Karabo: A versatile SKA Observation Simulation Framework
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arXiv
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| Autores principales: | , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866913771548573696 |
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| author | Sharma, Rohit Felix, Simon Valle, Luis Fernando Machado Poletti Timmel, Vincenzo Gehrig, Lukas Wassmer, Andreas Studer, Jennifer Hitz, Pascal Schramka, Filip Bianco, Michele Crichton, Devin Spinelli, Marta Csillaghy, André Kögel, Stefan Réfrégier, Alexandre |
| author_facet | Sharma, Rohit Felix, Simon Valle, Luis Fernando Machado Poletti Timmel, Vincenzo Gehrig, Lukas Wassmer, Andreas Studer, Jennifer Hitz, Pascal Schramka, Filip Bianco, Michele Crichton, Devin Spinelli, Marta Csillaghy, André Kögel, Stefan Réfrégier, Alexandre |
| contents | Karabo is a versatile Python-based software framework simplifying research with radio astronomy data. It bundles existing software packages into a coherent whole to improve the ease of use of its components. Karabo includes useful abstractions, like strategies to scale and parallelize typical workloads or science-specific Python modules. The framework includes functionality to access datasets and mock observations to study the Square Kilometer Array (SKA) instruments and their expected accuracy. SKA will address problems in a wide range of fields of astronomy. We demonstrate the application of Karabo to some of the SKA science cases from HI intensity mapping, mock radio surveys, radio source detection, the epoch of re-ionisation and heliophysics. We discuss the capabilities and challenges of simulating large radio datasets in the context of SKA. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_00303 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Karabo: A versatile SKA Observation Simulation Framework Sharma, Rohit Felix, Simon Valle, Luis Fernando Machado Poletti Timmel, Vincenzo Gehrig, Lukas Wassmer, Andreas Studer, Jennifer Hitz, Pascal Schramka, Filip Bianco, Michele Crichton, Devin Spinelli, Marta Csillaghy, André Kögel, Stefan Réfrégier, Alexandre Instrumentation and Methods for Astrophysics Karabo is a versatile Python-based software framework simplifying research with radio astronomy data. It bundles existing software packages into a coherent whole to improve the ease of use of its components. Karabo includes useful abstractions, like strategies to scale and parallelize typical workloads or science-specific Python modules. The framework includes functionality to access datasets and mock observations to study the Square Kilometer Array (SKA) instruments and their expected accuracy. SKA will address problems in a wide range of fields of astronomy. We demonstrate the application of Karabo to some of the SKA science cases from HI intensity mapping, mock radio surveys, radio source detection, the epoch of re-ionisation and heliophysics. We discuss the capabilities and challenges of simulating large radio datasets in the context of SKA. |
| title | Karabo: A versatile SKA Observation Simulation Framework |
| topic | Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2504.00303 |