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The recently launched NASA Transiting Exoplanet Survey Satellite (TESS) mission is going to collect lightcurves for a few hundred million of stars and we expect to increase the number of pulsating stars to analyze compared to the few thousand stars observed by the CoRoT, $textit{Kepler}$ and K2 missions. However, most of the TESS targets have not yet been properly classified and characterized. In order to improve the analysis of the TESS data, it is crucial to determine the type of stellar pulsations in a timely manner. We propose an automatic method to classify stars attending to their pulsation properties, in particular, to identify solar-like pulsators among all TESS targets. It relies on the use of the global amount of power contained in the power spectrum (already known as the FliPer method) as a key parameter, along with the effective temperature, to feed into a machine learning classifier. Our study, based on TESS simulated datasets, shows that we are able to classify pulsators with a $98%$ accuracy.
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The NASAs Transiting Exoplanet Survey Satellite (TESS) is about to provide full-frame images of almost the entire sky. The amount of stellar data to be analysed represents hundreds of millions stars, which is several orders of magnitude above the amount of stars observed by CoRoT, Kepler, or K2 missions. We aim at automatically classifying the newly observed stars, with near real-time algorithms, to better guide their subsequent detailed studies. In this paper, we present a classification algorithm built to recognise solar-like pulsators among classical pulsators, which relies on the global amount of power contained in the PSD, also known as the FliPer (Flicker in spectral Power density). As each type of pulsating star has a characteristic background or pulsation pattern, the shape of the PSD at different frequencies can be used to characterise the type of pulsating star. The FliPer Classifier (FliPer$_{Class}$) uses different FliPer parameters along with the effective temperature as input parameters to feed a machine learning algorithm in order to automatically classify the pulsating stars observed by TESS. Using noisy TESS simulated data from the TESS Asteroseismic Science Consortium (TASC), we manage to classify pulsators with a 98% accuracy. Among them, solar-like pulsating stars are recognised with a 99% accuracy, which is of great interest for further seismic analysis of these stars like our Sun. Similar results are obtained when training our classifier and applying it to 27 days subsets of real Kepler data. FliPer$_{Class}$ is part of the large TASC classification pipeline developed by the TESS Data for Asteroseismology (TDA) classification working group.
Massive stars briefly pass through the yellow supergiant (YSG) phase as they evolve redward across the HR diagram and expand into red supergiants (RSGs). Higher-mass stars pass through the YSG phase again as they evolve blueward after experiencing significant RSG mass loss. These post-RSG objects offer us a tantalizing glimpse into which stars end their lives as RSGs, and why. One telltale sign of a post-RSG object may be an instability to pulsations, depending on the stars interior structure. Here we report the discovery of five YSGs with pulsation periods faster than 1 day, found in a sample of 76 cool supergiants observed by tess at two-minute cadence. These pulsating YSGs are concentrated in a HR diagram region not previously associated with pulsations; we conclude that this is a genuine new class of pulsating star, Fast Yellow Pulsating Supergiants (FYPS). For each FYPS, we extract frequencies via iterative prewhitening and conduct a time-frequency analysis. One FYPS has an extracted frequency that is split into a triplet, and the amplitude of that peak is modulated on the same timescale as the frequency spacing of the triplet; neither rotation nor binary effects are likely culprits. We discuss the evolutionary status of FYPS and conclude that they are candidate post-RSGs. All stars in our sample also show the same stochastic low-frequency variability (SLFV) found in hot OB stars and attributed to internal gravity waves. Finally, we find four $alpha$ Cygni variables in our sample, of which three are newly discovered.
We report on the detection of pulsations of three pulsating subdwarf B stars observed by the TESS satellite and our results of mode identification in these stars based on an asymptotic period relation. SB 459 (TIC 067584818), SB 815 (TIC 169285097) and PG 0342+026 (TIC 457168745) have been monitored during single sectors resulting in 27 days coverage. These datasets allowed for detecting, in each star, a few tens of frequencies, which we interpreted as stellar oscillations. We found no multiplets, though we partially constrained mode geometry by means of period spacing, which recently became a key tool in analyses of pulsating subdwarf B stars. Standard routine that we have used allowed us to select candidates for trapped modes that surely bear signatures of non-uniform chemical profile inside the stars. We have also done statistical analysis using collected spectroscopic and asteroseismic data of previously known subdwarf B stars along with our three stars. Making use of high precision trigonometric parallaxes from the Gaia mission and spectral energy distributions we converted atmospheric parameters to stellar ones. Radii, masses and luminosities are close to their canonical values for extreme horizontal branch stars. In particular, the stellar masses are close to the canonical one of 0.47 M$_odot$ for all three stars but uncertainties on the mass are large. The results of the analyses presented here will provide important constrains for asteroseismic modelling.
Heartbeat stars are eccentric binaries exhibiting characteristic shape of brightness changes during periastron passage caused by tidal distortion of the components. Variable tidal potential can drive tidally excited oscillations (TEOs), which are usually gravity modes. Studies of heartbeat stars and TEOs open a new possibility to probe interiors of massive stars. There are only a few massive (masses of components $gtrsim 2 $M$_odot$) systems of this type known. Using TESS data from the first 16 sectors, we searched for new massive heartbeat stars and TEOs using a sample of over 300 eccentric spectroscopic binaries. We analysed TESS 2-min and 30-min cadence data. Then, we fitted Kumars analytical model to the light curves of stars showing heartbeats and performed times-series analysis of the residuals searching for TEOs and periodic intrinsic variability. We found 20 massive heartbeat systems, of which seven show TEOs. The TEOs occur at harmonics of orbital frequencies in the range between 3 and 36, with the median value equal to 9, lower than those in known Kepler systems with TEOs. The most massive system in this sample is the quadruple star HD 5980, a member of Small Magellanic Cloud. With the total mass of $sim$150 M$_{odot}$ it is the most massive system showing a heartbeat. Six stars in the sample of the new heartbeat stars are eclipsing. Comparison of the parameters derived from fitting Kumars model and from light-curve modelling shows that Kumars model does not provide reliable parameters. Finally, intrinsic pulsations of $beta$ Cep, SPB, $delta$ Sct, and $gamma$ Dor-type were found in nine heartbeat systems. This opens an interesting possibility of studies of pulsation-binarity interaction and the co-existence of forced and self-excited oscillations.
We have studied over 1600 Am stars at a photometric precision of 1 mmag with SuperWASP photometric data. Contrary to previous belief, we find that around 200 Am stars are pulsating delta Sct and gamma Dor stars, with low amplitudes that have been missed in previous, less extensive studies. While the amplitudes are generally low, the presence of pulsation in Am stars places a strong constraint on atmospheric convection, and may require the pulsation to be laminar. While some pulsating Am stars have been previously found to be delta Sct stars, the vast majority of Am stars known to pulsate are presented in this paper. They will form the basis of future statistical studies of pulsation in the presence of atomic diffusion.
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