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Register a new userTESS Data for Asteroseismology (TDA) Stellar Variability Classification Pipeline: Set-Up and Application to the Kepler Q9 Data
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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.
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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. TESS in particular will produce more than an order of magnitude more such data than has ever been available before. While the standard TESS mission products include light curves from 120-sec observations suitable for both exoplanet and asteroseismic studies, they do not include light curves for the vastly larger number of targets observed by the mission at a longer 1800-sec cadence in Full Frame Images (FFIs). To address this lack, the TESS Data for Asteroseismology (TDA) group under the TESS Asteroseismic Science Consortium (TASC), has constructed an open-source pipeline focused on producing light curves for all stars observed by TESS at all cadences, currently including stars down to a TESS magnitude of 15. The pipeline includes target identification, background estimation and removal, correction of FFI timestamps, and a range of potential photometric extraction methodologies, though aperture photometry is currently the default approach. For the brightest targets, we transparently apply a halo photometry algorithm to construct a calibrated light curve from unsaturated pixels in the image. In this paper, we describe in detail the algorithms, functionality, and products of this pipeline, and summarize the noise metrics for the light curves. Companion papers will address the removal of systematic noise sources from our light curves, and a stellar variability classification from these.
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 relevant for the high-quality time series that TESS will make during its two year all-sky survey. Using TESS for asteroseismology introduces strong timing requirements, especially for coherent oscillators. Although the internal clock on board TESS is precise in its own time, it might have a constant drift and will thus need calibration, or offsets might inadvertently be introduced. Here we present simultaneously ground- and space-based observations of primary eclipses of several binary systems in the Southern ecliptic hemisphere, used to verify the reliability of the TESS timestamps. From twelve contemporaneous TESS/ground observations we determined a time offset equal to 5.8 +/- 2.5 sec, in the sense that the Barycentric time measured by TESS is ahead of real time. The offset is consistent with zero at 2.3-sigma level. In addition, we used 405 individually measured mid-eclipse times of 26 eclipsing binary stars observed solely by TESS to test the existence of a potential drift with a monotonic growth (or decay) affecting the observations of all stars. We find a drift corresponding to sigma_drift = 0.009 +/- 0.015 sec/day. We find that the measured offset is of a size that will not become an issue for comparing ground-based and space data for coherent oscillations for most of the targets observed with TESS.
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 oscillations in the red giants observed by TESS in the Kepler field of view. Using the full 4-yr Kepler results as the ground truth, we aim to characterise how well the seismic signal can be detected using TESS data. Because our data are based on one and two sectors of observation, our results will be representative of what one can expect for the vast majority of the TESS data. We detect clear oscillations in $sim$3000 stars with another $sim$1000 borderline (low S/N) cases, all of which yield a measurement of the frequency of maximum acoustic power, numax. In comparison, a simple calculation predicts $sim$4500 stars would show detectable oscillations. Of the clear detections we reliably measure the frequency separation between overtone radial modes, dnu, in 570 stars, meaning an overall dnu yield of 20%, which splits into a one-sector yield of 14% and a two-sector yield of 26%. These yields imply that typical (1-2 sector) TESS data will result in significant detection biases. Hence, to boost the number of stars, one might need to use only numax as the seismic input for stellar property estimation. On the up side, we find little or no bias in the seismic measurements and typical scatter relative to the Kepler `truth is about 5-6% in numax and 2-3% in dnu. These values, coupled with typical uncertainties in parallax, Teff, and Fe/H in a grid-based approach, would provide internal uncertainties of 3% in inferred stellar radius, 6% in mass and 20% in age. Finally, despite relatively large pixels of TESS, we find red giant seismology is not expected to be significantly affected by blending for stars with Tmag < 12.5.
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 treasure trove for the study of stellar variability and exoplanets. However, to fully utilize the data in such studies a proper removal of systematic noise sources must be performed before any analysis. The TESS Data for Asteroseismology (TDA) group is tasked with providing analysis-ready data for the TESS Asteroseismic Science Consortium, which covers the full spectrum of stellar variability types, including stellar oscillations and pulsations, spanning a wide range of variability timescales and amplitudes. We present here the two current implementations for co-trending of raw photometric light curves from TESS, which cover different regimes of variability to serve the entire seismic community. We find performance in terms of commonly used noise statistics to meet expectations and to be applicable to a wide range of different intrinsic variability types. Further, we find that the correction of light curves from a full sector of data can be completed well within a few days, meaning that when running in steady-state our routines are able to process one sector before data from the next arrives. Our pipeline is open-source and all processed data will be made available on TASOC and MAST.
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 on the evaluation of the atmospheric parameters. We have used a version of the code ROTFIT that exploits a wide and homogeneous collection of real star spectra, i.e. the Indo US library. We provide a catalog with the atmospheric parameters (Teff, logg, [Fe/H]), the radial velocity (RV) and an estimate of the projected rotation velocity (vsini). For cool stars (Teff<6000 K) we have also calculated the H-alpha and CaII-IRT chromospheric fluxes. We have derived the RV and the atmospheric parameters for 61,753 spectra of 51,385 stars. Literature data for a few hundred stars have been used to do a quality control of our results. The final accuracy of RV, Teff, logg, and [Fe/H] measurements is about 14 km/s, 3.5%, 0.3 dex, and 0.2 dex, respectively. However, while the Teff values are in very good agreement with the literature, we noted some issues with the determination of [Fe/H] of metal poor stars and the tendency, for logg, to cluster around the values typical for main sequence and red giant stars. We propose correction relations based on these comparison. The RV distribution is asymmetric and shows an excess of stars with negative RVs which is larger at low metallicities. We could identify stars with variable RV, ultrafast rotators, and emission-line objects. Based on the H-alpha and CaII-IRT fluxes, we have found 442 chromospherically active stars, one of which is a likely accreting object. The availability of precise rotation periods from the Kepler photometry has allowed us to study the dependency of the chromospheric fluxes on the rotation rate for a quite large sample of field stars.
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