Physicists use supercomputers and AI to create the most accurate model yet of black hole mergers | 1/24/2019 | Staff
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One of the most cataclysmic events to occur in the cosmos involves the collision of two black holes. Formed from the deathly collapse of massive stars, black holes are incredibly compact—a person standing near a stellar-mass black hole would feel gravity about a trillion times more strongly than they would on Earth. When two objects of this extreme density spiral together and merge, a fairly common occurrence in space, they radiate more power than all the stars in the universe.

"Imagine taking 30 suns and packing them into a region the size of Hawaii. Then take two such objects and accelerate them to half the speed of light and make them collide. This is one of the most violent events in nature," says Vijay Varma, a graduate student at Caltech.

Study - January - Issue - Physical - Review

In a new study in the January 11 issue of the journal Physical Review Letters, Varma and his colleagues report the most accurate computer model yet of the end stage of black hole mergers, a period when a new, more massive black hole has formed. The model, which was aided by supercomputers and machine-learning, or artificial intelligence (AI) tools, will ultimately help physicists perform more precise tests of Einstein's general theory of relativity.

"We can predict what's left after a black hole merger—properties of the final black hole such as its spin and mass—with an accuracy 10 to 100 times better than what was possible before," says co-author Davide Gerosa, an Einstein Postdoctoral Fellow in Theoretical Astrophysics at Caltech. "This is important because tests of general relativity depend on how well we can predict the end states of black hole mergers."

Research - Effort - Holes - LIGO - Laser

The research is related to a larger effort to study black holes with LIGO, the Laser Interferometer Gravitational-wave Observatory, which made history in 2015 by making the first direct detection of gravitational waves...
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