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Register a new userThe Asteroseismic Target List (ATL) for solar-like oscillators observed in 2-minute cadence with the Transiting Exoplanet Survey Satellite (TESS)
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We present the target list of solar-type stars to be observed in short-cadence (2-min) for asteroseismology by the NASA Transiting Exoplanet Survey Satellite (TESS) during its 2-year nominal survey mission. The solar-like Asteroseismic Target List (ATL) is comprised of bright, cool main-sequence and subgiant stars and forms part of the larger target list of the TESS Asteroseismic Science Consortium (TASC). The ATL uses Gaia DR2 and the Extended Hipparcos Compilation (XHIP) to derive fundamental stellar properties, calculate detection probabilities and produce a rank-ordered target list. We provide a detailed description of how the ATL was produced and calculate expected yields for solar-like oscillators based on the nominal photometric performance by TESS. We also provide publicly available source code which can be used to reproduce the ATL, thereby enabling comparisons of asteroseismic results from TESS with predictions from synthetic stellar populations.
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The Transiting Exoplanet Survey Satellite (TESS) will search for planets transiting bright and nearby stars. TESS has been selected by NASA for launch in 2017 as an Astrophysics Explorer mission. The spacecraft will be placed into a highly elliptical 13.7-day orbit around the Earth. During its two-year mission, TESS will employ four wide-field optical CCD cameras to monitor at least 200,000 main-sequence dwarf stars with I = 4-13 for temporary drops in brightness caused by planetary transits. Each star will be observed for an interval ranging from one month to one year, depending mainly on the stars ecliptic latitude. The longest observing intervals will be for stars near the ecliptic poles, which are the optimal locations for follow-up observations with the James Webb Space Telescope. Brightness measurements of preselected target stars will be recorded every 2 min, and full frame images will be recorded every 30 min. TESS stars will be 10-100 times brighter than those surveyed by the pioneering Kepler mission. This will make TESS planets easier to characterize with follow-up observations. TESS is expected to find more than a thousand planets smaller than Neptune, including dozens that are comparable in size to the Earth. Public data releases will occur every four months, inviting immediate community-wide efforts to study the new planets. The TESS legacy will be a catalog of the nearest and brightest stars hosting transiting planets, which will endure as highly favorable targets for detailed investigations.
A novel artificial intelligence (AI) technique that uses machine learning (ML) methodologies combines several algorithms, which were developed by ThetaRay, Inc., is applied to NASAs Transiting Exoplanets Survey Satellite (TESS) dataset to identify exoplanetary candidates. The AI/ML ThetaRay system is trained initially with Kepler exoplanetary data and validated with confirmed exoplanets before its application to TESS data. Existing and new features of the data, based on various observational parameters, are constructed and used in the AI/ML analysis by employing semi-supervised and unsupervised machine learning techniques. By the application of ThetaRay system to 10,803 light curves of threshold crossing events (TCEs) produced by the TESS mission, obtained from the Mikulski Archive for Space Telescopes, the algorithm yields about 50 targets for further analysis, and we uncover three new exoplanetary candidates by further manual vetting. This study demonstrates for the first time the successful application of the particular combined multiple AI/ML-based methodologies to a large astrophysical dataset for rapid automated classification of TCEs.
Uncertainties in stellar structure and evolution theory are largest for stars undergoing core convection on the main sequence. A powerful way to calibrate the free parameters used in the theory of stellar interiors is asteroseismology, which provides direct measurements of angular momentum and element transport. We report the detection and classification of new variable O and B stars using high-precision short-cadence (2-min) photometric observations assembled by the Transiting Exoplanet Survey Satellite (TESS). In our sample of 154 O and B stars, we detect a high percentage (90%) of variability. Among these we find 23 multiperiodic pulsators, 6 eclipsing binaries, 21 rotational variables, and 25 stars with stochastic low-frequency variability. Several additional variables overlap between these categories. Our study of O and B stars not only demonstrates the high data quality achieved by TESS for optimal studies of the variability of the most massive stars in the Universe, but also represents the first step towards the selection and composition of a large sample of O and B pulsators with high potential for joint asteroseismic and spectroscopic modeling of their interior structure with unprecedented precision.
We describe the catalogs assembled and the algorithms used to populate the revised TESS Input Catalog (TIC), based on the incorporation of the Gaia second data release. We also describe a revised ranking system for prioritizing stars for 2-minute cadence observations, and assemble a revised Candidate Target List (CTL) using that ranking. The TIC is available on the Mikulski Archive for Space Telescopes (MAST) server, and an enhanced CTL is available through the Filtergraph data visualization portal system at the URL http://filtergraph.vanderbilt.edu/tess_ctl.
During its two-year prime mission, the Transiting Exoplanet Survey Satellite (TESS) is obtaining full-frame images with a regular 30-minute cadence in a sequence of 26 sectors that cover a combined 85% of the sky. While its primary science case is to discover new exoplanets transiting nearby stars, TESS data are superb for studying many types of stellar variability, with the number of publications using TESS data for other areas of astrophysics keeping pace with exoplanet papers. Following the conclusion of its prime mission in July 2020, TESS will revisit the sky in an extended mission that records full-frame images at a faster ten-minute cadence. In this note, I demonstrate that choosing a large submultiple of the original exposure times for the new cadence limits the synergy between prime and extended TESS mission data since both sampling rates produce many of the same Nyquist aliases. Adjusting the extended mission exposure time by as little as one second would largely resolve Nyquist ambiguities in the combined TESS data set.
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