Discovering g- and p-mode pulsators in the TESS-PLATO field of view with machine learning

The millions of light curves that are being delivered by TESS contain an incredible amount of information for asteroseismology. The first step in uncovering this information is to identify the pulsating stars in the data set. We therefore constructed a machine learning classifier to hunt for p- and g-mode pulsators in TESS. We updated the training set from the TESS Data for Asteroseismology (T’DA) Working Group and optimized the classifier for the 10-minute Extended Mission 1 (EM1) and 200-second Extended Mission 2 (EM2) light curves. In this contribution, we will focus on the TESS light curves in the southern hemisphere, and in particular on the ones in the first observing field of the upcoming ESA PLATO mission (launch 2026). We will specifically discuss our classifications for the half a million light curves in the g- and p-mode temperature regime in this field. The classifications are of key importance for the community as the PLATO satellite will only send back the observations for a pre-selected list of targets. Hence, our TESS classifications will allow the asteroseismic community to create an optimal selection of targets to follow up with PLATO. This project is the first part of our full-sky TESS stellar variability catalog.