Scientists Used AI to Create a Hyper Detailed 3D Map of Stars, Galaxies, and Quasars
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Scientists Used AI to Create a Hyper Detailed 3D Map of Stars, Galaxies, and Quasars:
A team of astronomers from the University of Hawaii at Mnoa's Institute for Astronomy (IfA) has produced the most comprehensive astronomical imaging catalog of stars, galaxies, and quasars ever created with help from an artificially intelligent neural network.
The group of astronomers from the University of Hawaii at Mnoa's Institute for Astronomy (IfA) released a catalog containing 3 billion celestial objects in 2016, including stars, galaxies, and quasars (the active cores of supermassive black holes). Needless to say, the parsing of this extensive database-packed with 2 petabytes of data-was a task unfit for puny humans, and even grad students. A major goal coming out of the 2016 catalog release was to better characterize these distant specks of light, and to also map the arrangement of galaxies in all three dimensions. The Pan-STARRS team can now check these items off their to-do list, owing to the powers of machine learning. The results of their work have been published to the Monthly Notices of the Royal Astronomical Society.
Journal Reference:
Beck, Robert, Szapudi, Istvan, Flewelling, Heather, et al. PS1-STRM: Neural network source classification and photometric redshift catalogue for PS1 3 DR1, Monthly Notices of the Royal Astronomical Society (DOI: 10.1093/mnras/staa2587)
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