Upgrading the Fast Calorimeter Simulation in ATLAS
Abstract
The tremendous need for simulated samples now and even more so in the future, encourages the development of fast simulation techniques. The Fast Calorimeter Simulation is a faster though less accurate alternative to the full calorimeter simulation with GEANT4. It is based on parametrizing the longitudunal and lateral energy deposits of single particles in the ATLAS calorimeter. Principal component analysis and machine learning techniques are used to improve the performance and decrease the memory need compared to the current version of the ATLAS Fast Calorimeter Simulation. The parametrizations are expanded to cover very high energies and very forward detector regions, to increase the applicability of the tool. A prototype of this upgraded Fast Calorimeter Simulation has been developed and first validations with single particles show substantial improvements over the previous version.
- Authors:
- Publication Date:
- Research Org.:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- Contributing Org.:
- ATLAS collaboration
- OSTI Identifier:
- 1544173
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Conference Series
- Additional Journal Information:
- Journal Volume: 1085; Journal ID: ISSN 1742-6588
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Citation Formats
Schaarschmidt, J. Upgrading the Fast Calorimeter Simulation in ATLAS. United States: N. p., 2018.
Web. doi:10.1088/1742-6596/1085/3/032018.
Schaarschmidt, J. Upgrading the Fast Calorimeter Simulation in ATLAS. United States. https://doi.org/10.1088/1742-6596/1085/3/032018
Schaarschmidt, J. Sat .
"Upgrading the Fast Calorimeter Simulation in ATLAS". United States. https://doi.org/10.1088/1742-6596/1085/3/032018. https://www.osti.gov/servlets/purl/1544173.
@article{osti_1544173,
title = {Upgrading the Fast Calorimeter Simulation in ATLAS},
author = {Schaarschmidt, J.},
abstractNote = {The tremendous need for simulated samples now and even more so in the future, encourages the development of fast simulation techniques. The Fast Calorimeter Simulation is a faster though less accurate alternative to the full calorimeter simulation with GEANT4. It is based on parametrizing the longitudunal and lateral energy deposits of single particles in the ATLAS calorimeter. Principal component analysis and machine learning techniques are used to improve the performance and decrease the memory need compared to the current version of the ATLAS Fast Calorimeter Simulation. The parametrizations are expanded to cover very high energies and very forward detector regions, to increase the applicability of the tool. A prototype of this upgraded Fast Calorimeter Simulation has been developed and first validations with single particles show substantial improvements over the previous version.},
doi = {10.1088/1742-6596/1085/3/032018},
journal = {Journal of Physics. Conference Series},
number = ,
volume = 1085,
place = {United States},
year = {Sat Sep 01 00:00:00 EDT 2018},
month = {Sat Sep 01 00:00:00 EDT 2018}
}
Works referenced in this record:
Geant4—a simulation toolkit
journal, July 2003
- Agostinelli, S.; Allison, J.; Amako, K.
- Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 506, Issue 3
The ATLAS Simulation Infrastructure
journal, September 2010
- Aad, G.; Abbott, B.; Abdallah, J.
- The European Physical Journal C, Vol. 70, Issue 3