Fink: transient astronomy in the Rubin era
Emille E. O. Ishida
Université Clermont-Auvergne, FR
Next generation experiments such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will provide a rich source of information for multi-messenger astronomy tasks. To fully harness the power of these surveys, we require analysis methods capable of dealing with large streams, and which can identify promising transients within minutes for follow-up coordination. In this talk I will present Fink, an astronomy broker specifically designed for LSST. Fink is based on high-end technology and designed for fast and efficient analysis of big data streams. It has been chosen as one of the official LSST brokers who will receive the full data stream. I will highlight the state-of-the-art machine learning techniques used to generate early classification scores for a variety of time-domain phenomena, including supernovae, kilonovae, AGNs, young stellar objects, among many others. I will also describe the current efforts being developed in Brazil that will enable easy access to LSST the data stream through Fink, and discuss the possibility to develop tailored filters and science modules for other applications. In combination with other efforts already developed within the Fink community, this collaboration has the potential to boost scientific outcomes as soon as LSST comes online.