Journal Article

GSI-2021-00718

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png A fast centrality-meter for heavy-ion collisions at the CBM experiment

Omana Kuttan, M. (Corresponding author) ; Steinheimer, J. ; Zhou, K. ; Redelbach, A. ; Stoecker, H.GSI*

2020
North-Holland Publ. Amsterdam

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Please use a persistent id in citations: doi:10.1016/j.physletb.2020.135872  doi:10.15120/GSI-2021-00718

Report No.: arXiv:2009.01584

Abstract: A new method of event characterization based on Deep Learning is presented. The PointNet models can be used for fast, online event-by-event impact parameter determination at the CBM experiment. For this study, UrQMD and the CBM detector simulation are used to generate Au+Au collision events at 10 A GeV which are then used to train and evaluate PointNet based architectures. The models can be trained on features like the hit position of particles in the CBM detector planes, tracks reconstructed from the hits or combinations thereof. The Deep Learning models reconstruct impact parameters from 2-14 fm with a mean error varying from -0.33 to 0.22 fm. For impact parameters in the range of 5-14 fm, a model which uses the combination of hit and track information of particles has a relative precision of 4-9% and a mean error of -0.33 to 0.13 fm. In the same range of impact parameters, a model with only track information has a relative precision of 4-10% and a mean error of -0.18 to 0.22 fm. This new method of event-classification is shown to be more accurate and less model dependent than conventional methods and can utilize the performance boost of modern GPU processor units.

Keyword(s): heavy ion: scattering ; quantum molecular dynamics: relativistic ; CBM ; impact parameter ; neural network ; tracks ; performance ; numerical methods

Note: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP3.

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Contributing Institute(s):

1. Heiße & Dichte QCD Materie (TES)

Research Program(s):

1. 612 - Cosmic Matter in the Laboratory (POF4-612) (POF4-612)

Experiment(s):

1. no experiment theory work (POF3; theory)

Appears in the scientific report 2021

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Database coverage:
; ; ; ; ; Clarivate Analytics Master Journal List ; Current Contents - Physical, Chemical and Earth Sciences ; DOAJ Seal ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; Nationallizenz ; SCOAP3 sponsored Journal ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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