New simulation maps the first few seconds after the great explosionfocusing on what scientists call the galactic medium, or gas and dust between galaxies.
A team led by researchers at the Institute of Astrophysics in the Canary Islands (IAC) used machine learning, a type of algorithm in which a computer is trained to recognize patterns, to complete 100,000 hours of computation. The algorithm for this project is called Hydro-BAM.
This new work allowed researchers to map phenomena including dark matterActivated gas, neutral hydrogen and other cosmic components essential to understanding the structure of our universe, IAC representatives said May 20 statement (Opens in a new tab).
They added: “The research also made it possible to reproduce the so-called” Lyman alpha “forests at high resolution. This is a specific pattern of lines in the spectrum (light signature) of galaxies and similar objects created when clouds of hydrogen gas absorb galactic light.
“These ‘virtual universes’ serve as test beds for study cosmologyThe researchers added: “However, computational simulations are expensive, and current computing facilities only allow this [us] To explore the small cosmic scales. “
Hydro-BAM is designed to include probability, machine learning, and cosmology, which means the history of the universe. “This algorithm made it possible to obtain highly accurate predictions in just a few tens of seconds,” the researchers said.
Drawing absorption lines in the galaxy’s spectra allowed the team to get a sense of where clouds of hydrogen gas lie. Location is a proxy for distance, given that The universe is constantly expanding. Clouds also provide clues to what is in the intergalactic medium of gas and dust.
“The breakthrough came when we realized that the connections between the amounts of intergalactic gas, dark matter, and neutral hydrogen that we were trying to model are well organized in a hierarchical way,” said Francesco Cengiglia, a doctoral student at the University of La Laguna in Spain, IAC, University of Padua in Italy and lead author of the research. in the statement.
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