Washington, A team of scientists from Northwestern University in the United States developed an artificial intelligence tool using 1.4 million historical images from nearly 16,000 sources to train its machine-learning algorithm.
The new system allows automation of the entire star explosion discovery process, which not only eliminates human error but also dramatically increases speed.
The astronomer, Nabeel Rehemtulla from Northwestern University said: "This significantly streamlines large studies of supernovae, helping us better understand the life cycles of stars and the origin of elements supernovae create, like carbon, iron and gold." Though supernovae are bright and energetic events, they're not that common, or simple to spot. Traditional methods of detection rely on astronomers to visually inspect large volumes of data from robotic telescopes that continuously scan the night sky for new sources of light.
It is estimated that astronomers have only discovered a small fraction of all supernovae that occur in the Universe.
Source: Qatar News Agency