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Author |
ATLAS Collaboration (Aad, G. et al); Cabrera Urban, S.; Castillo Gimenez, V.; Costa, M.J.; Fassi, F.; Ferrer, A.; Fiorini, L.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Hernandez Jimenez, Y.; Higon-Rodriguez, E.; Irles Quiles, A.; Kaci, M.; Lacasta, C.; Lacuesta, V.R.; March, L.; Marti-Garcia, S.; Miñano, M.; Mitsou, V.A.; Moles-Valls, R.; Moreno Llacer, M.; Oliver Garcia, E.; Pedraza Lopez, S.; Perez Garcia-Estañ, M.T.; Romero Adam, E.; Ros, E.; Salt, J.; Sanchez Martinez, V.; Solans, C.A.; Soldevila, U.; Sanchez, J.; Torro Pastor, E.; Valero, A.; Valladolid Gallego, E.; Valls Ferrer, J.A.; Villaplana Perez, M.; Vos, M. |
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Title |
Characterisation and mitigation of beam-induced backgrounds observed in the ATLAS detector during the 2011 proton-proton run |
Type |
Journal Article |
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Year |
2013 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
8 |
Issue |
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Pages |
P07004 - 72pp |
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Keywords |
Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors; Accelerator modelling and simulations (multi-particle dynamics; single-particle dynamics); Analysis and statistical methods |
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Abstract |
This paper presents a summary of beam-induced backgrounds observed in the ATLAS detector and discusses methods to tag and remove background contaminated events in data. Trigger-rate based monitoring of beam-related backgrounds is presented. The correlations of backgrounds with machine conditions, such as residual pressure in the beam-pipe, are discussed. Results from dedicated beam-background simulations are shown, and their qualitative agreement with data is evaluated. Data taken during the passage of unpaired, i.e. non-colliding, proton bunches is used to obtain background-enriched data samples. These are used to identify characteristic features of beam-induced backgrounds, which then are exploited to develop dedicated background tagging tools. These tools, based on observables in the Pixel detector, the muon spectrometer and the calorimeters, are described in detail and their efficiencies are evaluated. Finally an example of an application of these techniques to a monojet analysis is given, which demonstrates the importance of such event cleaning techniques for some new physics searches. |
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Address  |
[Jackson, P.; Soni, N.] Univ Adelaide, Sch Chem & Phys, Adelaide, SA, Australia |
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Publisher |
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:000322572900015 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1557 |
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Author |
CALICE Collaboration (Lai, S. et al); Irles, A. |
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Title |
Software compensation for highly granular calorimeters using machine learning |
Type |
Journal Article |
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Year |
2024 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
19 |
Issue |
4 |
Pages |
P04037 - 28pp |
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Keywords |
Large detector-systems performance; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors |
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Abstract |
A neural network for software compensation was developed for the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL). The neural network uses spatial and temporal event information from the AHCAL and energy information, which is expected to improve sensitivity to shower development and the neutron fraction of the hadron shower. The neural network method produced a depth-dependent energy weighting and a time-dependent threshold for enhancing energy deposits consistent with the timescale of evaporation neutrons. Additionally, it was observed to learn an energy-weighting indicative of longitudinal leakage correction. In addition, the method produced a linear detector response and outperformed a published control method regarding resolution for every particle energy studied. |
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Address |
[Lai, S.; Utehs, J.; Wilhahn, A.] Georg August Univ Gottingen, Phys Inst 2, Friedrich Hund Pl 1, D-37077 Gottingen, Germany, Email: jack.rolph@desy.de |
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Publisher |
IOP Publishing Ltd |
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English |
Summary Language |
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Series Editor |
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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 |
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Conference |
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Notes |
WOS:001230094600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6128 |
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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. |
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Title |
Centrality determination in heavy-ion collisions with the LHCb detector |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
5 |
Pages |
P05009 - 31pp |
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Keywords |
Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors; Simulation methods and programs |
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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. |
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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 |
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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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Area |
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Expedition |
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Conference |
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Notes |
WOS:000832952600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5315 |
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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. |
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Title |
Identification of charm jets at LHCb |
Type |
Journal Article |
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Year |
2022 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
17 |
Issue |
2 |
Pages |
P02028 - 23pp |
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Keywords |
Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors |
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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. |
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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 |
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Corporate Author |
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Thesis |
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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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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000770368300015 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5177 |
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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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Thesis |
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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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Medium |
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Area |
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Expedition |
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Conference |
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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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| Permanent link to this record |
