Astronomers have formed the AI ​​to find collisions of ancient galaxies in the early Universe



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There are bright lights everywhere in the universe where galaxies are smashing. And there are bright spots all over the universe – especially the very distant universe – where galaxies produce stars at an unusual rate. Now, a team of astronomers has a new way of distinguishing them.

Here's the problem: telescopes can not see distant and ancient parts of the universe clearly enough to spot the usual signatures of galaxy fusion. There is no good way to distinguish these two types of super bright galaxies.

In an article published in the July issue of the Royal Astronomical Society's Monthly Review, researchers described a new system for distinguishing far-distant galaxy fusions from far-flung galaxies that shine brightly because they give birth to an unusually high number of new stars.

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In parts relatively close to the universe, we can easily identify galactic fusions based on star tsunamis at their periphery. Long "tidal arms" of stars extend nuclei from recently fused galaxies, like arrows identifying them for stellar archaeologists exploring space.

But the light of the old universe has traveled too far and seems too fuzzy for these patterns to be visible. At the same time, the first billions of years of the history of our universe have been defined by galaxies producing stars at a high rate, which would be unusual nowadays. Thus, it is not known for a long time which super-bright and far-distant galaxies can see in the primitive universe the result of fusions, and which are so brilliant on their own.

The team felt that since we know galaxies that form stars and galactic fusions, it would be relatively simple to create false images, then fade them and scramble them as if the light from these galaxies was captured from afar by one of our space telescopes. This is what the team did by creating more than one million fake Hubble space telescopes and images from the James Webb Space Telescope. Astronomers knew which were fuzzy and distant images of galactic collisions compared to fuzzy images of super-bright galaxies, forming stars, even if they seemed very similar at first sight. The researchers were able to find subtle signatures that astronomers use to distinguish galaxy fusions from galactic star plants in the distant and ancient universe. And they themselves formed an automatic learning algorithm to distinguish images from both types of galaxies.

This is a big problem because the entire universe is filled with fused galaxies, said the researchers in a statement – up to 5% of galaxies are involved in mergers at any given time, and even the Milky Way should one day merge with its neighbor Andromeda.

The new method has its limits, the researchers wrote. The database of simulations still has potential for bias, she writes, and the creation of the database is tainted with empirical inaccuracies. To further improve the machine learning algorithm, they wrote, and distinguished fusions from even older galaxies. They must therefore create a much larger database.

Originally published on Science live.

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