Data Science Journal (Mar 2020)

MASER: A Science Ready Toolbox for Low Frequency Radio Astronomy

  • Baptiste Cecconi,
  • Alan Loh,
  • Pierre Le Sidaner,
  • Renaud Savalle,
  • Xavier Bonnin,
  • Quynh Nhu Nguyen,
  • Sonny Lion,
  • Albert Shih,
  • Stéphane Aicardi,
  • Philippe Zarka,
  • Corentin Louis,
  • Andrée Coffre,
  • Laurent Lamy,
  • Laurent Denis,
  • Jean-Mathias Grießmeier,
  • Jeremy Faden,
  • Chris Piker,
  • Nicolas André,
  • Vincent Génot,
  • Stéphane Erard,
  • Joseph N. Mafi,
  • Todd A. King,
  • Jim Sky,
  • Markus Demleitner

DOI
https://doi.org/10.5334/dsj-2020-012
Journal volume & issue
Vol. 19, no. 1

Abstract

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MASER (Measurements, Analysis, and Simulation of Emission in the Radio range) is a comprehensive infrastructure dedicated to time-dependent low frequency radio astronomy (up to about 50 MHz). The main radio sources observed in this spectral range are the Sun, the magnetized planets (Earth, Jupiter, Saturn), and our Galaxy, which are observed either from ground or space. Ground observatories can capture high resolution data streams with a high sensitivity. Conversely, space-borne instruments can observe below the ionospheric cut-off (at about 10 MHz) and can be placed closer to the studied object. Several tools have been developed in the last decade for sharing space physics data. Data visualization tools developed by various institutes are available to share, display and analyse space physics time series and spectrograms. The MASER team has selected a sub-set of those tools and applied them to low frequency radio astronomy. MASER also includes a Python software library for reading raw data from agency archives.

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