Publications
Publication Information
| Title | The CLAS12 Geant4 Simulation |
| Authors | Maurizio Ungaro, Marco Battaglieri, Marco Contalbrigo, Volker Burkert, Daniel Carman, Pierre Chatagnon, Maxime Defurne, Burcu Duran, Raffaella De Vita, Ruben Fair, Michel Garcon, Yuri Gotra, Probir Ghoshal, Renuka Rajput-Ghoshal, Sylvester Joosten, Giovanni Angelini, Andrey Kim, Daniel Lersch, Nikolay Markov, Mac Mestayer, Robert Miller, Marco Mirazita, Joseph Newton, Silvia Niccolai, William Phelps, Sebastien Procureur, Yelena Prok, Andrew Puckett, Youri Sharabian, Daria Sokhan, Armenak Stepanyan, Rong Wang, Cyril Wiggins, Veronique Ziegler |
| JLAB number | JLAB-PHY-19-3124 |
| LANL number | (None) |
| Other number | DOE/OR/23177-4867 |
| Document Type(s) | (Journal Article) |
| Associated with EIC: | No |
| Supported by Jefferson Lab LDRD Funding: | No |
| Funding Source: | Nuclear Physics (NP) |
|
Journal Compiled for Nuclear Instruments & Methods in Physics Research, Section A Volume 959 Page(s) 163422 Refereed | |
| Publication Abstract: | The Geant4 Monte-Carlo (GEMC) package is used to simulate the passage of particles through the various CLAS12 detectors. The geometry is implemented through a database of Geant4 volumes created either through the GEMC native API, by the CLAS12 geometry service, or imported from the CAD engineering model. The truth information is digitized with a plugin mechanism by routines specific to each detector and includes the use of the CLAS12 calibration database constants to produce both ADC and TDC response functions. Theoretical models that produce the generated events interface with GEMC through the LUND data format. The merging of simulated data with real random trigger data provides a mechanism to include both beam and electronic background into the simulation of generated events to accurately model beam data from the CLAS12 detector. The performance of simulation is demonstrated by comparison with the experimental data. |
| Experiment Numbers: | |
| Group: | Hall B |
| Document: | |
| DOI: | https://doi.org/10.1016/j.nima.2020.163422 |
| Accepted Manuscript: | simulations1.pdf |
| Supporting Documents: | |
| Supporting Datasets: | |