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| Main Authors: | , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.02810 |
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| _version_ | 1866915370674159616 |
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| author | Meirose, Bernhard Amaral, Jorge Burgman, Alexander Holl, Matthias Kemp, Ernesto Kozela, Adam Milstead, David Nepomuceno, André Oskarsson, Anders Pysz, Krzysztof Santoro, Valentina Quirino, Tiago Rataj, Blahoslav Silva, Gabriel Silverstein, Samuel Wolke, Magnus Åstrand, Lucas |
| author_facet | Meirose, Bernhard Amaral, Jorge Burgman, Alexander Holl, Matthias Kemp, Ernesto Kozela, Adam Milstead, David Nepomuceno, André Oskarsson, Anders Pysz, Krzysztof Santoro, Valentina Quirino, Tiago Rataj, Blahoslav Silva, Gabriel Silverstein, Samuel Wolke, Magnus Åstrand, Lucas |
| contents | The HIBEAM-NNBAR program is a proposed two-stage experiment at the European Spallation Source focusing on searches for baryon number violation processes as well as ultralight dark matter. This paper presents recent advancements in computing and simulation, including machine learning for event selection, fast parametric simulations for detector studies, and detailed modeling of the time projection chamber and readout electronics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_02810 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Advancements in Computing and Simulation Techniques for the HIBEAM-NNBAR Experiment Meirose, Bernhard Amaral, Jorge Burgman, Alexander Holl, Matthias Kemp, Ernesto Kozela, Adam Milstead, David Nepomuceno, André Oskarsson, Anders Pysz, Krzysztof Santoro, Valentina Quirino, Tiago Rataj, Blahoslav Silva, Gabriel Silverstein, Samuel Wolke, Magnus Åstrand, Lucas Instrumentation and Detectors The HIBEAM-NNBAR program is a proposed two-stage experiment at the European Spallation Source focusing on searches for baryon number violation processes as well as ultralight dark matter. This paper presents recent advancements in computing and simulation, including machine learning for event selection, fast parametric simulations for detector studies, and detailed modeling of the time projection chamber and readout electronics. |
| title | Advancements in Computing and Simulation Techniques for the HIBEAM-NNBAR Experiment |
| topic | Instrumentation and Detectors |
| url | https://arxiv.org/abs/2507.02810 |