Astronomers are using machine learning to identify early galaxies accurately and understand the growth of supermassive black holes in the early Universe.
The Universe is filled with supermassive black holes . Almost every galaxy in the cosmos has one, and they are the most well-studied black holes by astronomers. But one thing we still don’t understand is just how they grew so massive so quickly. To answer that, astronomers have to identify lots of black holes in the early Universe , and since they are typically found in merging galaxies , that means astronomers have to identify early galaxies accurately. By hand.
But thanks to the power of machine learning, that’s changing. With the power of current and future sky surveys, the challenge of astronomy is less about capturing the right data and more about filtering out the right data from the vast trove we gather. It takes a tremendous amount of skill to distinguish a true merging galaxy from an irregular galaxy or two independent galaxies that just happen to be seen in the same patch of sky. People can be trained to do it well, but the need for skilled identifiers far surpasses the number of skilled people. One way to overcome this is to allow volunteers to fill the ga
Universe Supermassive Black Holes Galaxies Astronomers Machine Learning Early Universe Merging Galaxies Sky Surveys
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