TY  - CONF
AU  - McKeown, Peter
AU  - Gaede, Frank
AU  - Krüger, Katja
AU  - Eren, Engin
AU  - Korol, Anatolii
AU  - Rustige, Lennart
AU  - Bieringer, Sebastian Guido
AU  - Buhmann, Erik
AU  - Diefenbacher, Sascha Daniel
AU  - Kasieczka, Gregor
AU  - Korcari, William
AU  - Shekhzadeh, Imahn
TI  - Generative Models for Fast Simulation of Electromagnetic and Hadronic Showers in Highly Granular Calorimeters
JO  - Proceedings of Science / International School for Advanced Studies
VL  - (ICHEP2022)
IS  - DESY-22-188
SN  - 1824-8039
CY  - Trieste
PB  - SISSA
M1  - PUBDB-2022-06817
M1  - DESY-22-188
SP  - 236
PY  - 2023
AB  - While simulation is a crucial cornerstone of modern high energy physics, it places a heavy burden on the available computing resources. These computing pressures are expected to become a major bottleneck for the upcoming high luminosity phase of the LHC and for future colliders, motivating a concerted effort to develop computationally efficient solutions. Methods based on generative machine learning models hold promise to alleviate the computational strain produced by simulation, while providing the physical accuracy required of a surrogate simulator.This contribution provides an overview of a growing body of work focused on simulating showers in highly granular calorimeters, which is making significant strides towards realising fast simulation tools based on deep generative models. Progress on the simulation of both electromagnetic and hadronic showers will be reported, with a focus on the high degree of physical fidelity achieved. Additional steps taken to address the challenges faced when broadening the scope of these simulators, such as those posed by multi-parameter conditioning, will also be discussed.
T2  - 41st International Conference on High Energy Physics
CY  - 6 Jul 2022 - 13 Jul 2022, Bologna (Italy)
Y2  - 6 Jul 2022 - 13 Jul 2022
M2  - Bologna, Italy
LB  - PUB:(DE-HGF)16 ; PUB:(DE-HGF)8
DO  - DOI:10.22323/1.414.0236
UR  - https://bib-pubdb1.desy.de/record/485749
ER  -