# MASER: A Science Ready Toolbox for Low Frequency Radio Astronomy

**Authors:** Baptiste Cecconi, Alan Loh, Pierre Le Sidaner, Renaud Savalle, Xavier, Bonnin, Quynh Nhu Nguyen, Sonny Lion, Albert Shih, St\'ephane Aicardi,, Philippe Zarka, Corentin Louis, Andr\'ee Coffre, Laurent Lamy, Laurent Denis,, Jean-Mathias Grie{\ss}meier, Jeremy Faden, Chris Piker, Nicolas Andr\'e,, Vincent G\'enot, St\'ephane Erard, Joseph N Mafi, Todd A King, Jim Sky,, Markus Demleitner

arXiv: 1902.00300 · 2021-10-26

## TL;DR

MASER is a comprehensive toolbox integrating data analysis, simulation, and visualization tools for low frequency radio astronomy, supporting ground and space-based observations of solar, planetary, and galactic radio sources.

## Contribution

It introduces a unified infrastructure combining existing tools and a Python library for low frequency radio data analysis, tailored for the astronomy community.

## Key findings

- Enhanced data sharing and visualization capabilities.
- Support for both ground and space-based low frequency observations.
- Facilitates analysis of solar, planetary, and galactic radio emissions.

## Abstract

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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Source: https://tomesphere.com/paper/1902.00300