20 citations · 61 across the 21 of their papers we have counts for
7 papers · 1 filter
Construction and commissioning of CMS CE prototype silicon modules
B. Acar, G. Adamov, C. Adloff +327
As part of its HL-LHC upgrade program, the CMS Collaboration is developing a High Granularity Calorimeter (CE) to replace the existing endcap calorimeters. The CE is a sampling cal…
The DAQ system of the 12,000 Channel CMS High Granularity Calorimeter Prototype
B. Acar, G. Adamov, C. Adloff +327
The CMS experiment at the CERN LHC will be upgraded to accommodate the 5-fold increase in the instantaneous luminosity expected at the High-Luminosity LHC (HL-LHC). Concomitant wit…
Muon Energy Measurement from Radiative Losses in a Calorimeter for a Collider Detector
Tommaso Dorigo, Jan Kieseler, Lukas Layer +1
The performance demands of future particle-physics experiments investigating the high-energy frontier pose a number of new challenges, forcing us to find new solutions for the dete…
Jet Flavour Classification Using DeepJet
Emil Bols, Jan Kieseler, Mauro Verzetti +2
Jet flavour classification is of paramount importance for a broad range of applications in modern-day high-energy-physics experiments, particularly at the LHC. In this paper we pro…
Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics
Yutaro Iiyama, Gianluca Cerminara, Abhijay Gupta +19
Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet tagging, and clustering…
Fast convolutional neural networks for identifying long-lived particles in a high-granularity calorimeter
Juliette Alimena, Yutaro Iiyama, Jan Kieseler
We present a first proof of concept to directly use neural network based pattern recognition to trigger on distinct calorimeter signatures from displaced particles, such as those t…