Open Access
| Issue |
EPJ Web Conf.
Volume 251, 2021
25th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2021)
|
|
|---|---|---|
| Article Number | 03012 | |
| Number of page(s) | 10 | |
| Section | Offline Computing | |
| DOI | https://doi.org/10.1051/epjconf/202125103012 | |
| Published online | 23 August 2021 | |
- ATLAS collaboration, The ATLAS Experiment at the CERN Large Hadron Collider, JINST 3, S08003 (2008) [Google Scholar]
- L. Evans, P. Bryant, LHC Machine, Journal of Instrumentation 3, S08001 (2008) [Google Scholar]
- S. Agostinelli et al., Geant4—a simulation toolkit, Nucl. Instrum. Meth. A 506, 250–303 (2003) [Google Scholar]
- J. Allison et al., Geant4 developments and applications, IEEE T Nucl. Sci. 53, 270–278 (2006) [Google Scholar]
- P. Calafiura, J. Catmore, D. Costanzo, A. Di Girolamo, ATLAS HL-LHC Computing Conceptual Design Report, CERN-LHCC-2020-015 (2020) [Google Scholar]
- T. Yamanaka, The ATLAS calorimeter simulation FastCaloSim, J. Phys. Conf. Ser. 331 032053 [Google Scholar]
- ATLAS collaboration, The ATLAS Simulation Infrastructure, Eur. Phys. J. C70: 823–874 (2010) doi: 10.1088/1742-6596/523/1/012035 [Google Scholar]
- K. Edmonds, S. Fleischmann, T. Lenz, C. Magass, J. Mechnich, A. Salzburger, The Fast ATLAS Track Simulation (FATRAS), ATL-SOFT-PUB-2008-001 (2008), https://cds.cern.ch/record/1091969 [Google Scholar]
- ATLAS collaboration, AtlFast3: Next Generation of Fast Simulation in ATLAS, Computing and Software for Big Science, in press (2021) [Google Scholar]
- ATLAS collaboration, The new Fast Calorimeter Simulation in ATLAS, ATL-SOFT-PUB-2018-002 (2018), http://cds.cern.ch/record/2630434 [Google Scholar]
- ATLAS collaboration, Fast simulation of the ATLAS calorimeter system with Generative Adversarial Networks, ATL-SOFT-PUB-2020-006 (2020), https://cds.cern.ch/record/2746032 [Google Scholar]
- Athena, https://doi.org/10.5281/zenodo.2641997 [Google Scholar]
- ATLAS collaboration, Emulating the impact of additional proton-proton interactions in the ATLAS simulation by pre-sampling sets of inelastic Monte Carlo events, arXiv arXiv:2102.09495 (2021) [Google Scholar]
- CMS collaboration, Upgrades for the CMS simulation, J. Phys.: Conf. Ser. 608 012056 (2015) [Google Scholar]
- Ch. Gumpert, A. Salzburger, M. Kiehn, J. Hrdinka, N. Calace, ACTS: from ATLAS software towards a common track reconstruction software, J. Phys. Conf. Ser. 898 (2017) 042011 [Google Scholar]
- E. Ritsch, Concepts and Plans towards fast large scale MonteCarlo production for the ATLAS Experiment, J. Phys. Conf. Ser. 523, 012035 (2014), doi: 10.1088/1742-6596/523/1/012035 [Google Scholar]
- A. Basalaev, Z. Marshall, The Fast Simulation Chain for ATLAS, J. Phys. Conf. Ser. 898, 042016 (2017), doi: 10.1088/1742-6596/898/4/042016 [Google Scholar]
- R. Jansky, The ATLAS Fast Monte Carlo Production Chain Project, J. Phys. Conf. Ser. 664, 072024 (2015), doi: 10.1088/1742-6596/664/7/072024 [Google Scholar]
- E. Ritsch et al., Modernising ATLAS Software Build Infrastructure, J. Phys.: Conf. Ser. 1085, 032033 (2018), doi: 10.1088/1742-6596/1085/3/032033 [Google Scholar]
- T. Cuhadar-Donszelmann, W. Lampl, G.A. Stewart, ART ATLAS Release Tester using the Grid, EPJ Web Conf. 245, 05015 (2020), doi: 10.1051/epjconf/202024505015 [Google Scholar]
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