Machine Learning Algorithm Helps Scientists Find Quasar Candidates in the Early Universe
Artificial intelligence has once again proven its value in the field of astronomy, as scientists have utilized a specially trained machine learning algorithm to identify potential quasars in the early Universe. Quasars, which are incredibly bright and distant celestial objects, can sometimes be difficult to detect due to distortions caused by gravitational lensing.
Gravitational lensing occurs when a massive object, such as a galaxy, bends the path of light from a distant object, creating a distorted image. While this phenomenon can sometimes make quasars easier to detect by magnifying their brightness, it can also alter their appearance, making them appear different from their actual nature.
Led by astronomer Xander Byrne from the University of Cambridge, a team of researchers set out to uncover these hidden quasars in the vast Dark Energy Survey data archive. With over 700 million objects to sift through, the team needed a more efficient way to identify potential candidates.
Byrne turned to a contrast learning algorithm, a type of artificial intelligence that sorts data points based on their similarities to each other. By applying this unsupervised AI process to the dataset, the team was able to identify a subset of objects that showed promise as high redshift quasar candidates.
Further observations using data from the Gemini South telescope confirmed that three out of the four candidates identified by the algorithm were indeed high redshift quasars. One of these candidates may even be a gravitationally lensed quasar, a rare and valuable discovery in the field of astronomy.
This groundbreaking research, published in the journal Monthly Notices of the Royal Astronomical Society, highlights the power of artificial intelligence in helping scientists uncover hidden treasures in the vast expanse of the Universe. With further imaging and confirmation, this discovery could provide valuable insights into the early Universe and the nature of these distant celestial objects.
