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Register a new userThe K2 Galactic Archaeology Program Data Release 3: Age-abundance patterns in C1-C8, C10-C18
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We present the third and final data release of the K2 Galactic Archaeology Program (K2 GAP) for Campaigns C1-C8 and C10-C18. We provide asteroseismic radius and mass coefficients, $kappa_R$ and $kappa_M$, for $sim 19,000$ red giant stars, which translate directly to radius and mass given a temperature. As such, K2 GAP DR3 represents the largest asteroseismic sample in the literature to date. K2 GAP DR3 stellar parameters are calibrated to be on an absolute parallactic scale based on Gaia DR2, with red giant branch and red clump evolutionary state classifications provided via a machine-learning approach. Combining these stellar parameters with GALAH DR3 spectroscopy, we determine asteroseismic ages with precisions of $sim 20-30%$ and compare age-abundance relations to Galactic chemical evolution models among both low- and high-$alpha$ populations for $alpha$, light, iron-peak, and neutron-capture elements. We confirm recent indications in the literature of both increased Ba production at late Galactic times, as well as significant contribution to r-process enrichment from prompt sources associated with, e.g., core-collapse supernovae. With an eye toward other Galactic archaeology applications, we characterize K2 GAP DR3 uncertainties and completeness using injection tests, suggesting K2 GAP DR3 is largely unbiased in mass/age and with uncertainties of $2.9%,(rm{stat.}),pm0.1%,(rm{syst.})$ & $6.7%,(rm{stat.}),pm0.3%,(rm{syst.})$ in $kappa_R$ & $kappa_M$ for red giant branch stars and $4.7%,(rm{stat.}),pm0.3%,(rm{syst.})$ & $11%,(rm{stat.}),pm0.9%,(rm{syst.})$ for red clump stars. We also identify percent-level asteroseismic systematics, which are likely related to the time baseline of the underlying data, and which therefore should be considered in TESS asteroseismic analysis.
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NASAs K2 mission is observing tens of thousands of stars along the ecliptic, providing data suitable for large scale asteroseismic analyses to inform galactic archaeology studies. Its first campaign covered a field near the north galactic cap, a region never covered before by large asteroseismic-ensemble investigations, and was therefore of particular interest for exploring this part of our Galaxy. Here we report the asteroseismic analysis of all stars selected by the K2 Galactic Archaeology Program during the missions North Galactic Cap campaign 1. Our consolidated analysis uses six independent methods to measure the global seismic properties, in particular the large frequency separation, and the frequency of maximum power. From the full target sample of 8630 stars we find about 1200 oscillating red giants, a number comparable with estimates from galactic synthesis modeling. Thus, as a valuable by-product we find roughly 7500 stars to be dwarfs, which provide a sample well suited for galactic exoplanet occurrence studies because they originate from our simple and easily reproducible selection function. In addition, to facilitate the full potential of the data set for galactic archaeology we assess the detection completeness of our sample of oscillating red giants. We find the sample is at least near complete for stars with 40 < numax/microHz < 270, and numax_detec < 2.6*1e6 * 2e-Kp microHz. There is a detection bias against helium core burning stars with numax ~ 30 microHz, affecting the number of measurements of DeltaNu and possibly also numax. Although we can detect oscillations down to Kp = 15, our campaign 1 sample lacks enough faint giants to assess the detection completeness for stars fainter than Kp ~ 14.5.
Studies of Galactic structure and evolution have benefitted 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 $textit{en masse}$, 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 $ u_{mathrm{max}}$ and $Delta u$ 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 & mass coefficients, $kappa_R$ & $kappa_M$, 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 $3.3% mathrm{ (stat.)} pm 1% mathrm{ (syst.)}$ for $kappa_R$ and $7.7% mathrm{ (stat.)} pm 2% mathrm{ (syst.)}$ for $kappa_M$ among RGB stars, and $5.0% mathrm{ (stat.)} pm 1% mathrm{ (syst.)}$ for $kappa_R$ and $10.5% mathrm{ (stat.)} pm 2% mathrm{ (syst.)}$ for $kappa_M$ among RC stars. We verify that the sample is nearly complete -- except for a dearth of stars with $ u_{mathrm{max}} lesssim 10-20mu$Hz -- by comparing to Galactic models and visual inspection. Our asteroseismic radii agree with radii derived from Gaia Data Release 2 parallaxes to within $2.2 pm 0.3%$ for RGB stars and $2.0 pm 0.6%$ for RC stars.
A tutorial for the Stellar Abundances for Galactic Archaeology (SAGA) database is presented. This paper describes the outline of the database, reports the current status of the data compilation and known problems, and presents plans for future updates and extensions.
We produce a clean and well-characterised catalogue of objects within 100,pc of the Sun from the G Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best practices for its use. The selection of objects within 100,pc from the full catalogue used selected training sets, machine-learning procedures, astrometric quantities, and solution quality indicators to determine a probability that the astrometric solution is reliable. The training set construction exploited the astrometric data, quality flags, and external photometry. For all candidates we calculated distance posterior probability densities using Bayesian procedures and mock catalogues to define priors. Any object with reliable astrometry and a non-zero probability of being within 100,pc is included in the catalogue. We have produced a catalogue of NFINAL objects that we estimate contains at least 92% of stars of stellar type M9 within 100,pc of the Sun. We estimate that 9% of the stars in this catalogue probably lie outside 100,pc, but when the distance probability function is used, a correct treatment of this contamination is possible. We produced luminosity functions with a high signal-to-noise ratio for the main-sequence stars, giants, and white dwarfs. We examined in detail the Hyades cluster, the white dwarf population, and wide-binary systems and produced candidate lists for all three samples. We detected local manifestations of several streams, superclusters, and halo objects, in which we identified 12 members of G Enceladus. We present the first direct parallaxes of five objects in multiple systems within 10,pc of the Sun.
In this letter, we have carried out an independent validation of the Gaia EDR3 photometry using about 10,000 Landolt standard stars from Clem & Landolt (2013). Using a machine learning technique, the UBVRI magnitudes are converted into the Gaia magnitudes and colors and then compared to those in the EDR3, with the effect of metallicity incorporated. Our result confirms the significant improvements in the calibration process of the Gaia EDR3. Yet modest trends up to 10 mmag with G magnitude are found for all the magnitudes and colors for the 10 < G < 19 mag range, particularly for the bright and faint ends. With the aid of synthetic magnitudes computed on the CALSPEC spectra with the Gaia EDR3 passbands, absolute corrections are further obtained, paving the way for optimal usage of the Gaia EDR3 photometry in high accuracy investigations.
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