New insights on stellar evolution and stellar interior physics are being made possible by asteroseismology. Throughout the course of the Kepler mission, asteroseismology has also played an important role in the characterization of exoplanet-host stars and their planetary systems. The upcoming NASA Transiting Exoplanet Survey Satellite (TESS) will be performing a near all-sky survey for planets that transit bright nearby stars. In addition, its excellent photometric precision, combined with its fine time sampling and long intervals of uninterrupted observations, will enable asteroseismology of solar-type and red-giant stars. Here we develop a simple test to estimate the detectability of solar-like oscillations in TESS photometry of any given star. Based on an all-sky stellar and planetary synthetic population, we go on to predict the asteroseismic yield of the TESS mission, placing emphasis on the yield of exoplanet-host stars for which we expect to detect solar-like oscillations. This is done for both the target stars (observed at a 2-minute cadence) and the full-frame-image stars (observed at a 30-minute cadence). A similar exercise is also conducted based on a compilation of known host stars. We predict that TESS will detect solar-like oscillations in a few dozen target hosts (mainly subgiant stars but also in a smaller number of F dwarfs), in up to 200 low-luminosity red-giant hosts, and in over 100 solar-type and red-giant known hosts, thereby leading to a threefold improvement in the asteroseismic yield of exoplanet-host stars when compared to Keplerʼs.

Asteroseismic constraints on K giants make it possible to infer radii, masses and ages of tens of thousands of field stars. Tests against independent estimates of these properties are however scarce, especially in the metal-poor regime. Here, we report the detection of solar-like oscillations in 8 stars belonging to the red-giant branch and red-horizontal branch of the globular cluster M4. The detections were made in photometric observations from the K2 Mission during its Campaign 2. Making use of independent constraints on the distance, we estimate masses of the 8 stars by utilising different combinations of seismic and non-seismic inputs. When introducing a correction to the ∆ν scaling relation as suggested by stellar models, for RGB stars we find excellent agreement with the expected masses from isochrone fitting, and with a distance modulus derived using independent methods. The offset with respect to independent masses is lower, or comparable with, the uncertainties on the average RGB mass (4 − 10%, depending on the combination of constraints used). Our results lend confidence to asteroseismic masses in the metal poor regime. We note that a larger sample will be needed to allow more stringent tests to be made of systematic uncertainties in all the observables (both seismic and non-seismic), and to explore the properties of RHB stars, and of different populations in the cluster.

A key aspect in the determination of stellar properties is the comparison of observational constraints with predictions from stellar models. Asteroseismic Inference on a Massive Scale (AIMS) is an open source code that uses Bayesian statistics and a Markov Chain Monte Carlo approach to find a representative set of models that reproduce a given set of classical and asteroseismic constraints. These models are obtained by interpolation on a pre-calculated grid, thereby increasing computational efficiency. We test the accuracy of the different operational modes within AIMS for grids of stellar models computed with the Liège stellar evolution code (main sequence and red giants) and compare the results to those from another asteroseismic analysis pipeline, PARAM. Moreover, using artificial inputs generated from models within the grid (assuming the models to be correct), we focus on the impact on the precision of the code when considering different combinations of observational constraints (individual mode frequencies, period spacings, parallaxes, photospheric constraints,...). Our tests show the absolute limitations of precision on parameter inferences using synthetic data with AIMS, and the consistency of the code with expected parameter uncertainty distributions. Interpolation testing highlights the significance of the underlying physics to the analysis performance of AIMS and provides caution as to the upper limits in parameter step size. All tests demonstrate the flexibility and capability of AIMS as an analysis tool and its potential to perform accurate ensemble analysis with current and future asteroseismic data yields.

Context. The study of stellar activity cycles is crucial to understand the underlying dynamo and how it causes magnetic activity signatures such as dark spots and bright faculae. Having knowledge about the dominant source of surface activity might allow us to draw conclusions about the stellar age and magnetic field topology, and to put the solar cycle in context. Aims. We investigate the underlying process that causes magnetic activity by studying the appearance of activity signatures in contemporaneous photometric and chromospheric time series. Methods. Lomb-Scargle periodograms are used to search for cycle periods present in the photometric and chromospheric time series. To emphasize the signature of the activity cycle we account for rotation-induced scatter in both data sets by fitting a quasi-periodic Gaussian process model to each observing season. After subtracting the rotational variability, cycle amplitudes and the phase difference between the two time series are obtained by fitting both time series simultaneously using the same cycle period. Results. We find cycle periods in 27 of the 30 stars in our sample. The phase difference between the two time series reveals that the variability in fast-rotating active stars is usually in anti-phase, while the variability of slowly rotating inactive stars is in phase. The photometric cycle amplitudes are on average six times larger for the active stars. The phase and amplitude information demonstrates that active stars are dominated by dark spots, whereas less-active stars are dominated by bright faculae. We find the transition from spot to faculae domination to be at the Vaughan–Preston gap, and around a Rossby number equal to one. Conclusions. We conclude that faculae are the dominant ingredient of stellar activity cycles at ages ≳2.55 Gyr. The data further suggest that the Vaughan–Preston gap cannot explain the previously detected dearth of Kepler rotation periods between 15 and 25 days. Nevertheless, our results led us to propose an explanation for the lack of rotation periods to be due to the non-detection of periodicity caused by the cancelation of dark spots and bright faculae at ∼800 Myr.

The angle ψ between a planet's orbital axis and the spin axis of its parent star is an important diagnostic of planet formation, migration, and tidal evolution. We seek empirical constraints on ψ by measuring the stellar inclination i s via asteroseismology for an ensemble of 25 solar-type hosts observed with NASA's Kepler satellite. Our results for i s are consistent with alignment at the 2σ level for all stars in the sample, meaning that the system surrounding the red-giant star Kepler-56 remains as the only unambiguous misaligned multiple-planet system detected to date. The availability of a measurement of the projected spin-orbit angle λ for two of the systems allows us to estimate ψ. We find that the orbit of the hot Jupiter HAT-P-7b is likely to be retrograde ( 116 . 4 14.730.2, whereas that of Kepler-25c seems to be well aligned with the stellar spin axis ( 12 . 6 11.0 6.7While the latter result is in apparent contradiction with a statement made previously in the literature that the multi-transiting system Kepler-25 is misaligned, we show that the results are consistent, given the large associated uncertainties. Finally, we perform a hierarchical Bayesian analysis based on the asteroseismic sample in order to recover the underlying distribution of ψ. The ensemble analysis suggests that the directions of the stellar spin and planetary orbital axes are correlated, as conveyed by a tendency of the host stars to display large values of inclination.

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We present the discovery of HD 221416 b, the first transiting planet identified by the Transiting Exoplanet Survey Satellite (TESS) for which asteroseismology of the host star is possible. HD 221416 b (HIP 116158, TOI-197) is a bright (V=8.2 mag), spectroscopically classified subgiant that oscillates with an average frequency of about 430 μHz and displays a clear signature of mixed modes. The oscillation amplitude confirms that the redder TESS bandpass compared to Kepler has a small effect on the oscillations, supporting the expected yield of thousands of solar-like oscillators with TESS 2 minute cadence observations. Asteroseismic modeling yields a robust determination of the host star radius (R å =2.943±0.064 R e), mass (M å =1.212±0.074 M e), and age (4.9±1.1 Gyr), and demonstrates that it has just started ascending the red-giant branch. Combining asteroseismology with transit modeling and radial-velocity observations, we show that the planet is a "hot Saturn" (R p =9.17±0.33 R ⊕) with an orbital period of ∼14.3 days, irradiance of F=343±24 F ⊕ , and moderate mass (M p =60.5±5.7 M ⊕) and density (ρ p =0.431±0.062 g cm −3). The properties of HD 221416 b show that the host-star metallicity-planet mass correlation found in sub-Saturns (4-8 R ⊕) does not extend to larger radii, indicating that planets in the transition between sub-Saturns and Jupiters follow a relatively narrow range of densities. With a density measured to ∼15%, HD 221416 b is one of the best characterized Saturn-size planets to date, augmenting the small number of known transiting planets around evolved stars and demonstrating the power of TESS to characterize exoplanets and their host stars using asteroseismology.

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 toward 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 α-abundances.