Fremling's SNIascore identifies 1000 supernovae

Today's astronomical facilities scan the night sky deeper and faster than ever before. Identifying and classifying known and potentially interesting cosmic events is becoming impossible for one or a group of astronomers. Therefore, increasingly they train supercomputers to do the work for them. Astronomers from the Zwicky Transient Facility collaboration at Caltech have announced that their machine-learning algorithm has now classified and reported 1000 supernovae completely autonomously. "We needed a helping hand and we knew that once we train our computers to do the job, they would take a big load off our backs", says Christoffer Fremling, a staff astronomer at Caltech and the mastermind behind the new algorithm, dubbed SNIascore. "SNIascore classified its first supernova in April 2021 and a year and a half later we are hitting a nice milestone of 1000 supernovae without any human involvement."