scholarly journals Performance of a triple-GEM demonstrator in pp collisions at the CMS detector

2021 ◽  
Vol 16 (11) ◽  
pp. P11014
Author(s):  
M. Abbas ◽  
M. Abbrescia ◽  
H. Abdalla ◽  
A. Abdelalim ◽  
S. AbuZeid ◽  
...  
Keyword(s):  
Hadron Collider ◽  
Preliminary Investigation ◽  
Operational Experience ◽  
Detector Performance ◽  
Proton Proton ◽  
Background Rate ◽  
Electron Multiplier ◽  
Gem Detector ◽  
Gem Detectors

Abstract After the Phase-2 high-luminosity upgrade to the Large Hadron Collider (LHC), the collision rate and therefore the background rate will significantly increase, particularly in the high η region. To improve both the tracking and triggering of muons, the Compact Muon Solenoid (CMS) Collaboration plans to install triple-layer Gas Electron Multiplier (GEM) detectors in the CMS muon endcaps. Demonstrator GEM detectors were installed in CMS during 2017 to gain operational experience and perform a preliminary investigation of detector performance. We present the results of triple-GEM detector performance studies performed in situ during normal CMS and LHC operations in 2018. The distribution of cluster size and the efficiency to reconstruct high pT muons in proton-proton collisions are presented as well as the measurement of the environmental background rate to produce hits in the GEM detector.

scholarly journals Study of the GEM detector performance in BM@N experiment

2018 ◽  
Vol 177 ◽  
pp. 04004
Author(s):  
Sergei Bazylev ◽  
Mikhail Kapishin ◽  
Kacper Kapusniak ◽  
Vladimir Karjavine ◽  
Sergei Khabarov ◽  
...  
Keyword(s):  
Tracking System ◽  
Deuteron Beam ◽  
Heavy Ion ◽  
Relativistic Heavy Ion Collisions ◽  
Fixed Target ◽  
Detector Performance ◽  
Ion Collisions ◽  
Target Experiment ◽  
Gem Detector ◽  
Gem Detectors

BM@N is the fixed target experiment at the accelerator complex NICA-Nuclotron aimed to study nuclear matter in the relativistic heavy ion collisions. Triple-GEM detectors were identified as appropriate for the BM@N tracking system located inside the analyzing magnet. Seven GEM chambers are integrated into the BM@N experimental setup and data acquisition system. GEM construction, main characteristics and first obtained results of the GEM tracking system performance in the technical run with the deuteron beam are shortly reviewed.

scholarly journals GEM Detector Performance Assessment in the BM@N Experiment

2018 ◽  
Vol 173 ◽  
pp. 04007
Author(s):  
Mikhail Kapishin ◽  
Vladimir Karjavin ◽  
Elena Kulish ◽  
Vasilisa Lenivenko ◽  
Alexander Makankin ◽  
...  
Keyword(s):  
Elementary Particle ◽  
Performance Assessment ◽  
Spatial Resolution ◽  
Particle Physics ◽  
Charged Particles ◽  
Detector Performance ◽  
Electron Multiplier ◽  
Gas Electron Multiplier ◽  
Elementary Particle Physics ◽  
Gem Detector

The Gas Electron Multiplier (GEM) chambers are developed for modern purposes in the elementary particle physics. In the BM@N experiment, a GEM system is used for the reconstruction of the trajectories of the charged particles. The investigation of GEM performance (efficiency and spatial resolution) is presented.

scholarly journals GRAAL: A novel package to reconstruct data of triple-GEM detectors

2020 ◽  
Vol 245 ◽  
pp. 02021
Author(s):  
Riccardo Farinelli
Keyword(s):  
High Energy Physics ◽  
High Energy ◽  
Reconstruction Method ◽  
Detector Performance ◽  
Electron Multiplier ◽  
Innovative Cluster ◽  
Alignment Algorithms ◽  
Micro Pattern ◽  
Tracking Devices ◽  
Gem Detectors

Micro-Pattern Gas Detectors (MPGDs) are the new frontier among the gas tracking systems. Among them, the triple Gas Electron Multiplier (triple-GEM) detectors are widely used. In particular, cylindrical triple-GEM (CGEM) detectors can be used as inner tracking devices in high energy physics experiments. In this contribution, a new offline software called GRAAL (Gem Reconstruction And Analysis Library) is presented: digitization, reconstruction, alignment algorithms and analysis of the data collected with APV-25 and TIGER ASICs are reported. An innovative cluster reconstruction method based on charge centroid, micro-TPC and their merge is discussed, and the detector performance evaluated experimentally for both planar triple-GEM and CGEM prototypes.

scholarly journals Search for squarks and gluinos in final states with jets and missing transverse momentum using 139 fb−1 of $$ \sqrt{s} $$ = 13 TeV pp collision data with the ATLAS detector

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
G. Aad ◽  
◽  
B. Abbott ◽  
D. C. Abbott ◽  
A. Abed Abud ◽  
...  
Keyword(s):  
Transverse Momentum ◽  
Hadron Collider ◽  
Atlas Detector ◽  
Simplified Model ◽  
Supersymmetric Particle ◽  
Final States ◽  
Proton Proton ◽  
Missing Transverse Momentum ◽  
First And Second Generation ◽  
Proton Proton Collisions

Abstract A search for the supersymmetric partners of quarks and gluons (squarks and gluinos) in final states containing jets and missing transverse momentum, but no electrons or muons, is presented. The data used in this search were recorded by the ATLAS experiment in proton-proton collisions at a centre-of-mass energy of $$ \sqrt{s} $$ s = 13 TeV during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1. The results are interpreted in the context of various R-parity-conserving models where squarks and gluinos are produced in pairs or in association and a neutralino is the lightest supersymmetric particle. An exclusion limit at the 95% confidence level on the mass of the gluino is set at 2.30 TeV for a simplified model containing only a gluino and the lightest neutralino, assuming the latter is massless. For a simplified model involving the strong production of mass-degenerate first- and second-generation squarks, squark masses below 1.85 TeV are excluded if the lightest neutralino is massless. These limits extend substantially beyond the region of supersymmetric parameter space excluded previously by similar searches with the ATLAS detector.

scholarly journals Does SUSY have friends? A new approach for LHC event analysis

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Anna Mullin ◽  
Stuart Nicholls ◽  
Holly Pacey ◽  
Michael Parker ◽  
Martin White ◽  
...  
Keyword(s):  
Hadron Collider ◽  
Local Network ◽  
Proton Collision ◽  
Event Analysis ◽  
Final State ◽  
Proton Proton ◽  
Kinematic Space ◽  
Boosted Decision Tree ◽  
The Individual ◽  
Particle Search

Abstract We present a novel technique for the analysis of proton-proton collision events from the ATLAS and CMS experiments at the Large Hadron Collider. For a given final state and choice of kinematic variables, we build a graph network in which the individual events appear as weighted nodes, with edges between events defined by their distance in kinematic space. We then show that it is possible to calculate local metrics of the network that serve as event-by-event variables for separating signal and background processes, and we evaluate these for a number of different networks that are derived from different distance metrics. Using a supersymmetric electroweakino and stop production as examples, we construct prototype analyses that take account of the fact that the number of simulated Monte Carlo events used in an LHC analysis may differ from the number of events expected in the LHC dataset, allowing an accurate background estimate for a particle search at the LHC to be derived. For the electroweakino example, we show that the use of network variables outperforms both cut-and-count analyses that use the original variables and a boosted decision tree trained on the original variables. The stop example, deliberately chosen to be difficult to exclude due its kinematic similarity with the top background, demonstrates that network variables are not automatically sensitive to BSM physics. Nevertheless, we identify local network metrics that show promise if their robustness under certain assumptions of node-weighted networks can be confirmed.

Measurement Of Gas Electron Multiplier (GEM) Detector Characteristics

2011 ◽  
Author(s):  
Seongtae Park ◽  
Edwin Baldelomar ◽  
Kwangjune Park ◽  
Mark Sosebee ◽  
Andy White ◽  
...  
Keyword(s):  
Electron Multiplier ◽  
Gas Electron Multiplier ◽  
Gem Detector

scholarly journals Study of charged-particle multiplicity fluctuations in pp collisions with Monte Carlo event generators at the LHC

2020 ◽  
Vol 29 (09) ◽  
pp. 2050074
Author(s):  
E. Shokr ◽  
A. H. El-Farrash ◽  
A. De Roeck ◽  
M. A. Mahmoud
Keyword(s):  
Charged Particle ◽  
Particle Production ◽  
Local Density ◽  
Particle Density ◽  
Hadron Collider ◽  
Center Of Mass ◽  
Monte Carlo Event ◽  
Particle Multiplicity ◽  
Charged Particle Multiplicity ◽  
Proton Proton

Proton–Proton ([Formula: see text]) collisions at the Large Hadron Collider (LHC) are simulated in order to study events with a high local density of charged particles produced in narrow pseudorapidty windows of [Formula: see text] = 0.1, 0.2, and 0.5. The [Formula: see text] collisions are generated at center of mass energies of [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] TeV, i.e., the energies at which the LHC has operated so far, using PYTHIA and HERWIG event generators. We have also studied the average of the maximum charged-particle density versus the event multiplicity for all events, using the different pseudorapidity windows. This study prepares for the multi-particle production background expected in a future search for anomalous high-density multiplicity fluctuations using the LHC data.

scholarly journals Artificial Neural Networks on FPGAs for Real-Time Energy Reconstruction of the ATLAS LAr Calorimeters

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Georges Aad ◽  
Anne-Sophie Berthold ◽  
Thomas Calvet ◽  
Nemer Chiedde ◽  
Etienne Marie Fortin ◽  
...  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Real Time ◽  
Hadron Collider ◽  
Liquid Argon ◽  
Learning Approaches ◽  
High Luminosity ◽  
Proton Proton ◽  
Real Time Processing ◽  
Energy Reconstruction

AbstractThe ATLAS experiment at the Large Hadron Collider (LHC) is operated at CERN and measures proton–proton collisions at multi-TeV energies with a repetition frequency of 40 MHz. Within the phase-II upgrade of the LHC, the readout electronics of the liquid-argon (LAr) calorimeters of ATLAS are being prepared for high luminosity operation expecting a pileup of up to 200 simultaneous proton–proton interactions. Moreover, the calorimeter signals of up to 25 subsequent collisions are overlapping, which increases the difficulty of energy reconstruction by the calorimeter detector. Real-time processing of digitized pulses sampled at 40 MHz is performed using field-programmable gate arrays (FPGAs). To cope with the signal pileup, new machine learning approaches are explored: convolutional and recurrent neural networks outperform the optimal signal filter currently used, both in assignment of the reconstructed energy to the correct proton bunch crossing and in energy resolution. The improvements concern in particular energies derived from overlapping pulses. Since the implementation of the neural networks targets an FPGA, the number of parameters and the mathematical operations need to be well controlled. The trained neural network structures are converted into FPGA firmware using automated implementations in hardware description language and high-level synthesis tools. Very good agreement between neural network implementations in FPGA and software based calculations is observed. The prototype implementations on an Intel Stratix-10 FPGA reach maximum operation frequencies of 344–640 MHz. Applying time-division multiplexing allows the processing of 390–576 calorimeter channels by one FPGA for the most resource-efficient networks. Moreover, the latency achieved is about 200 ns. These performance parameters show that a neural-network based energy reconstruction can be considered for the processing of the ATLAS LAr calorimeter signals during the high-luminosity phase of the LHC.

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