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| 001 | 481363 | ||
| 005 | 20220810211447.0 | ||
| 037 | _ | _ | |a PUBDB-2022-04336 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Scham, Moritz |0 P:(DE-H253)PIP1088880 |b 0 |e Corresponding author |
| 111 | 2 | _ | |a Center for Data and Computing in Natural Sciences (CDCS) Symposium |g CDCS2022 |c Hamburg |d 2022-04-26 - 2022-04-28 |w Germany |
| 245 | _ | _ | |a Generative modeling with Graph Neural Networks for the CMS HGCal |
| 260 | _ | _ | |c 2022 |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a CONFERENCE_POSTER |2 ORCID |
| 336 | 7 | _ | |a Output Types/Conference Poster |2 DataCite |
| 336 | 7 | _ | |a Poster |b poster |m poster |0 PUB:(DE-HGF)24 |s 1660136150_1173 |2 PUB:(DE-HGF) |
| 520 | _ | _ | |a In high energy physics, detailed and time-consuming simulations are used for particle interactions with detectors. For the upcoming High-Luminosity phase of the Large Hadron Collider (HL-LHC), the computational costs of conventional simulation tools exceeds the projected computational resources. Generative machine learning is expected to provide a fast and accurate alternative. The CMS experiment at the LHC will use a new High Granularity Calorimeter (HGCal) to cope with the high particle density. The new HGCal is an imaging calorimeter with a complex geometry and more than 3 million cells. We report on the development of a GraphGAN to simulate particle showers under these challenging conditions. |
| 536 | _ | _ | |a 611 - Fundamental Particles and Forces (POF4-611) |0 G:(DE-HGF)POF4-611 |c POF4-611 |f POF IV |x 0 |
| 693 | _ | _ | |a LHC |e LHC: CMS |1 EXP:(DE-588)4398783-7 |0 EXP:(DE-H253)LHC-Exp-CMS-20150101 |5 EXP:(DE-H253)LHC-Exp-CMS-20150101 |x 0 |
| 700 | 1 | _ | |a Bhattacharya, Soham |0 P:(DE-H253)PIP1094654 |b 1 |u desy |
| 700 | 1 | _ | |a Borras, Kerstin |0 P:(DE-H253)PIP1002900 |b 2 |u desy |
| 700 | 1 | _ | |a Bein, Sam |b 3 |
| 700 | 1 | _ | |a Eren, Engin |b 4 |
| 700 | 1 | _ | |a Gaede, Frank |b 5 |
| 700 | 1 | _ | |a Kasieczka, Gregor |b 6 |
| 700 | 1 | _ | |a Korcari, William |b 7 |
| 700 | 1 | _ | |a Krücker, Dirk |0 P:(DE-H253)PIP1005319 |b 8 |u desy |
| 700 | 1 | _ | |a McKeown, Peter |b 9 |
| 700 | 1 | _ | |a CMS Collaboration |0 P:(DE-HGF)0 |b 10 |e Collaboration author |
| 856 | 4 | _ | |u https://indico.desy.de/event/31214/contributions/120857/ |
| 856 | 4 | _ | |u https://bib-pubdb1.desy.de/record/481363/files/HelmholtzAI-VC21-DeGeSim.pdf |y Restricted |
| 856 | 4 | _ | |u https://bib-pubdb1.desy.de/record/481363/files/HelmholtzAI-VC21-DeGeSim.pdf?subformat=pdfa |x pdfa |y Restricted |
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| 910 | 1 | _ | |a Deutsches Elektronen-Synchrotron |0 I:(DE-588b)2008985-5 |k DESY |b 0 |6 P:(DE-H253)PIP1088880 |
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| 910 | 1 | _ | |a Deutsches Elektronen-Synchrotron |0 I:(DE-588b)2008985-5 |k DESY |b 8 |6 P:(DE-H253)PIP1005319 |
| 910 | 1 | _ | |a Deutsches Elektronen-Synchrotron |0 I:(DE-588b)2008985-5 |k DESY |b 10 |6 P:(DE-HGF)0 |
| 913 | 1 | _ | |a DE-HGF |b Forschungsbereich Materie |l Matter and the Universe |1 G:(DE-HGF)POF4-610 |0 G:(DE-HGF)POF4-611 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-600 |4 G:(DE-HGF)POF |v Fundamental Particles and Forces |x 0 |
| 914 | 1 | _ | |y 2022 |
| 920 | 1 | _ | |0 I:(DE-H253)CMS-20120731 |k CMS |l LHC/CMS Experiment |x 0 |
| 980 | _ | _ | |a poster |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-H253)CMS-20120731 |
| 980 | _ | _ | |a UNRESTRICTED |
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