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The NASA Transiting Exoplanet Survey Satellite (TESS) is observing tens of millions of stars with time spans ranging from $sim$ 27 days to about 1 year of continuous observations. This vast amount of data contains a wealth of information for variability, exoplanet, and stellar astrophysics studies but requires a number of processing steps before it can be fully utilized. In order to efficiently process all the TESS data and make it available to the wider scientific community, the TESS Data for Asteroseismology working group, as part of the TESS Asteroseismic Science Consortium, has created an automated open-source processing pipeline to produce light curves corrected for systematics from the short- and long-cadence raw photometry data and to classify these according to stellar variability type. We will process all stars down to a TESS magnitude of 15. This paper is the next in a series detailing how the pipeline works. Here, we present our methodology for the automatic variability classification of TESS photometry using an ensemble of supervised learners that are combined into a metaclassifier. We successfully validate our method using a carefully constructed labelled sample of Kepler Q9 light curves with a 27.4 days time span mimicking single-sector TESS observations, on which we obtain an overall accuracy of 94.9%. We demonstrate that our methodology can successfully classify stars outside of our labeled sample by applying it to all $sim$ 167,000 stars observed in Q9 of the Kepler space mission.
Over the last two decades, asteroseismology has increasingly proven to be the observational tool of choice for the study of stellar physics, aided by the high quality of data available from space-based missions such as CoRoT, Kepler, K2 and TESS. TES
The Transiting Exoplanet Survey Satellite (TESS) is NASAs latest space telescope dedicated to the discovery of transiting exoplanets around nearby stars. Besides the main goal of the mission, asteroseismology is an important secondary goal and very r
The recently launched TESS mission is for the first time giving us the potential to perform inference asteroseismology across the whole sky. TESS observed the Kepler field entirely in its Sector 14 and partly in Sector 15. Here, we seek to detect osc
Data from the Transiting Exoplanet Survey Satellite (TESS) has produced of order one million light curves at cadences of 120 s and especially 1800 s for every ~27-day observing sector during its two-year nominal mission. These data constitute a treas
The LAMOST-Kepler survey, whose spectra are analyzed in the present paper, is the first large spectroscopic project aimed at characterizing these sources. Our work is focused at selecting emission-line objects and chromospherically active stars and o