Chilean astronomy broker ALeRCE has created a tool to automatically identify galaxies where new supernovae are being produced, the University of Chile reported.
Supernovae or stellar explosions that occur at the end of the life of a certain type of star are one of the astronomical objects that have most interested scientists around the world. The reason for this is that these phenomena are of great importance in various fields of study of astronomy. Not only do they serve as large stellar astrophysics laboratories, since when they explode they sow space with various chemical elements, but they also serve to measure cosmological distances and understand the chemical composition of the galaxies that host them.
However, as in many areas of astronomy, the large amount of data produced by new and modern instruments can make their detection like finding a needle in a haystack. For this reason, the development of computational tools is essential when it comes to analyzing and continuing to exploit the information they provide.
With this in mind, the team of ALeRCE, the Chilean astronomical broker promoted by the Center for Mathematical Modeling (CMM) of the University of Chile, the Millennium Institute of Astrophysics (MAS), the Data Observatory and the University of Concepción, has developed DELIGHT , a new tool that automatically identifies galaxies in which new supernovae occur in the sky and, with this, determines the distance to the supernova with high precision, a work that was published in The Astronomical Journal.
As Francisco Förster, director of ALeRCE and research associate at CMM and MAS explains, DELIGHT “works on the basis of an artificial neural network which receives the position in the sky of the candidate supernova as input and returns the most probable position of its galaxy. ”. The system provides an answer to an important astrophysical problem to be solved, due to the difficulties that arise due to the different scales and shapes that galaxies have.
“DELIGHT was designed to operate very quickly, using multi-resolution archival images of the sky for faster download, with a huge application in mind for future survey telescopes. It is a tool that can be used by the entire supernova or transient research community, in general, and in particular by those who want to work with large samples of these events”, comments the researcher.
How does it work?
Based on the animals’ visual system, ALeRCE experts created a neural network that was trained with more than 16,000 examples that the team manually identified, reporting new transient candidates daily in the Transient Name Server, the official tool of the Union Astronomica Internazionale to communicate new objects of this type. According to Förster, this training was carried out using the Tensorflow and Ray Tune libraries, using its own GPU cards, obtained thanks to the infrastructure project of the Quimal funds of the National Research and Development Agency, which ALeRCE was awarded through the MAS in 2019 .
“This instrument has great potential to accelerate the process of detecting and characterizing new supernovae in large samples of these objects. Indeed, it is already of great help for the selection of the host galaxies on a daily basis, allowing us to save more than 30 minutes a day in the process of selecting the candidate galaxies detected by ALeRCE in the stream of the ZTF (Zwicky Transient Facility). We have also found other uses. By adding the information provided by DELIGHT, we can automatically and more accurately detect tidal disruption events, which occur when a star approaches a black hole and is destroyed by tidal forces,” concludes the astronomer.
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