| Autor: |
Mainetti Gabriele, Hernandez Fabio, Jammes Fabrice, Le Boulc’h Quentin |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
EPJ Web of Conferences, Vol 295, p 07017 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2100-014X |
| DOI: |
10.1051/epjconf/202429507017 |
| Popis: |
The Vera C. Rubin Observatory is preparing for the execution of the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently in its final phase of construction in the Andes mountains in Chile and due to start operations in 2025 for 10 years, its 8.4-meter telescope will nightly scan the southern sky and collect images of the entire visible sky every 4 nights using a 3.2 Gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this paper, we briefly present the infrastructure deployed at the French Rubin data facility (operated by IN2P3 computing center, CC-IN2P3) to deploy the Rubin Science Platform, a set of web-based services to provide effective and convenient access to LSST data for scientific analysis. We describe the main services of the platform, the components that provide those services and our deployment model. We also present the Kubernetes-based infrastructure we are experimenting with for hosting the LSST astronomical catalog, a petabyte-scale relational database developed for the specific needs of the project. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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