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Abstract

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.

Details

1009240
Title
Offline data processing software for the High Energy cosmic-Radiation Detection facility
Publication title
Volume
337
Source details
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
Number of pages
8
Publication year
2025
Publication date
2025
Publisher
EDP Sciences
Place of publication
Les Ulis
Country of publication
France
Publication subject
ISSN
21016275
e-ISSN
2100014X
Source type
Conference Paper
Language of publication
English
Document type
Conference Proceedings
Publication history
 
 
Online publication date
2025-10-07
Publication history
 
 
   First posting date
07 Oct 2025
ProQuest document ID
3263159904
Document URL
https://www.proquest.com/conference-papers-proceedings/offline-data-processing-software-high-energy/docview/3263159904/se-2?accountid=208611
Copyright
© 2025. This work is licensed under https://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.
Last updated
2025-10-21
Database
ProQuest One Academic