Records |
Author |
ATLAS Collaboration (Aad, G. et al); Aparisi Pozo, J.A.; Bailey, A.J.; Cabrera Urban, S.; Castillo, F.L.; Castillo Gimenez, V.; Cerda Alberich, L.; Costa, M.J.; Escobar, C.; Estrada Pastor, O.; Ferrer, A.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Higon-Rodriguez, E.; Lacasta, C.; Lozano Bahilo, J.J.; Madaffari, D.; Mamuzic, J.; Marti-Garcia, S.; Martinez Agullo, P.; Miñano, M.; Mitsou, V.A.; Moreno Llacer, M.; Poveda, J.; Rodriguez Bosca, S.; Rodriguez Rodriguez, D.; Ruiz-Martinez, A.; Salt, J.; Santra, A.; Sayago Galvan, I.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M. |
Title |
Performance of the ATLAS muon triggers in Run 2 |
Type |
Journal Article |
Year |
2020 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
15 |
Issue |
9 |
Pages |
P09015 - 57pp |
Keywords |
Data acquisition concepts; Data processing methods; Online farms and online filtering; Trigger concepts and systems (hardware and software) |
Abstract |
The performance of the ATLAS muon trigger system is evaluated with proton-proton (pp) and heavy-ion (HI) collision data collected in Run 2 during 2015-2018 at the Large Hadron Collider. It is primarily evaluated using events containing a pair of muons from the decay of Z bosons to cover the intermediate momentum range between 26 GeV and 100 GeV. Overall, the efficiency of the single-muon triggers is about 68% in the barrel region and 85% in the endcap region. The p(T) range for efficiency determination is extended by using muons from decays of J/psi mesons, W bosons, and top quarks. The performance in HI collision data is measured and shows good agreement with the results obtained in pp collisions. The muon trigger shows uniform and stable performance in good agreement with the prediction of a detailed simulation. Dedicated multi-muon triggers with kinematic selections provide the backbone to beauty, quarkonia, and low-mass physics studies. The design, evolution and performance of these triggers are discussed in detail. |
Address |
[Deliot, F.; Duvnjak, D.; Jackson, P.; Kong, A. X. Y.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
Corporate Author |
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Thesis |
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Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000577273400015 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
4571 |
Permanent link to this record |
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Author |
Kasieczka, G. et al; Sanz, V. |
Title |
The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics |
Type |
Journal Article |
Year |
2021 |
Publication |
Reports on Progress in Physics |
Abbreviated Journal |
Rep. Prog. Phys. |
Volume |
84 |
Issue |
12 |
Pages |
124201 - 64pp |
Keywords |
anomaly detection; machine learning; unsupervised learning; weakly supervised learning; semisupervised learning; beyond the standard model; model-agnostic methods |
Abstract |
A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders. |
Address |
[Kasieczka, Gregor] Univ Hamburg, Inst Expt Phys, Hamburg, Germany, Email: gregor.kasieczka@uni-hamburg.de; |
Corporate Author |
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Thesis |
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Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
IOP Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0034-4885 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000727698500001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5039 |
Permanent link to this record |
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Author |
LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J. |
Title |
Identification of charm jets at LHCb |
Type |
Journal Article |
Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
17 |
Issue |
2 |
Pages |
P02028 - 23pp |
Keywords |
Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors |
Abstract |
The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement. |
Address |
[Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: dcraik@cern.ch |
Corporate Author |
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Thesis |
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Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
IOP Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
|
Area |
|
Expedition |
|
Conference |
|
Notes |
WOS:000770368300015 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5177 |
Permanent link to this record |
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Author |
ATLAS Collaboration (Aad, G. et al); Aparisi Pozo, J.A.; Bailey, A.J.; Cabrera Urban, S.; Cardillo, F.; Castillo Gimenez, V.; Costa, M.J.; Escobar, C.; Estrada Pastor, O.; Ferrer, A.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Higon-Rodriguez, E.; Lacasta, C.; Lozano Bahilo, J.J.; Mamuzic, J.; Marti-Garcia, S.; Martinez Agullo, P.; Mitsou, V.A.; Moreno Llacer, M.; Navarro-Gonzalez, J.; Poveda, J.; Prades Ibañez, A.; Ruiz-Martinez, A.; Sabatini, P.; Salt, J.; Sayago Galvan, I.; Soldevila, U.; Sanchez, J.; Torro Pastor, E.; Valero, A.; Valls Ferrer, J.A.; Villaplana Perez, M.; Vos, M. |
Title |
The ATLAS Fast TracKer system |
Type |
Journal Article |
Year |
2021 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
16 |
Issue |
7 |
Pages |
P07006 - 61pp |
Keywords |
Modular electronics; Online farms and online filtering; Pattern recognition, cluster finding, calibration and fitting methods; Trigger concepts and systems (hardware and software) |
Abstract |
The ATLAS Fast TracKer (FTK) was designed to provide full tracking for the ATLAS high-level trigger by using pattern recognition based on Associative Memory (AM) chips and fitting in high-speed field programmable gate arrays. The tracks found by the FTK are based on inputs from all modules of the pixel and silicon microstrip trackers. The as-built FTK system and components are described, as is the online software used to control them while running in the ATLAS data acquisition system. Also described is the simulation of the FTK hardware and the optimization of the AM pattern banks. An optimization for long-lived particles with large impact parameter values is included. A test of the FTK system with the data playback facility that allowed the FTK to be commissioned during the shutdown between Run 2 and Run 3 of the LHC is reported. The resulting tracks from part of the FTK system covering a limited eta-phi region of the detector are compared with the output from the FTK simulation. It is shown that FTK performance is in good agreement with the simulation. |
Address |
[Duvnjak, D.; Jackson, P.; Kong, A. X. Y.; Oliver, J. L.; Ruggeri, T. A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
Corporate Author |
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Thesis |
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Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
IOP Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
|
Notes |
WOS:000791152800006 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5225 |
Permanent link to this record |
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Author |
LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J. |
Title |
Centrality determination in heavy-ion collisions with the LHCb detector |
Type |
Journal Article |
Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
Volume |
17 |
Issue |
5 |
Pages |
P05009 - 31pp |
Keywords |
Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors; Simulation methods and programs |
Abstract |
The centrality of heavy-ion collisions is directly related to the created medium in these interactions. A procedure to determine the centrality of collisions with the LHCb detector is implemented for lead-lead collisions root s(NN) = 5 TeV and lead-neon fixed-target collisions at root s(NN) = 69 GeV. The energy deposits in the electromagnetic calorimeter are used to determine and define the centrality classes. The correspondence between the number of participants and the centrality for the lead-lead collisions is in good agreement with the correspondence found in other experiments, and the centrality measurements for the lead-neon collisions presented here are performed for the first time in fixed-target collisions at the LHC. |
Address |
[Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil |
Corporate Author |
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Thesis |
|
Publisher ![sorted by Publisher field, descending order (down)](img/sort_desc.gif) |
IOP Publishing Ltd |
Place of Publication |
|
Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
|
Medium |
|
Area |
|
Expedition |
|
Conference |
|
Notes |
WOS:000832952600001 |
Approved |
no |
Is ISI |
yes |
International Collaboration |
yes |
Call Number |
IFIC @ pastor @ |
Serial |
5315 |
Permanent link to this record |