Grid-based modelling is widely used for estimating stellar parameters. However, stellar model grid is sparse because of the computational cost. This paper demonstrates an application of a machine-learning algorithm using the Gaussian Process (GP) Regression that turns a sparse model grid onto a continuous function. We train GP models to map five fundamental inputs (mass, equivalent evolutionary phase, initial metallicity, initial helium fraction, and the mixing-length parameter) to observable outputs (effective temperature, surface gravity, radius, surface metallicity, and stellar age). We test the GP predictions for the five outputs using off-grid stellar models and find no obvious systematic offsets, indicating good accuracy in predictions.As a further validation, we apply these GP models to characterise 1,000 fake stars. Inferred masses and ages determined with GP models well recover true values within one standard deviation. An important consequence of using GP-based interpolation is that stellar ages are more precise than those estimated with the original sparse grid because of the full sampling of fundamental inputs.

With recent advances in modelling stars using high-precision asteroseismology, the systematic effects associated with our assumptions of stellar helium abundance (Y) and the mixing-length theory parameter (αMLT) are becoming more important. We apply a new method to improve the inference of stellar parameters for a sample of Kepler dwarfs and subgiants across a narrow mass range ($0.8 \lt M \lt 1.2\, \rm M_\odot$). In this method, we include a statistical treatment of Y and the αMLT. We develop a hierarchical Bayesian model to encode information about the distribution of Y and αMLT in the population, fitting a linear helium enrichment law including an intrinsic spread around this relation and normal distribution in αMLT. We test various levels of pooling parameters, with and without solar data as a calibrator. When including the Sun as a star, we find the gradient for the enrichment law, $\Delta Y / \Delta Z = 1.05\substack{+0.28\\-0.25}$ and the mean αMLT in the population, $\mu _\alpha = 1.90\substack{+0.10\\-0.09}$. While accounting for the uncertainty in Y and αMLT, we are still able to report statistical uncertainties of 2.5 per cent in mass, 1.2 per cent in radius, and 12 per cent in age. Our method can also be applied to larger samples that will lead to improved constraints on both the population level inference and the star-by-star fundamental parameters.

Data from the Transiting Exoplanet Survey Satellite (TESS) has produced of order one million light curves at cadences of 120 s and especially 1800 s for every 27-day observing sector during its two-year nominal mission. These data constitute a treasure trove for the study of stellar variability and exoplanets. However, to fully utilize the data in such studies a proper removal of systematic noise sources must be performed before any analysis. The TESS Data for Asteroseismology (T'DA) group is tasked with providing analysis-ready data for the TESS Asteroseismic Science Consortium, which covers the full spectrum of stellar variability types, including stellar oscillations and pulsations, spanning a wide range of variability timescales and amplitudes. We present here the two current implementations for co-trending of raw photometric light curves from TESS, which cover different regimes of variability to serve the entire seismic community. We find performance in terms of commonly used noise statistics to meet expectations and to be applicable to a wide range of different intrinsic variability types. Further, we find that the correction of light curves from a full sector of data can be completed well within a few days, meaning that when running in steady-state our routines are able to process one sector before data from the next arrives. Our pipeline is open-source and all processed data will be made available on TASOC and MAST.

Over the last two decades, asteroseismology has increasingly proven to be the observational tool of choice for the study of stellar physics, aided by the high quality of data available from space-based missions such as CoRoT, Kepler, K2, and the Transiting Exoplanet Survey Satellite (TESS). TESS in particular will produce more than an order of magnitude more such data than has ever been available before. While the standard TESS mission products include light curves from 120 s observations suitable for both exoplanet and asteroseismic studies, they do not include light curves for the vastly larger number of targets observed by the mission at a longer 1800 s cadence in Full Frame Images (FFIs). To address this lack, the TESS Data for Asteroseismology (T'DA) group under the TESS Asteroseismic Science Consortium (TASC) has constructed an open-source pipeline focused on producing light curves for all stars observed by TESS at all cadences, currently including stars down to a TESS magnitude of 15. The pipeline includes target identification, background estimation and removal, correction of FFI time stamps, and a range of potential photometric extraction methodologies, though aperture photometry is currently the default approach. For the brightest targets, we transparently apply a halo photometry algorithm to construct a calibrated light curve from unsaturated pixels in the image. In this paper, we describe in detail the algorithms, functionality, and products of this pipeline and summarize the noise metrics for the light curves. Companion papers will address the removal of systematic noise sources from our light curves, and a stellar variability classification from these.

Asteroseismology is an exceptional tool for studying stars using the properties of observed modes of oscillation. So far the process of performing an asteroseismic analysis of a star has remained somewhat esoteric and inaccessible to nonexperts. In this software paper we describe PBjam, an open-source Python package for analyzing the frequency spectra of solar-like oscillators in a simple but principled and automated way. The aim of PBjam is to provide a set of easy-to-use tools to extract information about the radial and quadropole oscillations in stars that oscillate like the Sun, which may then be used to infer bulk properties such as stellar mass, radius, age, or even structure. Asteroseismology and its data analysis methods are becoming increasingly important as space-based photometric observatories are producing a wealth of new data, allowing asteroseismology to be applied in a wide range of contexts such as exoplanet, stellar structure and evolution, and Galactic population studies.

Since the onset of the “space revolution” of high-precision high-cadence photometry, asteroseismology has been demonstrated as a powerful tool for informing Galactic archeology investigations. The launch of the NASA Transiting Exoplanet Survey Satellite (TESS) mission has enabled seismic-based inferences to go full sky—providing a clear advantage for large ensemble studies of the different Milky Way components. Here we demonstrate its potential for investigating the Galaxy by carrying out the first asteroseismic ensemble study of red giant stars observed by TESS. We use a sample of 25 stars for which we measure their global asteroseimic observables and estimate their fundamental stellar properties, such as radius, mass, and age. Significant improvements are seen in the uncertainties of our estimates when combining seismic observables from TESS with astrometric measurements from the Gaia mission compared to when the seismology and astrometry are applied separately. Specifically, when combined we show that stellar radii can be determined to a precision of a few percent, masses to 5%–10%, and ages to the 20% level. This is comparable to the precision typically obtained using end-of-mission Kepler data.

Context. The Transiting Exoplanet Survey Satellite (TESS) is observing bright known planet-host stars across almost the entire sky. These stars have been subject to extensive ground-based observations, providing a large number of radial velocity measurements.Aims. The objective of this work is to use the new TESS photometric observations to characterize the star lambda (2) Fornacis, and following this to update the parameters of the orbiting planet lambda (2) For b.Methods. We measured the frequencies of the p-mode oscillations in lambda (2) For, and in combination with non-seismic parameters estimated the stellar fundamental properties using stellar models. Using the revised stellar properties and a time series of archival radial velocities from the UCLES, HIRES and HARPS instruments spanning almost 20 years, we refit the orbit of lambda (2) For b and searched the residual radial velocities for remaining variability.Results. We find that lambda (2) For has a mass of 1.160.03 M-circle dot and a radius of 1.63 +/- 0.04 R-circle dot, with an age of 6.3 +/- 0.9 Gyr. This and the updated radial velocity measurements suggest a mass of lambda (2) For b of 16.8(-1.3)(+1.2)M(circle plus) 16 . 8 - 1.3 + 1.2 M circle plus , which is similar to 5M(circle plus) less than literature estimates. We also detect an additional periodicity at 33 days in the radial velocity measurements, which is likely due to the rotation of the host star.Conclusions. While previous literature estimates of the properties of lambda (2) For are ambiguous, the asteroseismic measurements place the star firmly at the early stage of its subgiant evolutionary phase. Typically only short time series of photometric data are available from TESS, but by using asteroseismology it is still possible to provide tight constraints on the properties of bright stars that until now have only been observed from the ground. This prompts a reexamination of archival radial velocity data that have been accumulated in the past few decades in order to update the characteristics of the planet hosting systems observed by TESS for which asteroseismology is possible.

Context. The Transiting Exoplanet Survey Satellite (TESS) is observing bright known planet-host stars across almost the entire sky. These stars have been subject to extensive ground-based observations, providing a large number of radial velocity measurements. Aims. The objective of this work is to use the new TESS photometric observations to characterize the star λ2 Fornacis, and following this to update the parameters of the orbiting planet λ2 For b. Methods. We measured the frequencies of the p-mode oscillations in λ2 For, and in combination with non-seismic parameters estimated the stellar fundamental properties using stellar models. Using the revised stellar properties and a time series of archival radial velocities from the UCLES, HIRES and HARPS instruments spanning almost 20 years, we refit the orbit of λ2 For b and searched the residual radial velocities for remaining variability. Results. We find that λ2 For has a mass of 1.16 ± 0.03 M and a radius of 1.63 ± 0.04 R , with an age of 6.3 ± 0.9 Gyr. This and the updated radial velocity measurements suggest a mass of λ2 For b of 16.8+1.2 −1.3 M⊕, which is ∼5M⊕ less than literature estimates. We also detect an additional periodicity at 33 days in the radial velocity measurements, which is likely due to the rotation of the host star. Conclusions. While previous literature estimates of the properties of λ2 For are ambiguous, the asteroseismic measurements place the star firmly at the early stage of its subgiant evolutionary phase. Typically only short time series of photometric data are available from TESS, but by using asteroseismology it is still possible to provide tight constraints on the properties of bright stars that until now have only been observed from the ground. This prompts a reexamination of archival radial velocity data that have been accumulated in the past few decades in order to update the characteristics of the planet hosting systems observed by TESS for which asteroseismology is possible.

The National Airspace System is a highly complex system of systems within which a number of participants with widely varying business and operating models exist. From the airspace user's perspective, a means by which to operate flights in a more flexible and efficient manner is highly desired to meet their business objectives. From the air navigation service provider's viewpoint, there is a need for increasing the capacity of the airspace, while maintaining or increasing the levels of efficiency and safety that currently exist in order to meet the charter under which they operate. Enhancing the communication between airspace operators and users is essential in order to meet these demands. In the spring of 2015, a prototype system that implemented an airborne tool to optimize en-route flight paths for fuel and time savings was designed and tested. The system utilized in-flight Internet as a high-bandwidth data link to facilitate collaborative decision making between the flight deck and an airline dispatcher. The system was tested and demonstrated in a laboratory environment, as well as in-situ. Initial results from these tests indicate that this system is not only feasible, but could also serve as a growth path and testbed for future air traffic management concepts that rely on shared situational awareness through data exchange and electronic negotiation between multiple entities operating within the National Airspace System.

There is an overwhelming desire to create and enhance communication mechanisms between entities that operate within the National Airspace System. Furthermore, airlines are always extremely interested in increasing the efficiency of their flights. An innovative system prototype was developed and tested that improves collaborative decision making without modifying existing infrastructure or operational procedures within the current Air Traffic Management System. This system enables collaboration between flight crew and airline dispatchers to share and assess optimized flight routes through an Internet connection. Using a sophisticated medium-fidelity flight simulation environment, a rapid-prototyping development, and a unified modeling language, the software was designed to ensure reliability and scalability for future growth and applications. Ensuring safety and security were primary design goals, therefore the software does not interact or interfere with major flight control or safety systems. The system prototype demonstrated an unprecedented use of in-flight Internet to facilitate effective communication with Airline Operations Centers, which may contribute to increased flight efficiency for airlines.

The K2 mission is a repurposed use of the Kepler spacecraft to perform high-precision photometry of selected fields in the ecliptic. We have developed an aperture photometry pipeline for K2 data which performs dynamic automated aperture mask selection, background estimation and subtraction, and positional decorrelation to minimize the effects of spacecraft pointing jitter. We also identify secondary targets in the K2 “postage stamps” and produce light curves for those targets as well. Pipeline results will be made available to the community. Here we describe our pipeline and the photometric precision we are capable of achieving with K2, and illustrate its utility with asteroseismic results from the serendipitous secondary targets.