60 citations · 170 across the 10 of their papers we have counts for
17 papers
Shower Separation in Five Dimensions for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +48
To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to se…
Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter
M. Aamir, G. Adamov, T. Adams +568
A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transv…
Software Compensation for Highly Granular Calorimeters using Machine Learning
S. Lai, J. Utehs, A. Wilhahn +61
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 in…
Timing Performance of the CMS High Granularity Calorimeter Prototype
CMS HGCAL collaboration
This paper describes the experience with the calibration, reconstruction and evaluation of the timing capabilities of the CMS HGCAL prototype in the beam tests in 2018. The calibra…
CaloClouds II: Ultra-Fast Geometry-Independent Highly-Granular Calorimeter Simulation
Erik Buhmann, Frank Gaede, Gregor Kasieczka +4
Fast simulation of the energy depositions in high-granular detectors is needed for future collider experiments with ever-increasing luminosities. Generative machine learning (ML) m…
CaloClouds: Fast Geometry-Independent Highly-Granular Calorimeter Simulation
Erik Buhmann, Sascha Diefenbacher, Engin Eren +6
Simulating showers of particles in highly-granular detectors is a key frontier in the application of machine learning to particle physics. Achieving high accuracy and speed with ge…
New Angles on Fast Calorimeter Shower Simulation
Sascha Diefenbacher, Engin Eren, Frank Gaede +5
The demands placed on computational resources by the simulation requirements of high energy physics experiments motivate the development of novel simulation tools. Machine learning…
Performance of the CMS High Granularity Calorimeter prototype to charged pion beams of 20300 GeV/c
B. Acar, G. Adamov, C. Adloff +454
The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimete…
Description and stability of a RPC-based calorimeter in electromagnetic and hadronic shower environments
D. Boumediene, V. Francais, J. Apostolakis +36
The CALICE Semi-Digital Hadron Calorimeter technological prototype completed in 2011 is a sampling calorimeter using Glass Resistive Plate Chamber (GRPC) detectors as the active me…
Hadrons, Better, Faster, Stronger
Erik Buhmann, Sascha Diefenbacher, Engin Eren +7
Motivated by the computational limitations of simulating interactions of particles in highly-granular detectors, there exists a concerted effort to build fast and exact machine-lea…
Response of a CMS HGCAL silicon-pad electromagnetic calorimeter prototype to 20-300 GeV positrons
B. Acar, G. Adamov, C. Adloff +385
The Compact Muon Solenoid Collaboration is designing a new high-granularity endcap calorimeter, HGCAL, to be installed later this decade. As part of this development work, a protot…
Measurement of lepton-jet correlation in deep-inelastic scattering with the H1 detector using machine learning for unfolding
H1 Collaboration, V. Andreev, M. Arratia +142
The first measurement of lepton-jet momentum imbalance and azimuthal correlation in lepton-proton scattering at high momentum transfer is presented. These data, taken with the H1 d…
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…
Software compensation in Particle Flow reconstruction
Huong Lan Tran, Katja Krüger, Felix Sefkow +4
The particle flow approach to calorimetry benefits from highly granular calorimeters and sophisticated software algorithms in order to reconstruct and identify individual particles…
Tracking within Hadronic Showers in the CALICE SDHCAL prototype using a Hough Transform Technique
The CALICE Collaboration
The high granularity of the CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) provides the capability to reveal the track segments present in hadronic showers. These segments are t…
Shower development of particles with momenta from 15 GeV to 150 GeV in the CALICE scintillator-tungsten hadronic calorimeter
The CALICE collaboration, M. Chefdeville, Y. Karyotakis +178
We present a study of showers initiated by electrons, pions, kaons, and protons with momenta from 15 GeV to 150 GeV in the highly granular CALICE scintillator-tungsten analogue had…
Pion and proton showers in the CALICE scintillator-steel analogue hadron calorimeter
The CALICE Collaboration, B. Bilki, J. Repond +169
Showers produced by positive hadrons in the highly granular CALICE scintillator-steel analogue hadron calorimeter were studied. The experimental data were collected at CERN and FNA…