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| Home > Publications database > Survey of Astrophysics Simulation Codes in Germany: An Initiative of the PUNCH4NFDI Consortium |
| Home > Publications database > Survey of Astrophysics Simulation Codes in Germany: An Initiative of the PUNCH4NFDI Consortium |
| Conference Presentation (After Call) | FZJ-2023-05419 |
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2023
Abstract: PUNCH4NFDI is the consortium of particle and astroparticle physics, astrophysics, and hadronic and nuclear physics in the national research data infrastructure of Germany. It aims at developing concepts and tools for efficient management of digital research products in fundamental physics and promotes the idea of FAIR data - which is to make scientific data sets findable, accessible, interoperable, and reusable. To better understand the software usage of the astrophysics community in Germany, PUNCH4NFDI developed a 9-question survey and disseminated it via various distribution channels (mailing list, conference flyer, personal communication) in 2022. In total, 130 computational astrophysicists responded to our survey. We found that parallel codes (like AREPO) to simulate gravitational N-body systems and magnetohydrodynamics are heavily used in the German astrophysics community. However, computer programs typically associated with research in solar physics and numerical relativity turned out to be less common among the participating astrophysicists. Regarding to code development and sharing of astrophysical HPC applications, the picture is divided. On the one hand, some codes are developed by and limited to a single research group in Germany; on the other hand, some codes are maintained and used by large consortia spread around the globe. In both cases, often a basic software version is open access, but numerous scientists indicated the usage of modified and unreleased versions. We also found that most astrophysicists in Germany view re-using other researchers' data sets as highly desirable. While smaller research groups are in principle willing to publish and openly share their simulation data, they often lack manpower to do so.
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