Abstract

A configurable calorimeter simulation for AI (CoCoA) applications is presented, based on the Geant4 toolkit and interfaced with the Pythia event generator. This open-source project is aimed to support the development of machine learning algorithms in high energy physics that rely on realistic particle shower descriptions, such as reconstruction, fast simulation, and low-level analysis. Specifications such as the granularity and material of its nearly hermetic geometry are user-configurable. The tool is supplemented with simple event processing including topological clustering, jet algorithms, and a nearest-neighbors graph construction. Formatting is also provided to visualise events using the Phoenix event display software.

Details

Title
Configurable calorimeter simulation for AI applications
Author
Anton Charkin-Gorbulin 1 ; Cranmer, Kyle 2   VIAFID ORCID Logo  ; Di Bello, Francesco Armando 3 ; Dreyer, Etienne 4   VIAFID ORCID Logo  ; Ganguly, Sanmay 5   VIAFID ORCID Logo  ; Gross, Eilam 4 ; Heinrich, Lukas 6 ; Kado, Marumi 7 ; Kakati, Nilotpal 4 ; Rieck, Patrick 8 ; Santi, Lorenzo 9 ; Tusoni, Matteo 9 

1  University of Luxembourg , Luxembourg, Luxembourg 
2  New York University , New York, United States of America; University of Wisconsin-Madison , Madison, Wisconsin, United States of America 
3  INFN and University of Genova , Genova, Italy 
4  Weizmann Institute of Science , Rehovot, Israel 
5  ICEPP, University of Tokyo , Tokyo, Japan 
6  Technical University of Munich , Munich, Germany 
7  Max Planck Institute for Physics , Munich, Germany; INFN and Sapienza University of Rome , Rome, Italy 
8  New York University , New York, United States of America 
9  INFN and Sapienza University of Rome , Rome, Italy 
First page
035042
Publication year
2023
Publication date
Sep 2023
Publisher
IOP Publishing
e-ISSN
26322153
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1088/2632-2153/acf186
ProQuest document ID
2861327211
Copyright
© 2023 The Author(s). Published by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.