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Register a new user$texttt{pySYD}$: Automated measurements of global asteroseismic parameters
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Asteroseismology is well-established in astronomy as the gold standard for determining precise and accurate fundamental stellar properties like masses, radii, and ages. Several tools have been developed for asteroseismic analyses but many of them are closed-source and therefore not accessible to the general astronomy community. Here we present $texttt{pySYD}$, a Python package for detecting solar-like oscillations and measuring global asteroseismic parameters. $texttt{pySYD}$ was adapted from the IDL-based $texttt{SYD}$ pipeline, which was extensively used to measure asteroseismic parameters for $textit{Kepler}$ stars. $texttt{pySYD}$ was developed using the same well-tested methodology and comes with several new improvements to provide accessible and reproducible results. Well-documented, open-source asteroseismology software that has been benchmarked against closed-source tools are critical to ensure the reproducibility of legacy results from the $textit{Kepler}$ mission. Moreover, $texttt{pySYD}$ will also be a promising tool for the broader astronomy community to analyze current and forthcoming data from the NASA TESS mission.
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This article describes a moving-windowed autocorrelation technique which, when applied to an asteroseismic Fourier power spectrum, can be used to automatically detect the frequency of maximum p-mode power, large and small separations, mean p-mode linewidth, and constrain the stellar inclination angle and rotational splitting. The technique is illustrated using data from the CoRoT and Kepler space telescopes and tested using artificial data.
The number of main-sequence stars for which we can observe solar-like oscillations is expected to increase considerably with the short-cadence high-precision photometric observations from the NASA Kepler satellite. Because of this increase in number of stars, automated tools are needed to analyse these data in a reasonable amount of time. In the framework of the asteroFLAG consortium, we present an automated pipeline which extracts frequencies and other parameters of solar-like oscillations in main-sequence and subgiant stars. The pipeline uses only the timeseries data as input and does not require any other input information. Tests on 353 artificial stars reveal that we can obtain accurate frequencies and oscillation parameters for about three quarters of the stars. We conclude that our methods are well suited for the analysis of main-sequence stars, which show mainly p-mode oscillations.
With the observations of an unprecedented number of oscillating subgiant stars expected from NASAs TESS mission, the asteroseismic characterization of subgiant stars will be a vital task for stellar population studies and for testing our theories of stellar evolution. To determine the fundamental properties of a large sample of subgiant stars efficiently, we developed a deep learning method that estimates distributions of fundamental parameters like age and mass over a wide range of input physics by learning from a grid of stellar models varied in eight physical parameters. We applied our method to four Kepler subgiant stars and compare our results with previously determined estimates. Our results show good agreement with previous estimates for three of them (KIC 11026764, KIC 10920273, KIC 11395018). With the ability to explore a vast range of stellar parameters, we determine that the remaining star, KIC 10005473, is likely to have an age 1 Gyr younger than its previously determined estimate. Our method also estimates the efficiency of overshooting, undershooting, and microscopic diffusion processes, from which we determined that the parameters governing such processes are generally poorly-constrained in subgiant models. We further demonstrate our methods utility for ensemble asteroseismology by characterizing a sample of 30 Kepler subgiant stars, where we find a majority of our age, mass, and radius estimates agree within uncertainties from more computationally expensive grid-based modelling techniques.
HATSouth is the worlds first network of automated and homogeneous telescopes that is capable of year-round 24-hour monitoring of positions over an entire hemisphere of the sky. The primary scientific goal of the network is to discover and characterize a large number of transiting extrasolar planets, reaching out to long periods and down to small planetary radii. HATSouth achieves this by monitoring extended areas on the sky, deriving high precision light curves for a large number of stars, searching for the signature of planetary transits, and confirming planetary candidates with larger telescopes. HATSouth employs 6 telescope units spread over 3 locations with large longitude separation in the southern hemisphere (Las Campanas Observatory, Chile; HESS site, Namibia; Siding Spring Observatory, Australia). Each of the HATSouth units holds four 0.18m diameter f/2.8 focal ratio telescope tubes on a common mount producing an 8.2x8.2 arcdeg field, imaged using four 4Kx4K CCD cameras and Sloan r filters, to give a pixel scale of 3.7 arcsec/pixel. The HATSouth network is capable of continuously monitoring 128 square arc-degrees. We present the technical details of the network, summarize operations, and present weather statistics for the 3 sites. On average each of the 6 HATSouth units has conducted observations on ~500 nights over a 2-year time period, yielding a total of more than 1million science frames at 4 minute integration time, and observing ~10.65 hours per day on average. We describe the scheme of our data transfer and reduction from raw pixel images to trend-filtered light curves and transiting planet candidates. Photometric precision reaches ~6 mmag at 4-minute cadence for the brightest non-saturated stars at r~10.5. We present detailed transit recovery simulations to determine the expected yield of transiting planets from HATSouth. (abridged)
The NASA Kepler mission has observed more than 190,000 stars in the constellations of Cygnus and Lyra. Around 4 years of almost continuous ultra high-precision photometry have been obtained reaching a duty cycle higher than 90% for many of these stars. However, almost regular gaps due to nominal operations are present in the light curves at different time scales. In this paper we want to highlight the impact of those regular gaps in asteroseismic analyses and we try to find a method that minimizes their effect in the frequency domain. To do so, we isolate the two main time scales of quasi regular gaps in the data. We then interpolate the gaps and we compare the power density spectra of four different stars: two red giants at different stages of their evolution, a young F-type star, and a classical pulsator in the instability strip. The spectra obtained after filling the gaps in the selected solar-like stars show a net reduction in the overall background level, as well as a change in the background parameters. The inferred convective properties could change as much as 200% in the selected example, introducing a bias in the p-mode frequency of maximum power. When global asteroseismic scaling relations are used, this bias can lead up to a variation in the surface gravity of 0.05 dex. Finally, the oscillation spectrum in the classical pulsator is cleaner compared to the original one.
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