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Author ATLAS Collaboration (Aad, G. 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.; Gonzalvo Rodriguez, G.R.; 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.
Title Resolution of the ATLAS muon spectrometer monitored drift tubes in LHC Run 2 Type Journal Article
Year (down) 2019 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 14 Issue Pages P09011 - 35pp
Keywords Gaseous detectors; Muon spectrometers; Particle tracking detectors (Gaseous detectors); Wire chambers (MWPC, Thin-gap chambers, drift chambers, drift tubes, proportional chambers etc)
Abstract The momentum measurement capability of the ATLAS muon spectrometer relies fundamentally on the intrinsic single-hit spatial resolution of the monitored drift tube precision tracking chambers. Optimal resolution is achieved with a dedicated calibration program that addresses the specific operating conditions of the 354 000 high-pressure drift tubes in the spectrometer. The calibrations consist of a set of timing offsets and drift time to drift distance transfer relations, and result in chamber resolution functions. This paper describes novel algorithms to obtain precision calibrations from data collected by ATLAS in LHC Run 2 and from a gas monitoring chamber, deployed in a dedicated gas facility. The algorithm output consists of a pair of correction constants per chamber which are applied to baseline calibrations, and determined to be valid for the entire ATLAS Run 2. The final single-hit spatial resolution, averaged over 1172 monitored drift tube chambers, is 81.7 +/- 2.2 μm.
Address [Deliot, F.; Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000486990000011 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4149
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Author Ortiz Arciniega, J.L.; Carrio, F.; Valero, A.
Title FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions Type Journal Article
Year (down) 2019 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 14 Issue Pages P09002 - 13pp
Keywords Data processing methods; Pattern recognition; cluster finding; calibration and fitting methods; Simulation methods and programs
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.
Address [Ortiz Arciniega, J. L.] Univ Valencia, Avinguda Univ S-N, Burjassot, Spain, Email: orarjo@alumni.uv.es
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000486990000002 Approved no
Is ISI yes International Collaboration no
Call Number IFIC @ pastor @ Serial 4150
Permanent link to this record
 

 
Author LHCb Collaboration (Aaij, R. et al); Garcia Martin, L.M.; Henry, L.; Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J.; Sanchez Mayordomo, C.
Title Measurement of the electron reconstruction efficiency at LHCb Type Journal Article
Year (down) 2019 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 14 Issue Pages P11023 - 20pp
Keywords Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors
Abstract The single electron track-reconstruction efficiency is calibrated using a sample corresponding to 1.3 fb(-1) of pp collision data recorded with the LHCb detector in 2017. This measurement exploits B+ -> J/psi (e(+)e(-))K+ decays, where one of the electrons is fully reconstructed and paired with the kaon, while the other electron is reconstructed using only the information of the vertex detector. Despite this partial reconstruction, kinematic and geometric constraints allow the B meson mass to be reconstructed and the signal to be well separated from backgrounds. This in turn allows the electron reconstruction efficiency to be measured by matching the partial track segment found in the vertex detector to tracks found by LHCb's regular reconstruction algorithms. The agreement between data and simulation is evaluated, and corrections are derived for simulated electrons in bins of kinematics. These correction factors allow LHCb to measure branching fractions involving single electrons with a systematic uncertainty below 1%.
Address [Bediaga, I; Cruz Torres, M.; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Soares Lavra, L.] Ctr Brasileiro Pesquisas Fis, Rio De Janeiro, Brazil, Email: laurent.dufour@cern.ch
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000507589800023 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4253
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Author ATLAS Collaboration (Aad, G. et al); Alvarez Piqueras, D.; 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.; Higon-Rodriguez, E.; 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.
Title Electron and photon performance measurements with the ATLAS detector using the 2015-2017 LHC proton-proton collision data Type Journal Article
Year (down) 2019 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 14 Issue Pages P12006 - 69pp
Keywords Particle identification methods; Performance of High Energy Physics Detectors
Abstract This paper describes the reconstruction of electrons and photons with the ATLAS detector, employed for measurements and searches exploiting the complete LHC Run 2 dataset. An improved energy clustering algorithm is introduced, and its implications for the measurement and identification of prompt electrons and photons are discussed in detail. Corrections and calibrations that affect performance, including energy calibration, identification and isolation efficiencies, and the measurement of the charge of reconstructed electron candidates are determined using up to 81 fb(-1) of proton-proton collision data collected at root s = 13 TeV between 2015 and 2017.
Address [Deliot, F.; Duvnjak, D.; Jackson, P.; Oliver, J. L.; Petridis, A.; Qureshi, A.; Sharma, A. S.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000510149300006 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 4269
Permanent link to this record
 

 
Author Double Chooz collaboration (Abrahao, T. et al); Novella, P.
Title Novel event classification based on spectral analysis of scintillation waveforms in Double Chooz Type Journal Article
Year (down) 2018 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 13 Issue Pages P01031 - 26pp
Keywords Digital signal processing (DSP); Particle identification methods; Scintillators, scintillation and light emission processes (solid, gas and liquid scintillators); Neutrino detectors
Abstract Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a novel approach for a pulse shape based event classification developed in the context of the Double Chooz reactor antineutrino experiment. Unlike previous implementations, this method uses the Fourier power spectra of the scintillation pulse shapes to obtain event-wise information. A classification variable built from spectral information was able to achieve an unprecedented performance, despite the lack of optimization at the detector design level. Several examples of event classification are provided, ranging from differentiation between the detector volumes and an efficient rejection of instrumental light noise, to some sensitivity to the particle type, such as stopping muons, ortho-positronium formation, alpha particles as well as electrons and positrons. In combination with other techniques the method is expected to allow for a versatile and more efficient background rejection in the future, especially if detector optimization is taken into account at the design level.
Address [Abrahao, T.; dos Anjos, J. C.; Lima, H.; Pepe, I.; Wagner, S.] Ctr Brasileiro Pesquisas Fis, BR-22290180 Rio De Janeiro, Brazil, Email: stefan.wagner@apc.in2p3.fr
Corporate Author Thesis
Publisher Iop Publishing Ltd Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 1748-0221 ISBN Medium
Area Expedition Conference
Notes WOS:000423783800003 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3466
Permanent link to this record