Tootfinder

Transient Classifiers for Fink: Benchmarks for LSST
B. M. O. Fraga, C. R. Bom, A. Santos, E. Russeil, M. Leoni, J. Peloton, E. E. O. Ishida, A. M\"oller, S. Blondin
https://arxiv.org/abs/2404.08798

Transient Classifiers for Fink: Benchmarks for LSST
The upcoming Legacy Survey of Space and Time (LSST) at the Vera Rubin Observatory is expected to detect a few million transients per night, which will generate a live alert stream during the entire 10 years of the survey. This will be distributed via community brokers whose task is to select subsets of the stream and direct them to scientific communities. Given the volume and complexity of data, machine learning (ML) algorithms will be paramount for this task. We present the infrastructure test…