The Astronomical Journal (Jan 2024)

Firmamento: A Multimessenger Astronomy Tool for Citizen and Professional Scientists

  • Dhurba Tripathi,
  • Paolo Giommi,
  • Adriano Di Giovanni,
  • Rawdha R. Almansoori,
  • Nouf Al Hamly,
  • Francesco Arneodo,
  • Andrea V. Macciò,
  • Goffredo Puccetti,
  • Ulisses Barres de Almeida,
  • Carlos Brandt,
  • Simonetta Di Pippo,
  • Michele Doro,
  • Davit Israyelyan,
  • A. M. T. Pollock,
  • Narek Sahakyan

DOI
https://doi.org/10.3847/1538-3881/ad216a
Journal volume & issue
Vol. 167, no. 3
p. 116

Abstract

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Firmamento ( https://firmamento.hosting.nyu.edu ) is a new-concept, web-based, and mobile-friendly data analysis tool dedicated to multifrequency/multimessenger emitters, as exemplified by blazars. Although initially intended to support a citizen researcher project at New York University–Abu Dhabi, Firmamento has evolved to be a valuable tool for professional researchers due to its broad accessibility to classical and contemporary multifrequency open data sets. From this perspective Firmamento facilitates the identification of new blazars and other multifrequency emitters in the localization uncertainty regions of sources detected by current and planned observatories such as Fermi-LAT, Swift, eROSITA, CTA, ASTRI Mini-Array, LHAASO, IceCube, KM3Net, SWGO, etc. The multiepoch and multiwavelength data that Firmamento retrieves from over 90 remote and local catalogs and databases can be used to characterize the spectral energy distribution and the variability properties of cosmic sources as well as to constrain physical models. Firmamento distinguishes itself from other online platforms due to its high specialization, the use of machine learning and other methodologies to characterize the data, and for its commitment to inclusivity. From this particular perspective, its objective is to assist both researchers and citizens interested in science, strengthening a trend that is bound to gain momentum in the coming years as data retrieval facilities improve in power and machine-learning/artificial-intelligence tools become more widely available.

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