Black holes are missing in the early universe, and computers are after them

As far as the eye can see, galaxies fill the images of the deep universe. What processes determined their shapes, colors and populations of stars? Astronomers think that primordial black holes were the engines of galaxies’ growth and transformation, and can explain the cosmic landscape we see now.

In an article published today (Dec. 6) in the journal Astronomy & Astrophysics, an international team led by Rodrigo Carvajal, of the Institute of Astrophysics and Space Sciences (IA) and the Faculty of Sciences of the University of Lisbon (Ciências ULisboa), presents a machine learning technique that recognizes superluminous galaxies in the early universe.

These are galaxies thought to be dominated by the activity of a voracious black hole at their core. According to the authors, this should be the first algorithm that predicts when this activity also radiates an intense signal in the radio frequencies. Radio emissions are often distinct from the other light of the galaxy, and sometimes it is difficult to link them. This technique of artificial intelligence will enable astronomers to be more effective in the search for the so-called radio galaxies.

Artist’s concept of an active galaxy, specifically a quasar. Quasars are the very bright centers of remote active galaxies, tilted relative to Earth in a way that exposes their nucleus directly at us. These superluminous centers are fed by massive black holes. As they are very far, they contain information about the first ages of the universe and the origin of galaxies. Video and images available on ESO’s website. Credit: ESO/M. Kornmesser

The algorithm, developed with the collaboration of the Closer company, acting in the sector of technological solutions for data science, was trained with images of galaxies obtained in several wavelengths of the electromagnetic spectrum. When tested with other images, it was able to predict four times more radio galaxies than the conventional methods that use explicit instructions.

As machine learning develops its own algorithms, trying to understand its success may help clarify the physical phenomena that were happening in these galaxies, 1.5 billion of years after the Big Bang, that is, when the universe was a tenth of its current age.

2023-12-06 11:41:03
Article from phys.org

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