The configuration of a galaxy provides clues about its history and how it was formed. The most common types are spirals, such as the Milky Way. Their central portion, called the bulge, houses a dense cluster of stars, typically older ones. From the bulge, plumes of new stars spiral off into space, fueled by the presence of cold gas. These stunning structures are informally referred to as \u201carms.\u201d<\/p>\n
Elliptical galaxies, which lack substantial amounts of gas, typically do not produce new stars and have a simpler and more uniform structure. They are round or oval in shape and primarily consist of older stars. \u201cElliptical galaxies are generally found in the central regions of galaxy clusters, while spiral galaxies are more commonly located on their periphery,\u201d explains Bom.<\/p>\n
![\"\"](\"https:\/\/revistapesquisa.fapesp.br\/wp-content\/uploads\/2024\/03\/RPF-galaxias-NGC2525-Messier59-2023-09-site-1140.jpg\")
ESA\u2009\/\u2009Hubble & NASA | ESA\u2009\/\u2009Hubble & NASA, P. Cote<\/span>Examples of the two primary galaxy classes: the spiral NGC 2525 (on the right<\/em>) and the elliptical Messier 59ESA\u2009\/\u2009Hubble & NASA | ESA\u2009\/\u2009Hubble & NASA, P. Cote<\/span><\/p><\/div>\n From manual to automated Advancements in computer science, and more recently in the fields of artificial intelligence and machine learning, now enable millions of images to be rapidly processed. \u201cThanks to these algorithms, the time it takes to classify a galaxy has been reduced to milliseconds,\u201d says Italian astrophysicist Arianna Cortesi from the Valongo Observatory at the Federal University of Rio de Janeiro (OV-UFRJ), a coauthor of the study. \u201cAutomated classification relies on good image resolution and depth.\u201d The algorithm can only recognize the arms and other structures of galaxies when fed with high-quality records of celestial bodies.<\/p>\n The T80S telescope is being operated primarily in support of the Southern Photometric Local Universe Survey (S-Plus), an ongoing survey mapping half of the Southern Hemisphere sky, including some regions not covered by other surveys. It is equipped with a relatively small, 80-centimeter mirror, but boasts a wide-field camera, making it ideal for rapidly surveying vast areas of the sky.<\/p>\n T80S also features a filter system that produces images of observed celestial bodies in 12 different photometric bands. \u201cMost surveys typically provide images in four to six bands,\u201d notes Claudia Mendes de Oliveira, an astrophysicist at the Institute of Astronomy, Geophysics, and Atmospheric Sciences at the University of S\u00e3o Paulo (IAG-USP), who helped develop the T80S telescope and is heading the S-Plus project. \u201cOur images contain a wealth of information, and artificial intelligence has provided a valuable tool in our analyses.\u201d<\/p>\n The S-Plus survey has cataloged and shared images of 21 million celestial objects so far. Approximately 200 researchers, with 60% of them being Brazilian, are participating in the project. The construction and operation of the T80S were primarily funded by FAPESP, with the Brazilian National Council for Scientific and Technological Development (CNPq), the Brazilian Funding Authority for Studies and Projects (FINEP), and the Rio de Janeiro State Research Foundation (FAPERJ) providing additional funding to help bring the telescope online.<\/p>\n Project<\/strong>
\n<\/strong>Just a few decades ago, astrophysicists classified galaxies and other celestial bodies using a manual process, examining each image individually. But the fast-growing body of data on celestial bodies, collected in multiple sky surveys, has led to a shift to automated classification, at least as an initial, rough determination.<\/p>\n
\nScience with the Brazilian robotic telescope<\/em> (n\u00ba 19\/26492-3<\/a>); Grant Mechanism<\/strong> Thematic Project; Principal Investigator<\/strong> Claudia Mendes de Oliveira (USP); Investment<\/strong> R$3,899,778.96.<\/p>\n