[論文レビュー] From a Network to a Networking: The Evolution of the Latin American Giant Observatory

C. Sarmiento-Cano, H. Asorey+12 more|arXiv (Cornell University)|Jan 15, 2026

Astrophysics and Cosmic Phenomena被引用数 0

ひとこと要約

The paper surveys how LAGO evolved from a high-altitude gamma-ray burst detector network into a multidisciplinary, open-science, digitally integrated observatory with ARTI-MEIGA, edge computing, and educational partnerships, enabling new applications across space weather, muography, and environmental monitoring.

ABSTRACT

The Latin American Giant Observatory (LAGO) is a collaborative initiative that deploys a network of low-cost, autonomous Water Cherenkov Detectors across Latin America and Spain. Initially focused on detecting gamma-ray bursts at high-altitude sites, LAGO has evolved into a multidisciplinary forum for astroparticle physics, space weather studies, and environmental monitoring. Its detectors operate from sea level to over 4300 meters above sea level (m a.s.l.) in diverse geomagnetic and atmospheric conditions. The ARTI-MEIGA simulation framework is a key development that models the entire cosmic-ray interaction chain, enabling site-specific simulations to be integrated into FAIR-compliant workflows. LAGO also plays a significant role in regional education and training through partnerships with ERASMUS+ projects, positioning itself as a hub for research capacity building. New contributions emerging from the collaboration include volcano muography, neutron hydrometry for precision agriculture, and space weather monitoring in the South Atlantic Magnetic Anomaly. LAGO demonstrates how Cherenkov-based detection and open science can drive scientific discovery and practical innovation.

研究の動機と目的

• Describe the origin and growth of the LAGO collaboration from a detector network to a multidisciplinary observatory.
• Highlight the core technology: water Cherenkov detectors, open-source hardware, and the appliance mindset for deployment across diverse environments.
• Explain the ARTI-MEIGA simulation framework and its role in site- and mission-specific analyses.
• Discuss advanced digital innovations (edge computing, blockchain, FAIR workflows) and their impact on data integrity and interoperability.
• Illustrate educational, capacity-building, and regional societal impacts via ERASMUS+ collaborations and new application areas.

提案手法

• Describe the LAGO network architecture and detector design (Water Cherenkov Detectors, PMTs, and calibration methods).
• Summarize the ARTI-MEIGA simulation pipeline and its integration with FAIR-compliant workflows and cloud deployment.
• Explain the transition to an appliance-based deployment model with standardized hardware/firmware interfaces.
• Outline edge computing and blockchain use for data preprocessing, trust, and on-chain metadata with off-chain data storage.
• Present extensions including neutron detection enhancements, SiPM adoption via C-ARAPUCA concepts, and muography workflows.
• Describe educational partnerships and ERASMUS+ capacity-building projects supporting training and open-data practices.

実験結果

リサーチクエスチョン

• RQ1 How has LAGO transformed from a detector network into a distributed, software-enabled scientific network across Latin America and Spain?
• RQ2 What are the key technological and organizational innovations enabling site-specific simulations, reproducible deployments, and open-data practices in LAGO?
• RQ3 What new scientific and societal applications emerge from LAGO’s expanded capabilities (e.g., muography, space weather, smart agriculture, SAA studies)?
• RQ4 How do ARTI-MEIGA, edge computing, and blockchain contribute to data integrity, FAIR compliance, and operational efficiency across a distributed observatory?
• RQ5 What role do international partnerships (ERASMUS+ and others) play in capacity building and education within the LAGO framework?

主な発見

• LAGO evolved from high-altitude gamma-ray burst detectors to a multidisciplinary observatory with space weather and environmental monitoring programs.
• ARTI-MEIGA provides a configurable, publicly available simulation chain for modeling cosmic-ray interactions and detector responses across sites.
• Edge computing and permissioned blockchain enable distributed data processing, trust, and FAIR-compliant workflows while reducing bandwidth needs.
• ERASMUS+ CBHE partnerships (e.g., LA-CoNGA, EL-BONGÓ) support capacity building and hands-on training via distributed detectors and live data streams.
• New contributions include muography for volcanology, neutron hydrometry for agriculture, and space weather studies in the South Atlantic Magnetic Anomaly.
• Neutron-detection enhancements (NaCl-doped water) and SiPM-based sensor upgrades (C-ARAPUCA concepts) expand detector capabilities.