021-01-18T00:17:33Z | - |
dc.date.available | 2021-01-18T00:17:33Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Aaboud, M., Aad, G., Abbott, B., Abdinov, O., Abeloos, B., Abhayasinghe, D. K., . . . Collaboration, A. (2020). ATLAS data quality operations and performance for 2015-2018 data-taking. Journal of Instrumentation, 15(4). doi: 10.1088/1748-0221/15/04/p04003 | por |
dc.identifier.issn | 1748-0221 | - |
dc.identifier.uri | https://hdl.handle.net/1822/69382 | - |
dc.description.abstract | The ATLAS detector at the Large Hadron Collider reads out particle collision data from over 100 million electronic channels at a rate of approximately 100 kHz, with a recording rate for physics events of approximately 1 kHz. Before being certified for physics analysis at computer centres worldwide, the data must be scrutinised to ensure they are clean from any hardware or software related issues that may compromise their integrity. Prompt identification of these issues permits fast action to investigate, correct and potentially prevent future such problems that could render the data unusable. This is achieved through the monitoring of detector-level quantities and reconstructed collision event characteristics at key stages of the data processing chain. This paper presents the monitoring and assessment procedures in place at ATLAS during 2015–2018 data-taking. Through the continuous improvement of operational procedures, ATLAS achieved a high data quality efficiency, with 95.6% of the recorded proton-proton collision data collected at √s=13 TeV certified for physics analysis. | por |
dc.description.sponsorship | We 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; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, 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; GSRT, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSWandNCN, Poland; FCT, Portugal; MNE/IFA, Romania; MESofRussia andNRCKI, Russia Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZS, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; ERC, ERDF, Horizon 2020, Marie Sklodowska-Curie Actions and COST, 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; CERCA Programme Generalitat de Catalunya and PROMETEO Programme Generalitat Valenciana, Spain; Goran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom.r The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, theATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF(Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (U.K.) and BNL (U.S.A.), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in ref. [40]. | por |
dc.language.iso | eng | por |
dc.publisher | IOP Publishing | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | por |
dc.subject | Large detector systems for particle and astroparticle physics | por |
dc.subject | Large detector-systems performance | por |
dc.title | ATLAS data quality operations and performance for 2015–2018 data-taking | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://iopscience.iop.org/article/10.1088/1748-0221/15/04/P04003 | por |
oaire.citationIssue | 4 | por |
oaire.citationVolume | 15 | por |
dc.identifier.doi | 10.1088/1748-0221/15/04/p04003 | por |
dc.subject.fos | Ciências Naturais::Ciências Físicas | por |
dc.description.publicationversion | info:eu-repo/semantics/publishedVersion | - |
dc.subject.wos | Science & Technology | por |
sdum.journal | Journal of Instrumentation | por |
oaire.version | VoR | por |
Aparece nas coleções: | LIP - Artigos/papers |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Aad_2020_J._Inst._15_P04003.pdf | 1,53 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons