| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01155 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/epjconf/202533701155 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701155
Offline data processing software for the High Energy cosmic-Radiation Detection facility
Key Laboratory of Particle Physics and Particle Irradiation (MOE), Institute of Frontier and Interdisciplinary Science, Shandong University, Qingdao, Shandong, 266327, China
* e-mail: shiqq@mail.sdu,edu,cn
** e-mail: tengli@sdu.edu.cn
*** e-mail: huangxt@sdu.edu.cn
Published online: 7 October 2025
The High Energy cosmic-Radiation Detection (HERD) facility was proposed as a space cosmic-ray and gamma-ray detector onboard China’s Space Station around 2027. The primary scientific objectives of HERD include searching for dark matter particles, studying the energy spectrum and composition of cosmic rays, and conducting high energy gamma-ray astronomy. The HERD offline software (HERDOS) is designed and developed based on SNiPER, a lightweight framework for high energy physics (HEP) experiments. HERDOS is designed to provide the common data processing functionalities and also responsible for building the offline data processing chain, which encompasses detector simulation, calibration, reconstruction, and data analysis. Several common HEP software toolkits, such as Geant4, ROOT, DD4hep, PODIO, and TBB, have also been integrated into HERDOS. This paper describes the design and implementation of the core software of the HERDOS, including the event data and detector data management system, parallelized simulation framework and database system. Currently, HERDOS operates at full capacity to support the conceptual design of detectors, conduct detector performance studies, and physics potential study.
© The Authors, published by EDP Sciences, 2025
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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