Issue |
EPJ Web Conf.
Volume 214, 2019
23rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|
|
---|---|---|
Article Number | 05027 | |
Number of page(s) | 8 | |
Section | T5 - Software development | |
DOI | https://doi.org/10.1051/epjconf/201921405027 | |
Published online | 17 September 2019 |
https://doi.org/10.1051/epjconf/201921405027
The BmnRoot framework for experimental data processing in the BM@N experiment at NICA
,
Veksler and Baldin Laboratory of High Energy Physics, JINR,
141980
Dubna,
Russia
* e-mail: gertsen@jinr.ru
# on behalf of the BM@N collaboration
Published online: 17 September 2019
A new generation of experiments for the relativistic nuclear physics is expected to be started up in the nearest years at the Nuclotron-based Ion Collider fAcility (NICA) under construction at the Joint Institute for Nuclear Research in Dubna. The main part of the facility is the essentially modernized accelerator Nuclotron. BM@N (Baryonic Matter at Nuclotron) is considered as a first stage towards realization of physics program available at NICA. It is a fixed target experiment aimed to work with the Nuclotron extracted beams of different species. The experiment had a set of technical runs since 2015. For a successful realization of the BM@N physics program, a well developed and tested software for simulation, digitization, reconstruction and analysis of collision events and other additional tasks is of utmost importance. The BmnRoot software developed in order to operate the mentioned tasks is described in this article. It includes modules for data digitizing obtained from BM@N detector systems, realistic simulation of signals in detectors, alignment of detectors, reconstruction of multiparticle interaction events, as well as all necessary systems for maintaining the databases of the experiment, visualization and providing information support for the experiment.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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