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Optimising longitudinal and lateral calorimeter granularity for software compensation in hadronic showers using deep neural networks / Neubüser, Coralie (INFN, Trento) ; Kieseler, Jan (CERN) ; Lujan, Paul (Canterbury U.)
We investigate the effect of longitudinal and transverse calorimeter segmentation on event-by-event software compensation for hadronic showers. To factorize out sampling and electronics effects, events are simulated in which a single charged pion is shot at a homogenous lead glass calorimeter, split into longitudinal and transverse segments of varying size. [...]
arXiv:2101.08150.- 2022-01-29 - Published in : Eur. Phys. J. C 82 (2022) 92 Fulltext: document - PDF; 2101.08150 - PDF;

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(91)

Qualification, Performance Validation and Fast Generative Modelling of Beam Test Calorimeter Prototypes for the CMS Calorimeter Endcap Upgrade / Quast, Thorben
In order to cope with the increased radiation level and the challenging pile-up conditions at High Luminosity-LHC, the CMS collaboration will replace its current calorimeter endcaps with the High Granularity Calorimeter (HGCAL) in the mid 2020s [...]
CERN-THESIS-2019-367 - Cham : Springer. - 244 p.

publication
thesis

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(88)

Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics / Belayneh, Dawit (U. Chicago (main)) ; Carminati, Federico (CERN) ; Farbin, Amir (Texas U., Arlington (main)) ; Hooberman, Benjamin (Illinois U., Urbana (main)) ; Khattak, Gulrukh (CERN ; Unlisted, PK) ; Liu, Miaoyuan (Fermilab) ; Liu, Junze (Illinois U., Urbana (main)) ; Olivito, Dominick (UC, San Diego (main)) ; Barin Pacela, Vitória (U. Helsinki (main)) ; Pierini, Maurizio (CERN) et al.
Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of particles produced in high-energy physics collisions. We train neural networks on shower data at the calorimeter-cell level, and show significant improvements for simulation and reconstruction when using these networks compared to methods which rely on currently-used state-of-the-art algorithms. [...]
arXiv:1912.06794; FERMILAB-PUB-20-448-CMS.- 2020-07-31 - 31 p. - Published in : Eur. Phys. J. C 80 (2020) 688 Article from SCOAP3: scoap3-fulltext - PDF; scoap - PDF; Fulltext: fermilab-pub-20-448-cms - PDF; 1912.06794 - PDF; Fulltext from Publisher: PDF;

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(82)

Charged pion energy reconstruction in HGCAL TB prototype using graph neural networks / Alpana, Alpana (IISER, Pune) /CMS Collaboration
The CMS Collaboration is preparing to replace its endcap calorimeters for the HL-LHC era with a high-granularity calorimeter (HGCAL). The HGCAL will have fine segmentation in both the transverse and longitudinal directions, and will be the first such calorimeter specifically optimized for particle-flow reconstruction to operate at a colliding-beam experiment. [...]
CMS-CR-2023-071.- Geneva : CERN, 2024 - 4 p. - Published in : Springer Proc.Phys. 304 (2024) 690-692 Fulltext: PDF;
In : 25th DAE-BRNS High Energy Physics Symposium, Punjab, India, 12 - 16 Dec 2022, pp.690-692

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(81)

Advances in hadron calorimetry / Wigmans, R (CERN)
CERN-PPE-91-39.- Geneva : CERN, 1991 - 69 p. - Published in : Annu. Rev. Nucl. Part. Sci. 41 (1991) 133-185 Fulltext: PDF; - CERN library copies

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(80)

Neural network-based sensor modeling and its application / Shi, H
2000
In : International Conference on Sensors and Control Techniques, Wuhan, China, 19 - 21 Jun 2000, pp.441-444

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(75)

Measurement of high $p_T$ isolated prompt photons in lead-lead collisions at $\sqrt{s_NN}$=2.76 TeV with the ATLAS detector at the LHC / Steinberg, Peter (Brookhaven)
Prompt photons are a powerful tool to study heavy ion collisions. [...]
arXiv:1209.4910 ; ATL-PHYS-PROC-2012-203. - 2013. - 5 p.
Original Communication (restricted to ATLAS) - Full text - Full text - Fulltext

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(73)

Testbeam results for a Shashlik calorimeter with longitudinal segmentation
In the frame of R & D for electromagnetic calorimetry at future e+ e- linear colliders different techniques have been studied to implement longitudinal segmentation in Shashlik calorimeters. Two prototypes with 5 multiplied by 5 cm2 lead/scintillator towers and WLS readout have been built. [...]
2000
In : 47th IEEE Nuclear Science Symposium and Medical Imaging Conference, Lyons, France, 15 - 20 Oct 2000, pp.6/100 (v.1)

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(71)

Training and validation of the ATLAS pixel clustering neural networks
The high centre-of-mass energy of the LHC gives rise to dense environments, such as the core of high-pT jets, in which the charge clusters left by ionising particles in the silicon sensors of the pixel detector can merge, compromising the tracking and vertexing efficiency. [...]
ATL-PHYS-PUB-2018-002. - 2018. - 30 p.
Original Communication (restricted to ATLAS) - Full text

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10.

(71)

Hadronic Shower Development in Tile Iron-Scintillator Calorimetry / Kulchitsky, Yuri A. (Dubna, JINR ; Minsk, Inst. Phys.) /TILECAL Collaboration
The lateral and longitudinal profiles of hadronic showers detected by a prototype of the ATLAS Iron-Scintillator Tile Hadron Calorimeter have been investigated. This calorimeter uses a unique longitudinal configuration of scintillator tiles. [...]
hep-ex/9910015; JINR-E1-2000-5; E1-2000-5; JINR-E1-2000-5.- Dubna : Joint Inst. Nucl. Res., 1999 - 11 p. - Published in : , pp. 480-490 Access to fulltext document: PDF; Fulltext: PDF; External link: JINR DUBNA Preprint Server
In : 8th International Conference on Calorimetry in High Energy Physics, Lisbon, Portugal, 13 - 19 Jun 1999, pp.480-490

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