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LHCb Detector Performance Papers

Najnovije dodano:
2023-05-21
09:16
The LHCb upgrade I / LHCb Collaboration
The LHCb upgrade represents a major change of the experiment. [...]
arXiv:2305.10515 ; LHCb-DP-2022-002.
- 232 p.
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2023-01-12
06:05
Graph Clustering: a graph-based clustering algorithm for the electromagnetic calorimeter in LHCb / Canudas, Núria Valls (Ramon Llull U., Barcelona) ; Calvo Gómez, Míriam (Ramon Llull U., Barcelona) ; Vilasís-Cardona, Xavier (Ramon Llull U., Barcelona) ; Ribé, Elisabet Golobardes (Ramon Llull U., Barcelona)
The recent upgrade of the LHCb experiment pushes data processing rates up to 40 Tbit/s. Out of the whole reconstruction sequence, one of the most time consuming algorithms is the calorimeter reconstruction. [...]
arXiv:2212.11061; LHCb-DP-2022-003.- 2023-02-25 - 15 p. - Published in : Eur. Phys. J. C 83 (2023) 179 Fulltext: 2212.11061 - PDF; document - PDF;

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2022-11-23
04:27
Long-lived particle reconstruction downstream of the LHCb magnet
Charged-particle trajectories are usually reconstructed with the LHCb detector using combined information from the tracking devices placed upstream and downstream of the 4 Tm dipole magnet. [...]
arXiv:2211.10920 ; LHCb-DP-2022-001.
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2022-06-01
04:19
Performance of the LHCb RICH detectors during LHC Run 2 / Calabrese, R. (INFN, Ferrara ; U. Ferrara (main)) ; Fiorini, M. (INFN, Ferrara ; U. Ferrara (main)) ; Luppi, E. (INFN, Ferrara ; U. Ferrara (main)) ; Minzoni, L. (INFN, Ferrara ; U. Ferrara (main)) ; Slazyk, I. (INFN, Ferrara ; U. Ferrara (main)) ; Tomassetti, L. (INFN, Ferrara ; U. Ferrara (main)) ; Bartolini, M. (INFN, Genoa ; U. Genoa) ; Cardinale, R. (INFN, Genoa ; U. Genoa) ; Fontanelli, F. (INFN, Genoa ; U. Genoa) ; Petrolini, A. (INFN, Genoa ; U. Genoa) et al.
The performance of the ring-imaging Cherenkov detectors at the LHCb experiment is determined during the LHC Run 2 period between 2015 and 2018. The stability of the Cherenkov angle resolution and number of detected photons with time and running conditions is measured. [...]
arXiv:2205.13400; LHCb-DP-2021-004.- 2022-07-06 - 23 p. - Published in : JINST 17 (2022) P07013 Fulltext: document - PDF; 2205.13400 - PDF;

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2021-12-18
04:06
Identification of charm jets at LHCb / LHCb Collaboration
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. [...]
arXiv:2112.08435; LHCb-DP-2021-006.- 2022-02-22 - 22 p. - Published in : JINST 17 (2022) P02028 Fulltext: document - PDF; Aaij_2022_J._Inst._17_P02028 - PDF; 2112.08435 - PDF;

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2021-11-03
07:30
Centrality determination in heavy-ion collisions with the LHCb detector / LHCb Collaboration
The centrality of heavy-ion collisions is directly related to the medium created therein. A procedure to determine the centrality of collisions with the LHCb detector is implemented for lead-lead collisions at $\sqrt{s_{\scriptscriptstyle\text{NN}}}=5\, \mathrm{TeV}$ and lead-neon fixed-target collisions at $\sqrt{s_{\scriptscriptstyle\text{NN}}}=69\, \mathrm{GeV}$. [...]
arXiv:2111.01607; CERN-LHCb-DP-2021-002.- 2022-05-05 - 31 p. - Published in : JINST 17 (2022) P05009 Fulltext: 2111.01607 - PDF; document - PDF;

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2021-10-23
04:04
A Neural-Network-defined Gaussian Mixture Model for particle identification applied to the LHCb fixed-target programme / Graziani, Giacomo (INFN, Florence) ; Anderlini, Lucio (INFN, Florence) ; Mariani, Saverio (INFN, Florence ; Florence U. ; CERN) ; Franzoso, Edoardo (INFN, Ferrara ; Ferrara U.) ; Pappalardo, Luciano Libero (INFN, Ferrara ; Ferrara U.) ; di Nezza, Pasquale (Frascati)
Particle identification in large high-energy physics experiments typically relies on classifiers obtained by combining many experimental observables. Predicting the probability density function (pdf) of such classifiers in the multivariate space covering the relevant experimental features is usually challenging. [...]
arXiv:2110.10259; LHCb-DP-2021-007.- 2022-02-09 - 27 p. - Published in : JINST 17 (2022) P02018 Fulltext: document - PDF; 2110.10259 - PDF;

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2021-10-08
04:21
Characterisation of signal-induced noise in Hamamatsu R11265 Multianode Photomultiplier Tubes / LHCb Collaboration
Signal-induced noise is observed in Hamamatsu R11265 Multianode Photomultiplier Tubes, manifesting up to several microseconds after the single photoelectron response signal and localised in specific anodes. The mean number of noise pulses varies between devices, and shows significant dependence on the applied high-voltage. [...]
arXiv:2110.00831; CERN-LHCb-DP-2021-005.- 2021-11-23 - 24 p. - Published in : JINST 16 (2021) P11030 Fulltext: PDF; Fulltext from publisher: PDF;

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2021-05-12
04:01
A Comparison of CPU and GPU implementations for the LHCb Experiment Run 3 Trigger / LHCb Collaboration
The LHCb experiment at CERN is undergoing an upgrade in preparation for the Run 3 data taking period of the LHC. As part of this upgrade the trigger is moving to a fully software implementation operating at the LHC bunch crossing rate. [...]
arXiv:2105.04031; LHCb-DP-2021-003.- 2021-12-22 - 30 p. - Published in : Comput. Softw. Big Sci.: 6 (2022) , no. 1, pp. 1
Fulltext: Publication - PDF; 2105.04031 - PDF; External link: Fulltext

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2021-03-27
04:21
A parametrized Kalman filter for fast track fitting at LHCb / Billoir, Pierre (Paris U., VI-VII) ; De Cian, Michel (Ecole Polytechnique, Lausanne) ; Günther, Paul André (Heidelberg U.) ; Stemmle, Simon (Heidelberg U.)
We present an alternative implementation of the Kalman filter employed for track fitting within the LHCb experiment. It uses simple parametrizations for the extrapolation of particle trajectories in the field of the LHCb dipole magnet and for the effects of multiple scattering in the detector material. [...]
arXiv:2101.12040; LHCb-DP-2021-001.- 2021-08 - 7 p. - Published in : Comput. Phys. Commun. 265 (2021) 108026 Fulltext: PDF; Fulltext from publisher: PDF; Related data file(s): ZIP;

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