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ATLAS Collaboration (Aaboud, M. et al); Alvarez Piqueras, D.; Aparisi Pozo, J.A.; Bailey, A.J.; Barranco Navarro, L.; 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.; Higon-Rodriguez, E.; Jimenez Pena, J.; Lacasta, C.; Lozano Bahilo, J.J.; Madaffari, D.; Mamuzic, J.; Marti-Garcia, S.; Melini, D.; Miñano, M.; Mitsou, V.A.; Rodriguez Bosca, S.; Rodriguez Rodriguez, D.; Ruiz-Martinez, A.; Salt, J.; Santra, A.; Soldevila, U.; Sanchez, J.; Valero, A.; Valls Ferrer, J.A.; Vos, M. |
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Title  |
Electron and photon energy calibration with the ATLAS detector using 2015-2016 LHC proton-proton collision data |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
14 |
Issue |
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Pages |
P03017 - 60pp |
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Keywords |
Calorimeter methods; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors |
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Abstract |
This paper presents the electron and photon energy calibration obtained with the ATLAS detector using about 36 fb(-1) of LHC proton-proton collision data recorded at root s = 13 TeV in 2015 and 2016. The different calibration steps applied to the data and the optimization of the reconstruction of electron and photon energies are discussed. The absolute energy scale is set using a large sample of Z boson decays into electron-positron pairs. The systematic uncertainty in the energy scale calibration varies between 0.03% to 0.2% in most of the detector acceptance for electrons with transverse momentum close to 45 GeV. For electrons with transverse momentum of 10 GeV the typical uncertainty is 0.3% to 0.8% and it varies between 0.25% and 1% for photons with transverse momentum around 60 GeV. Validations of the energy calibration with J/psi -> e(+)e(-) decays and radiative Z boson decays are also presented. |
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Address |
[Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
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Iop Publishing Ltd |
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English |
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ISSN |
1748-0221 |
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Conference |
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Notes |
WOS:000463330900005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3972 |
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Author |
ATLAS Collaboration (Aad, G. et al); Aikot, A.; Amos, K.R.; Aparisi Pozo, J.A.; Bailey, A.J.; Bouchhar, N.; Cabrera Urban, S.; Cantero, J.; Cardillo, F.; Castillo Gimenez, V.; Chitishvili, M.; Costa, M.J.; Didenko, M.; Escobar, C.; Fiorini, L.; Fullana Torregrosa, E.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gomez Delegido, A.J.; Gonzalez de la Hoz, S.; Gonzalvo Rodriguez, G.R.; Guerrero Rojas, J.G.R.; Lacasta, C.; Marti-Garcia, S.; Martinez Agullo, P.; Miralles Lopez, M.; Mitsou, V.A.; Monsonis Romero, L.; Moreno Llacer, M.; Munoz Perez, D.; Navarro-Gonzalez, J.; Poveda, J.; Prades Ibañez, A.; Rubio Jimenez, A.; Ruiz-Martinez, A.; Sabatini, P.; Saibel, A.; Salt, J.; Sanchez Sebastian, V.; Sayago Galvan, I.; Senthilkumar, V.; Soldevila, U.; Sanchez, J.; Torro Pastor, E.; Valero, A.; Valiente Moreno, E.; Valls Ferrer, J.A.; Varriale, L.; Villaplana Perez, M.; Vos, M. |
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Title |
Electron and photon energy calibration with the ATLAS detector using LHC Run 2 data |
Type |
Journal Article |
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Year |
2024 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
19 |
Issue |
2 |
Pages |
P02009 - 58pp |
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Keywords |
Calorimeter methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors |
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Abstract |
This paper presents the electron and photon energy calibration obtained with the ATLAS detector using 140 fb-1 of LHC proton -proton collision data recorded at -Js = 13 TeV between 2015 and 2018. Methods for the measurement of electron and photon energies are outlined, along with the current knowledge of the passive material in front of the ATLAS electromagnetic calorimeter. The energy calibration steps are discussed in detail, with emphasis on the improvements introduced in this paper. The absolute energy scale is set using a large sample of Z -boson decays into electron -positron pairs, and its residual dependence on the electron energy is used for the first time to further constrain systematic uncertainties. The achieved calibration uncertainties are typically 0.05% for electrons from resonant Z -boson decays, 0.4% at ET – 10 GeV, and 0.3% at ET – 1 TeV; for photons at ET <^>' 60 GeV, they are 0.2% on average. This is more than twice as precise as the previous calibration. The new energy calibration is validated using .11tfr -, ee and radiative Z -boson decays. |
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Address |
[Filmer, E. K.; Grant, C. M.; Jackson, P.; Kong, A. X. Y.; Pandya, H. D.; Potti, H.; Ruggeri, T. A.; Ting, E. X. L.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia |
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Publisher |
IOP Publishing Ltd |
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Language |
English |
Summary Language |
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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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Area |
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Expedition |
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Conference |
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Notes |
WOS:001185791500005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6069 |
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Author |
Bouhova-Thacker, E.; Kostyukhin, V.; Koffas, T.; Liebig, W.; Limper, M.; Piacquadio, G.N.; Prokofiev, K.; Weiser, C.; Wildauer, A. |
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Title |
Expected Performance of Vertex Reconstruction in the ATLAS Experiment at the LHC |
Type |
Journal Article |
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Year |
2010 |
Publication |
IEEE Transactions on Nuclear Science |
Abbreviated Journal |
IEEE Trans. Nucl. Sci. |
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Volume |
57 |
Issue |
2 |
Pages |
760-767 |
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Keywords |
Data analysis; data reconstruction; high energy physics; pattern recognition; reconstruction algorithms; tracking; vertex detectors |
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Abstract |
In the harsh environment of the Large Hadron Collider at CERN (design luminosity of 10(34) cm(-2) s(-1)) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper is the expected performance of the vertex reconstruction used in the ATLAS experiment. The algorithms for the reconstruction of primary and secondary vertices as well as for finding photon conversions and vertex reconstruction in jets are described. The implementation of vertex algorithms which follows a very modular design based on object-oriented C++ is presented. A user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented. |
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Address |
[Bouhova-Thacker, Eva] Univ Lancaster, Lancaster LA1 4YB, England, Email: bouhova@mail.cern.ch |
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Ieee-Inst Electrical Electronics Engineers Inc |
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English |
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ISSN |
0018-9499 |
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Notes |
ISI:000276679200006 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
260 |
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Author |
Ortiz Arciniega, J.L.; Carrio, F.; Valero, A. |
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Title |
FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions |
Type |
Journal Article |
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Year |
2019 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
14 |
Issue |
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Pages |
P09002 - 13pp |
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Keywords |
Data processing methods; Pattern recognition; cluster finding; calibration and fitting methods; Simulation methods and programs |
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Abstract |
The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented. |
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Address |
[Ortiz Arciniega, J. L.] Univ Valencia, Avinguda Univ S-N, Burjassot, Spain, Email: orarjo@alumni.uv.es |
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Corporate Author |
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Publisher |
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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Notes |
WOS:000486990000002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
4150 |
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Author |
Aiola, S.; Amhis, Y.; Billoir, P.; Jashal, B.K.; Henry, L.; Oyanguren, A.; Marin Benito, C.; Polci, F.; Quagliani, R.; Schiller, M.; Wang, M. |
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Title |
Hybrid seeding: A standalone track reconstruction algorithm for scintillating fibre tracker at LHCb |
Type |
Journal Article |
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Year |
2021 |
Publication |
Computer Physics Communications |
Abbreviated Journal |
Comput. Phys. Commun. |
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Volume |
260 |
Issue |
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Pages |
107713 - 5pp |
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Keywords |
Track reconstruction; Pattern Recognition; LHCb |
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Abstract |
We describe the Hybrid seeding, a stand-alone pattern recognition algorithm aiming at finding charged particle trajectories for the LHCb upgrade. A significant improvement to the charged particle reconstruction efficiency is accomplished by exploiting the knowledge of the LHCb magnetic field and the position of energy deposits in the scintillating fibre tracker detector. Moreover, we achieve a low fake rate and a small contribution to the overall timing budget of the LHCb real-time data processing. |
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Address |
[Billoir, P.; Polci, F.; Quagliani, R.] Sorbonne Univ, Paris Diderot Sorbonne Paris Cite, LPNHE, CNRS IN2P3, Paris, France, Email: louis.henry@cern.ch; |
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Publisher |
Elsevier |
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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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 |
0010-4655 |
ISBN |
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Conference |
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Notes |
WOS:000608243400007 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4685 |
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| Permanent link to this record |
