The EOSC-Synergy cloud services implementation for the Latin American Giant Observatory (LAGO) [IMA]

http://arxiv.org/abs/2111.11190


The Latin American Giant Observatory (LAGO) is a distributed cosmic ray observatory at a regional scale in Latin America, by deploying a large network of Water Cherenkov detectors (WCD) and other astroparticle detectors in a wide range of latitudes from Antarctica to M\’exico, and altitudes from sea level to more than 5500 m a.s.l. Detectors telemetry, atmospherics conditions and flux of secondary particles at the ground are measured with extreme detail at each LAGO site by using our own-designed hardware and firmware (ACQUA).
To combine and analyse all these data, LAGO developed ANNA, our data analysis framework. Additionally, ARTI, a complete framework of simulations designed to simulate the expected signals at our detectors coming from primary cosmic rays entering the Earth atmosphere, allowing a precise characterization of the sites in realistic atmospheric, geomagnetic and detector conditions.
As the measured and synthetic data started to flow, we are facing challenging scenarios given a large amount of data emerging, performed on a diversity of detectors and computing architectures and e-infrastructures. These data need to be transferred, analyzed, catalogued, preserved, and provided for internal and public access and data-mining under an open e-science environment. In this work, we present the implementation of ARTI at the EOSC-Synergy cloud-based services as the first example of LAGO’ frameworks that will follow the FAIR principles for provenance, data curation and re-using of data.
For this, we calculate the flux of secondary particles expected in up to 1 week at detector level for all the 26 LAGO, and the 1-year flux of high energy secondaries expected at the ANDES Underground Laboratory and other sites. Therefore, we show how this development can help not only LAGO but other data-intensive cosmic rays observatories, muography experiments and underground laboratories.

Read this paper on arXiv…

J. Rubio-Montero, R. Pagán-Muñoz, R. Mayo-García, et. al.
Tue, 23 Nov 21
32/84

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