Artificial Intelligence Algorithm Detects and Classifies Supernova, Revolutionizing Astronomical Research
Move over, human astronomers! Artificial intelligence (AI) could soon be doing your supernova hunting for you. A groundbreaking new machine-learning algorithm, called Bright Transient Survey Bot (BTSbot), has successfully detected, identified, and classified its first supernova, marking the first time this has been achieved using AI. This development could significantly speed up the process of analyzing and categorizing supernovas, according to the developers.
Currently, spotting supernovas relies on a collaboration between humans and computers. However, BTSbot aims to eliminate the need for human intervention in this process. Over the past six years alone, human astronomers have spent an estimated 2,200 hours visually inspecting and classifying potential supernova candidates. BTSbot has the potential to free up astronomers’ time, allowing them to focus more on understanding the origins and behavior of these celestial explosions.
The team leader of BTSbot, Adam Miller, a professor of physics at Northwestern University in Illinois, explained the significance of this breakthrough. “For the first time ever, a series of robots and AI algorithms have observed, then identified, then communicated with another telescope to finally confirm the discovery of a supernova,” he said. Miller emphasized that removing humans from the equation would give researchers more time to analyze data and develop new hypotheses about these cosmic explosions.
To develop the BTSbot algorithm, Miller and his team trained the AI using over 1.4 million historical images from nearly 16,000 sources. These images included confirmed supernovas, as well as other explosive astronomical events such as flaring stars and galaxies. The algorithm was designed to identify patterns and characteristics that distinguish supernovas from other celestial phenomena.
To put BTSbot to the test, the researchers focused on a newly discovered supernova candidate designated SN2023tyk. Located approximately 760 million light-years from Earth, SN2023tyk is believed to be a Type Ia supernova. Using data from the Zwicky Transient Facility (ZTF) robotic telescope, BTSbot successfully identified SN2023tyk on October 5. The potential supernova’s spectrum was collected by the SED machine (SEDM) at Palomar Observatory, further confirming its classification as a Type Ia supernova. Remarkably, BTSbot autonomously shared this information with astronomers on October 7, without any human intervention.
Northwestern graduate student Nabeel Rehemtulla, who co-led the development of BTSbot, expressed the team’s relief and excitement when the algorithm’s performance exceeded expectations. “Once the observations from SEDM and the automated classification came in, we felt a huge wave of relief. The beauty of it is that once everything is turned on and working properly, we don’t actually do anything. We go to sleep at night, and, in the morning, we see that BTSbot and these other AIs unwaveringly do their jobs,” Rehemtulla said.
The capability of BTSbot to detect and classify supernovas autonomously has the potential to revolutionize the field of astronomy. By automating the labor-intensive process of visually inspecting and categorizing supernova candidates, astronomers can redirect their efforts towards studying the origin and behavior of these cosmic explosions. With further refinements, the algorithm may also be able to isolate specific subtypes of supernovas, unlocking new insights into these spectacular events that shape our universe.