Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
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|
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Article Number | 05020 | |
Number of page(s) | 12 | |
Section | Sustainable and Collaborative Software Engineering | |
DOI | https://doi.org/10.1051/epjconf/202429505020 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429505020
Dark Matter Science Project
1 Centre National de la Recherche Scientifique (CNRS)
2 The University of Manchester
3 Technical University of Munich
* e-mail: jared.little@cern.ch
** e-mail: Caterina.Doglioni@cern.ch
*** e-mail: lukas.heinrich@cern.ch
Published online: 6 May 2024
A Dark Matter Science Project is being developed in the context of the ESCAPE (European Science Cluster of Astronomy and Particle physics ESFRI research infrastructure) project as a collaboration between scientists in European Research Infrastructures and experiments seeking to explain the nature of dark matter (such as HL-LHC, KM3NeT, CTA, DarkSide). The goal of this ESCAPE Science Project is to highlight the synergies between different dark matter communities and experiments, by producing new scientific results as well as by making the necessary data and software tools fully available. As part of this Science Project, we use experimental data and software algorithms from selected direct detection, indirect detection, and particle collider experiments involved in ESCAPE as prototypes for end-to-end analysis pipelines on a Virtual Research Environment that is being prepared as one of the building blocks of the European Open Science Cloud (EOSC). This contribution focuses on the implementation of the workflows on the Virtual Research Environment using ESCAPE tools (such as the Data Lake and REANA), and on the prospects for data management, data analysis and computing in the EOSC-Future project.
© The Authors, published by EDP Sciences, 2024
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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