The new simulation allowed scientists to see the first few seconds after the Big Bang. The simulation was carried out by a group of researchers from the Institute of Astrophysics of the Canary Islands (IAC) using machine learning, a type of algorithm in which a computer is trained to recognize patterns to perform 100,000 hours of calculations. The algorithm of this project was called Hydro-BAM. The new work has allowed researchers to identify phenomena including dark matter, neutral hydrogen and other cosmic ingredients needed to understand the structure of our Universe.
“These “virtual universes” serve as testing grounds for the study of cosmology. However, modeling requires very large computing resources, and modern computing power allows exploring only small space volumes,” the researchers commented.
Hydro-BAM is designed with probability in mind, machine learning to simulate the history of the Universe. The algorithm allowed scientists to get very accurate predictions in just a few tens of seconds. For example, mapping the absorption lines in the galactic spectra allowed the team to find out where the clouds of hydrogen gas are located. Clouds also give an idea of what is contained in the intergalactic medium of gas and dust.
“The breakthrough came when we understood that the connections between the quantities of intergalactic gas, dark matter and neutral hydrogen that we were trying to model are well organized in a hierarchical way,” says Francesco Sinigaglia, a doctor at the University of La Laguna in Spain and the University of Padua in Italy, as well as the lead author of the study.
The results of the study were published in The Astrophysical Journal.
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