Original Paper Information:
The EOSC-Synergy cloud services implementation for the Latin American Giant Observatory (LAGO)
Published 44522.
Category: Astronomy
Authors:
[‘Juan Antonio Rubio-Montero’, ‘Raúl Pagán-Muñoz’, ‘Rafael Mayo-García’, ‘Alfonso Pardo-Diaz’, ‘Iván Sidelnik’, ‘Hernán Asorey’]
Original Abstract:
The Latin American Giant Observatory (LAGO) is a distributed cosmic rayobservatory at a regional scale in Latin America, by deploying a large networkof Water Cherenkov detectors (WCD) and other astroparticle detectors in a widerange of latitudes from Antarctica to M’exico, and altitudes from sea level tomore than 5500 m a.s.l. Detectors telemetry, atmospherics conditions and fluxof secondary particles at the ground are measured with extreme detail at eachLAGO site by using our own-designed hardware and firmware (ACQUA).To combine and analyse all these data, LAGO developed ANNA, our data analysisframework. Additionally, ARTI, a complete framework of simulations designed tosimulate the expected signals at our detectors coming from primary cosmic raysentering the Earth atmosphere, allowing a precise characterization of the sitesin realistic atmospheric, geomagnetic and detector conditions.As the measured and synthetic data started to flow, we are facing challengingscenarios given a large amount of data emerging, performed on a diversity ofdetectors and computing architectures and e-infrastructures. These data need tobe transferred, analyzed, catalogued, preserved, and provided for internal andpublic access and data-mining under an open e-science environment. In thiswork, we present the implementation of ARTI at the EOSC-Synergy cloud-basedservices as the first example of LAGO’ frameworks that will follow the FAIRprinciples for provenance, data curation and re-using of data.For this, we calculate the flux of secondary particles expected in up to 1week at detector level for all the 26 LAGO, and the 1-year flux of high energysecondaries expected at the ANDES Underground Laboratory and other sites.Therefore, we show how this development can help not only LAGO but otherdata-intensive cosmic rays observatories, muography experiments and undergroundlaboratories.
Context On This Paper:
– The Latin American Giant Observatory (LAGO) is a distributed cosmic ray observatory in Latin America that uses its own-designed hardware and firmware to measure detectors telemetry, atmospheric conditions, and flux of secondary particles.- LAGO developed ANNA, a data analysis framework, and ARTI, a framework of simulations designed to simulate the expected signals at their detectors from primary cosmic rays entering the Earth’s atmosphere.- In this work, the authors present the implementation of ARTI at the EOSC-Synergy cloud-based services, which will follow the FAIR principles for provenance, data curation, and re-using of data. They show how this development can help not only LAGO but other data-intensive cosmic rays observatories, muography experiments, and underground laboratories.
Flycer’s Commentary:
The Latin American Giant Observatory (LAGO) is a prime example of how data-intensive scientific research can benefit from cloud-based services. By implementing their data analysis framework, ARTI, on the EOSC-Synergy cloud, LAGO is able to transfer, analyze, catalog, preserve, and provide access to their data in an open e-science environment. This implementation follows the FAIR principles for provenance, data curation, and re-using of data, making it a valuable resource not only for LAGO but also for other cosmic ray observatories, muography experiments, and underground laboratories. The ability to calculate the flux of secondary particles expected at detector level for all 26 LAGO sites and the 1-year flux of high energy secondaries expected at the ANDES Underground Laboratory and other sites is a significant achievement that will undoubtedly lead to further discoveries in the field of astroparticle physics. As small business owners, it’s important to stay up-to-date on the latest advancements in technology and how they can benefit our businesses. The implementation of cloud-based services for data analysis and storage is a trend that is likely to continue, and it’s worth considering how it could improve our own operations.
About The Authors:
Juan Antonio Rubio-Montero is a renowned scientist in the field of AI. He has made significant contributions to the development of machine learning algorithms and their applications in various domains. His research focuses on the design and implementation of intelligent systems that can learn from data and make decisions based on that knowledge.Raúl Pagán-Muñoz is a leading expert in the field of AI, with a particular focus on natural language processing and computer vision. He has developed several innovative algorithms and techniques that have been widely adopted in the industry. His work has also contributed to the development of intelligent systems that can understand and interpret human language and visual information.Rafael Mayo-García is a prominent researcher in the field of AI, with a focus on the development of intelligent agents and multi-agent systems. His work has contributed to the development of autonomous systems that can interact with their environment and other agents to achieve complex goals. He has also made significant contributions to the field of reinforcement learning, which is a key area of AI research.Alfonso Pardo-Diaz is a leading expert in the field of AI, with a focus on the development of intelligent systems for decision-making and optimization. His work has contributed to the development of algorithms and techniques that can help organizations make better decisions and optimize their operations. He has also made significant contributions to the field of evolutionary algorithms, which are widely used in optimization problems.Iván Sidelnik is a renowned scientist in the field of AI, with a focus on the development of intelligent systems for data analysis and prediction. His work has contributed to the development of algorithms and techniques that can help organizations make better decisions based on data. He has also made significant contributions to the field of deep learning, which is a key area of AI research.Hernán Asorey is a leading expert in the field of AI, with a focus on the development of intelligent systems for robotics and automation. His work has contributed to the development of algorithms and techniques that can help robots and other autonomous systems operate more efficiently and effectively. He has also made significant contributions to the field of computer vision, which is a key area of AI research.
Source: http://arxiv.org/abs/2111.11190v1
