FliPer: Checking the reliability of global seismic parameters from automatic pipelines

Our understanding of stars through asteroseismic data analysis is limited by our ability to take advantage of the huge amount of observed stars provided by space missions such as CoRoT, Kepler, K2, and soon TESS and PLATO. Global seismic pipelines provide global stellar parameters such as mass and radius using the mean seismic parameters, as well as the effective temperature. These pipelines are commonly used automatically on thousands of stars observed by K2 for 3 months (and soon TESS for at least around 1 month). However, pipelines are not immune from misidentifying noise peaks and stellar oscillations. Therefore, new validation techniques are required to assess the quality of these results. We present a new metric called FliPer (Flicker in Power), which takes into account the average variability at all measured time scales. The proper calibration of FliPer enables us to obtain good estimations of global stellar parameters such as surface gravity that are robust against the influence of noise peaks and hence are an excellent way to find faults in asteroseismic pipelines.Comment: 4 pages, 3 figures, Proceedings for SF2A 2017 (Paris

Horizontal shear instabilities in rotating stellar radiation zones:II. Effects of the full Coriolis acceleration

Stellar interiors are the seat of efficient transport of angular momentum all along their evolution. Understanding the dependence of the turbulent transport triggered by the shear instabilities due to the differential rotation in stellar radiation zones is mandatory. Indeed, it constitutes one of the cornerstones of the rotational transport and mixing theory which is implemented in stellar evolution codes to predict the rotational and chemical evolutions of stars. We investigate horizontal shear instabilities in stellar radiation zones by considering the full Coriolis acceleration with both the dimensionless horizontal component $\tilde{f}$ and the vertical component $f$. We performed a linear stability analysis for a horizontal shear flow with a hyperbolic tangent profile, both numerically and asymptotically using the WKBJ approximation. As in the traditional approximation, we identified the inflectional and inertial instabilities. The inflectional instability is destabilized as $\tilde{f}$ increases and its maximum growth rate increases significantly, while the thermal diffusivity stabilizes the inflectional instability similarly to the traditional case. The inertial instability is also strongly affected; for instance, the inertially unstable regime is extended in the non-diffusive limit as $0<f<1+\tilde{f}^{2}/N^{2}$, where $N$ is the dimensionless Brunt-V\"ais\"al\"a frequency. More strikingly, in the high-thermal-diffusivity limit, it is always inertially unstable at any colatitude $\theta$ except at the poles (i.e., $0^{\circ}<\theta<180^{\circ}$). Using the asymptotic and numerical results, we propose a prescription for the effective turbulent viscosities induced by the instabilities to be possibly used in stellar evolution models. The characteristic time of this turbulence is short enough to redistribute efficiently angular momentum and mix chemicals in the radiation zones.Comment: Accepted in A&

Imaging the Spatial Distribution of Electronic States in Graphene Using Electron Energy-Loss Spectroscopy: Prospect of Orbital Mapping

The spatial distributions of antibonding π∗ and σ∗ states in epitaxial graphene multilayers are mapped using electron energy-loss spectroscopy in a scanning transmission electron microscope. Inelastic channeling simulations validate the interpretation of the spatially resolved signals in terms of electronic orbitals, and demonstrate the crucial effect of the material thickness on the experimental capability to resolve the distribution of unoccupied states. This work illustrates the current potential of core-level electron energy-loss spectroscopy towards the direct visualization of electronic orbitals in a wide range of materials, of huge interest to better understand chemical bonding among many other properties at interfaces and defects in solids

FliPer_Class:in search of solar-like pulsators among TESS targets

The NASA's 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 (T'DA) classification working group.Comment: 8 pages, 6 figures, accepted to A&

The K2 Galactic Archaeology Program Data Release 2: Asteroseismic Results from Campaigns 4, 6, and 7

Studies of Galactic structure and evolution have benefited enormously from Gaia kinematic information, though additional, intrinsic stellar parameters like age are required to best constrain Galactic models. Asteroseismology is the most precise method of providing such information for field star populations en masse, but existing samples for the most part have been limited to a few narrow fields of view by the CoRoT and Kepler missions. In an effort to provide well-characterized stellar parameters across a wide range in Galactic position, we present the second data release of red giant asteroseismic parameters for the K2 Galactic Archaeology Program (GAP). We provide V_{max} and Delta_{v} based on six independent pipeline analyses; first-ascent red giant branch (RGB) and red clump (RC) evolutionary state classifications from machine learning; and ready-to-use radius and mass coefficients, K_{R} and K_{M}, which, when appropriately multiplied by a solar-scaled effective temperature factor, yield physical stellar radii and masses. In total, we report 4395 radius and mass coefficients, with typical uncertainties of 3.3% (stat.) ± 1% (syst.) for K_{R} and 7.7% (stat.) ± 2% (syst.) for κM among RGB stars, and 5.0% (stat.) ± 1% (syst.) for K_{R} nd 10.5% (stat.) ± 2% (syst.) for κM among RC stars. We verify that the sample is nearly complete—except for a dearth of stars with V_{max} \leqslant 10-20 mHz-by comparing to Galactic models and visual inspection. Our asteroseismic radii agree with radii derived from Gaia Data Release 2 parallaxes to within 2.2% ± 0.3% for RGB stars and 2.0% ± 0.6% for RC stars