Collisions and mergers between galaxies trigger core activity and emit jets that stretch thousands of light years.

Active galactic nuclei (AGN) play an important role in galaxy evolution, and astronomers from SRON and RUG have now used a record-breaking sample of galaxies to confirm that galaxy mergers have a positive effect on igniting AGNs. By using a machine learning algorithm, the astronomers were able to compile images of 10 times more merging galaxies than in previous studies. One of the bigger questions in astronomy is: How do galaxies evolve from clouds of gas and dust into beautiful spiral structures such as those observed in the Milky Way neighborhood?

So-called active galactic nuclei (AGN) comprise interesting research objects to answer some of these questions, because there seems to be a co-evolution between AGNs and galaxies. AGNs host supermassive black holes that release enormous amounts of energy after accreting gas from their surroundings. Some have magnetic or gravitational fields large enough to send out jets from their poles that stretch for thousands of light years. Co-evolution is a two-way street. On one hand, the evolutionary stage of galaxies influences AGN activity. AGNs seem to flourish at specific stages of galaxy evolution. Their study was published in the journal Astronomy & Astrophysics.

Because AGN activity is seen to peak in galaxies at specific distances, it must also have peaked at specific times in the past. On the other hand, the activity of AGNs can influence the star formation of a galaxy. This can be either of two things: the jets from AGNs push gas away as it propagates through the galaxy, forcing it to collide with other gas, thus creating "seeds" for the birth of new stars. But AGNs can also release energy, heating the gas, thus preventing it from cooling and condensing into clumps.

Astronomers from SRON Netherlands Institute for Space Research and the University of Groningen (RUG) have now used a record number of galaxies to study one of the factors believed to have a positive influence on the ignition of AGN: mergers between galaxies. In fact, the researchers found a correlation, with about 1.4 times more AGNs in merging than in non-merging ones. On the other hand, the researchers found about 1.3 times more mergers in a sample of galaxies with AGNs than in a sample of galaxies without AGNs, which the team used a machine learning algorithm to identify.

The machine learning algorithm provides samples that are about an order of magnitude larger than in previous studies, making the correlation more reliable. "We have built a neural network to train the system to identify mergers in a large number of pictures, which allows us to use a large sample of two telescope observations of tens of thousands of galaxies," said Fangyou Gao, the first author of the study. "Active galactic nuclei are relatively easy to identify based on their spectra. But mergers must be classified from images, which is usually a job for humans. With machine learning, we can now let computers do this for us."

Bo Ke Yuan | Research/From: SRON Netherlands Institute for Space Research

The study was published in the journal Astronomy & Astrophysics

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