A 'Quick Look' at All-Sky Galactic Archeology with TESS: 158,000 Oscillating Red Giants from the MIT Quick-Look Pipeline

TL;DR

This paper reports the first near all-sky catalog of 158,505 oscillating red giants detected from TESS data using machine learning, enabling detailed Galactic structure and evolution studies.

Contribution

It introduces a machine learning pipeline applied to TESS data to identify red giant oscillations across the sky, significantly expanding the known sample for Galactic archaeology.

Findings

158,505 oscillating red giants detected, an order of magnitude more than Kepler/K2

First near all-sky Gaia-asteroseismology mass map showing Galactic structures

Identification of 354 new halo giant candidates and analysis of Galactic mass gradients

Abstract

We present the first near all-sky yield of oscillating red giants from the prime mission data of NASA's Transiting Exoplanet Survey Satellite (TESS). We apply machine learning towards long-cadence TESS photometry from the first data release by the MIT Quick-Look Pipeline to automatically detect the presence of red giant oscillations in frequency power spectra. The detected targets are conservatively vetted to produce a total of 158,505 oscillating red giants, which is an order of magnitude increase over the yield from Kepler and K2 and a lower limit to the possible yield of oscillating giants across TESS's nominal mission. For each detected target, we report effective temperatures and radii derived from colors and Gaia parallaxes, as well as estimates of their frequency at maximum oscillation power. Using our measurements, we present the first near all-sky Gaia-asteroseismology mass map, which shows global structures consistent with the expected stellar populations of our Galaxy. To demonstrate the strong potential of TESS asteroseismology for Galactic archeology even with only one month of observations, we identify 354 new candidates for oscillating giants in the Galactic halo, display the vertical mass gradient of the Milky Way disk, and visualize correlations of stellar masses with kinematic phase space substructures, velocity dispersions, and $\alpha$-abundances.