Their observations suggest that these wandering stars have been adrift for billions of years and were not stripped from their respective galaxies. Using NASA’s Hubble Space Telescope, a team from Yonsei University, Seoul, and the University of California, Davis, conducted an infrared survey of distant galaxy clusters. There are several theories, including the possibility that the stars were pulled from their galaxies, ejected in the course of galactic mergers, or were part of their cluster since its early formation billions of years ago. For astronomers, the explanation for how these stars became so scattered throughout their galaxy clusters has always been an unresolved question. These stars are not gravitationally bound to any individual galaxy but to the halo of galaxy clusters themselves and are only discernible by the diffuse light they emit – “Ghost Light” or “Intracluster light” (ICL). In the giant galaxy clusters in the Universe, which can consist of hundreds or thousands of galaxies, there are countless “rogue” stars wandering between them. Messier 85 slants through the constellation of Coma Berenices (Berenice’s Hair) and lies around 50 million light-years from Earth. Continue reading “Humans Can Still Find Galaxies That Machine Learning Algorithms Miss” This moody image shows a galaxy named Messier 85, captured in all its delicate, hazy glory by the NASA/ESA Hubble Space Telescope. In this image, new processing techniques have been applied, bringing out fine details of the nebula’s delicate threads and filaments of ionized gas. ![]() In this day of data-driven research, it’s good to know that sometimes there’s no substitute for human eyeballs and intellect. This image taken by the NASA/ESA Hubble Space Telescope revisits the Veil Nebula, which was featured in a previous Hubble image release. ![]() These galaxies, all satellites of the Sculptor Galaxy (NGC 253), are now named Donatello II, III, and IV, in his honor. ![]() While examining data collected by the Dark Energy Survey (DES), amateur astronomer Giuseppe Donatiello discovered three faint galaxies that a machine-learning algorithm had apparently missed. While AI plays a growing role in data analysis, there are some instances where citizen astronomers are proving more capable. If you had a lot of time on your hands, you could count 45,000 galaxies in this new photo from the James Webb Space Telescope. To keep up with this volume, astronomers are turning to machine learning and AI to handle the job of analysis. Once next-generation telescopes become operational, astronomy will likely enter the “exabyte era,” where 10 18 bytes (one quintillion) of data are obtained annually. Thanks to cutting-edge instruments, software, and data-sharing, observatories worldwide are accumulating hundreds of terabytes in a single day and between 100 to 200 Petabytes a year. The age of big data is upon us, and there are scarcely any fields of scientific research that are not affected.
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