Stellar Sample Research Articles

Ages of Stars and Planets in the Kepler Field Younger than Four Billion Years

Recent analyses of FGK stars in open clusters have helped clarify the precision with which a star’s rotation rate and lithium content can be used as empirical indicators for its age. Here we apply this knowledge to stars observed by Kepler. Rotation periods are drawn from previous work; lithium is measured from new and archival Keck/HIRES spectra. We report rotation-based ages for 23,813 stars (harboring 795 known planets) for which our method is applicable. We find that our rotational ages recover the ages of stars in open clusters spanning 0.04–2.5 Gyr; they also agree with ≳90% of the independent lithium ages. The resulting yield includes 63 planets younger than 1 Gyr at 2σ, and 109 with median ages below 1 Gyr. This is about half the number expected under the classic assumption of a uniform star formation history. The age distribution that we observe, rather than being uniform, shows that the youngest stars in the Kepler field are 3–5 times rarer than stars 3 Gyr old. This trend holds for both known planet hosts and for the parent stellar sample. We attribute this “demographic cliff” to a combination of kinematic heating and a declining star formation rate in the Galaxy’s thin disk, and highlight its impact on the age distribution of known transiting exoplanets.

Ionising properties of galaxies in JADES for a stellar mass complete sample: resolving the cosmic ionising photon budget crisis at the Epoch of Reionisation

Abstract We use NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) to study the ionising properties of a sample of 14652 galaxies at 3 ≤ zphot ≤ 9, 90% complete in stellar mass down to log(M⋆/[M⊙]) ≈ 7.5. Out of the full sample, 1620 of the galaxies have spectroscopic redshift measurements from the literature. We use the spectral energy distribution fitting code Prospector to fit all available photometry and infer galaxy properties. We find a significantly milder evolution of the ionising photon production efficiency (ξion) with redshift and UV magnitude than previously reported. Interestingly, we observe two distinct populations in ξion, distinguished by their burstiness (given by SFR10/SFR100). Both populations show the same evolution with z and MUV, but have a different ξion normalisation. We convolve the more representative log (ξion(z, MUV)) relations (accounting for ∼97% of the sample), with luminosity functions from literature, to place constraints on the cosmic ionising photon budget. By combining our results, we find that one of our models can match the observational constraints from the Lyα forest at z ≲ 6. We conclude that galaxies with MUV between −16 and −20, adopting a reasonable escape fraction, can produce enough ionising photons to ionise the Universe, without exceeding the required ionising photon budget.

The Gaia-ESO survey: New spectroscopic binaries in the Milky Way

The survey (GES) is a large public spectroscopic survey that acquired spectra for more than stars across all major components of the Milky Way. In addition to atmospheric parameters and stellar abundances that have been derived in previous papers of this series, the GES spectra allow us to detect spectroscopic binaries with one (SB1), two (SB2), or more (SB$n 3$) components. The present paper discusses the statistics of GES SB$n 2$ after analysing GIRAFFE HR10 and HR21 spectra, amounting to unique Milky Way field targets. Cross-correlation functions (CCFs) have been re-computed thanks to a dozen spectral masks probing a range of effective temperatures ($ kelvin < T_ eff kelvin $), surface gravities ($1.0 < g < 4.7$), and metallicities ($-2.6 < Fe H < 0.3$). By optimising the mask choice for a given spectrum, the newly computed, so-called (NArrow CRoss-correlation Experiment) CCFs are narrower and allow more stellar components to be unblended than standard masks. The (Detection Of Extrema) extremum-finding code then selects the individual components and provides their radial velocities. From the sample of HR10 and HR21 spectra corresponding to objects the present study leads to the detection of SB2, ten SB3 (three of them being tentative), and two tentative SB4. In particular, compared to our previous study, the CCFs allowed us to multiply the number of SB2 candidates by $ The colour-magnitude diagram reveals, as expected, the shifted location of the SB2 main sequence. A comparison between the SB identified in DR3 and the ones detected in the present work was performed and the complementarity of the two censuses is discussed. An application to the mass-ratio determination is presented, and the mass-ratio distribution of the GES SB2 is discussed. When accounting for the SB2 detection rate, an SB2 frequency of $ percent $ is derived within the present stellar sample of mainly FGK-type stars. As primary outliers identified within the GES data, SB$n$ spectra produce a wealth of information and useful constraints for the binary population synthesis studies.

Modelling stellar irradiances I: the transition regions of FGKM stars

ABSTRACT We employed advanced ionization equilibrium models that we developed in Dufresne et al. (2024), which include charge transfer and density effects, to model UV stellar irradiances for a sample of stars. Our sample includes $\epsilon$ Eridani (K2 V), $\alpha$ Centauri A (G2 V), Procyon (F5 V), and Proxima Centauri (M5.5 Ve). We measured line fluxes from STIS data sets and used O iv and O v as density diagnostics to find the formation pressure of ions in the transition region (TR) and adopted a simple differential emission measure (DEM) modelling. Our findings indicate significant improvements in modelling spectral lines from anomalous ions such as Si iv, C iv, and N v of the Li- and Na-like sequences, which produce the strongest lines in the UV. For example, the Si iv lines were under-predicted by a factor of 5 and now are within 40 per cent the observed fluxes. The improved models allow us to obtain for the first time reliable estimates of some stellar chemical abundances in the TR. We compared our results with available photospheric abundances in the literature and found no evidence for the first ionization potential (FIP) effect in the TR of our stellar sample. Finally, we compared our results with the solar TR that can also be described by photospheric abundances.

Chemical composition of planetary hosts: C, N, and α-element abundances

Accurate atmospheric parameters and chemical composition of planet hosts play a major role in characterising exoplanets and understanding their formation and evolution. Our objective is to uniformly determine atmospheric parameters and chemical abundances of carbon (C), nitrogen (N), oxygen(O), and the alpha -elements, magnesium (Mg) and silicon (Si), along with C/O, N/O and Mg/Si abundance ratios for planet-hosting stars. In this analysis, we aim to investigate the potential links between stellar chemistry and the presence of planets. e tai Observatory telescope. The determination of stellar parameters was based on a standard analysis using equivalent widths and one-dimensional, plane-parallel model atmospheres calculated under the assumption of local thermodynamical equilibrium. The differential synthetic spectrum method was used to uniformly determine the carbon C(C2), nitrogen N(CN), oxygen O I magnesium Mg I, and silicon Si I elemental abundances as well as the C/O, N/O, and Mg/Si ratios. We analysed elemental abundances and ratios in dwarf and giant stars, finding that C/Fe O/Fe and Mg/Fe are lower in metal-rich dwarf hosts; whereas N/Fe is close to the Solar ratio. Giants show smaller scatter in C/Fe and O/Fe and lower than the Solar average C/Fe and C/O ratios. The (C+N+O) abundances increase with Fe/H in giant stars, with a minimal scatter. We also noted an overabundance of Mg and Si in planet-hosting stars, particularly at lower metallicities, and a lower Mg/Si ratio in stars with planets. In giants hosting high-mass planets, nitrogen shows a moderate positive relationship with planet mass. C/O and N/O ratios show moderate negative and positive slopes in giant stars, respectively. The Mg/Si ratio shows a negative correlation with planet mass across the entire stellar sample.

Dust and power: Unravelling the merger-active galactic nucleus connection in the second half of cosmic history

Galaxy mergers represent a fundamental physical process under hierarchical structure formation, but their role in triggering active galactic nuclei (AGNs) is still unclear. We aim to investigate the merger-AGN connection using state-of-the-art observations and novel methods for detecting mergers and AGNs. We selected stellar mass-limited samples at redshift $z<1$ from the Kilo-Degree Survey (KiDS), focussing on the KiDS-N-W2 field with a wide range of multi-wavelength data. We analysed three AGN types, selected in the mid-infrared (MIR), X-ray, and via spectral energy distribution (SED) modelling. To identify mergers, we used convolutional neural networks (CNNs) trained on two cosmological simulations. We created mass- and redshift-matched control samples of non-mergers and non-AGNs. We first investigated the merger-AGN connection using a binary AGN/non-AGN classification. We observed a clear AGN excess (of a factor of $2-3$) in mergers with respect to non-mergers for the MIR AGNs, along with a mild excess for the X-ray and SED AGNs. This result indicates that mergers could trigger all three types, but are more connected to the MIR AGNs. About half of the MIR AGNs are in mergers but it is unclear whether mergers are the main trigger. For the X-ray and SED AGNs, mergers are unlikely to be the dominant triggering mechanism. We also explored the connection using the continuous AGN fraction $f_ AGN $ parameter. Mergers exhibit a clear excess of high $f_ AGN $ values relative to non-mergers, for all AGN types. We unveil the first merger fraction $f_ merger - f_ AGN $ relation with two distinct regimes. When the AGN is not very dominant, the relation is only mildly increasing or even flat, with the MIR AGNs showing the highest $f_ merger $. In the regime of very dominant AGNs ($f_ AGN merger $ shows the same steeply rising trend with increasing $f_ AGN $ for all AGN types. These trends are also seen when plotted against AGN bolometric luminosity. We conclude that mergers are most closely connected to dust-obscured AGNs, generally linked to a fast-growing phase of the supermassive black hole. Such mergers therefore stand as the main (or even the sole) fuelling mechanism of the most powerful AGNs.

Abundances of Planetary Nebulae and Evolved Stars: Iron and Sulfur Depletion, and Carbon and Nitrogen Enrichment, in Low- and Intermediate-mass Stellar Populations in the Milky Way

We research the elemental abundances in Galactic planetary nebulae (PNe) compared with those of their stellar progenitors (red giant branch and asymptotic giant branch, AGB, stars), to explore and quantify the expected—i.e., due to AGB evolution or condensation onto grains—differences. We gleaned the current literature for the nebular abundances while we used the APOGEE DR 17 survey data for the stellar sample. We examined the elements in common between the nebular and stellar samples, namely, C, N, O, Fe, and S. We confirm that iron in PNe is mostly entrapped in grains, with an average depletion 〈D[Fe/H]〉 = 1.741 ± 0.486 dex, and we disclose a weak correlation between iron depletion and the [O/H] abundance, D[Fe/H] = (6.6003 ± 2.443) × [O/H] + (1.972 ± 0.199). Sulfur may also be mildly depleted in PNe, with 〈D[S/H]〉 = 0.179 ± 0.291 dex. We also found an indication of nitrogen enrichment for PNe 〈E[N/H]〉 = 0.393 ± 0.421 dex, with maximum enrichment (0.980 ± 0.243) occurring for the PNe whose progenitors have gone through the hot-bottom burning. The carbon enrichment is 〈E[C/H]〉 = 0.337 ± 0.463 dex when measured for the general PN populations. Our results will be relevant for future Galactic and extragalactic studies comparing nebular and stellar samples.

SFNet: Stellar Feature Network with CWT for Stellar Spectra Recognition

Stellar spectral classification is crucial in astronomical data analysis. However, existing studies are often limited by the uneven distribution of stellar samples, posing challenges in practical applications. Even when balancing stellar categories and their numbers, there is room for improvement in classification accuracy. This study introduces a Continuous Wavelet Transform using the Super Morlet wavelet to convert stellar spectra into wavelet images. A novel neural network, the Stellar Feature Network, is proposed for classifying these images. Stellar spectra from Large Sky Area Multi-Object Fiber Spectroscopic Telescope DR9, encompassing five equal categories (B, A, F, G, K), were used. Comparative experiments validate the effectiveness of the proposed methods and network, achieving significant improvements in classification accuracy.

DESI Early Data Release Milky Way Survey value-added catalogue

ABSTRACT We present the stellar value-added catalogue based on the Dark Energy Spectroscopic Instrument (DESI) Early Data Release. The catalogue contains radial velocity and stellar parameter measurements for $\simeq$ 400 000 unique stars observed during commissioning and survey validation by DESI. These observations were made under conditions similar to the Milky Way Survey (MWS) currently carried out by DESI but also include multiple specially targeted fields, such as those containing well-studied dwarf galaxies and stellar streams. The majority of observed stars have $16\lt r\lt 20$ with a median signal-to-noise ratio in the spectra of $\sim$ 20. In the paper, we describe the structure of the catalogue, give an overview of different target classes observed, as well as provide recipes for selecting clean stellar samples. We validate the catalogue using external high-resolution measurements and show that radial velocities, surface gravities, and iron abundances determined by DESI are accurate to 1 km s−1, 0.3 dex, and $\sim$ 0.15 dex respectively. We also demonstrate possible uses of the catalogue for chemo-dynamical studies of the Milky Way stellar halo and Draco dwarf spheroidal. The value-added catalogue described in this paper is the very first DESI MWS catalogue. The next DESI data release, expected in less than a year, will add the data from the first year of DESI survey operations and will contain approximately 4 million stars, along with significant processing improvements.

GalaxyFlow: upsampling hydrodynamical simulations for realistic mock stellar catalogues

ABSTRACT Cosmological N-body simulations of galaxies operate at the level of ‘star particles’ with a mass resolution on the scale of thousands of solar masses. Turning these simulations into stellar mock catalogues requires ‘upsampling’ the star particles into individual stars following the same phase-space density. In this paper, we introduce two new upsampling methods. First, we describe GalaxyFlow, a sophisticated upsampling method that utilizes normalizing flows to both estimate the stellar phase-space density and sample from it. Secondly, we improve on existing upsamplers based on adaptive kernel density estimation (KDE), using maximum likelihood estimation to fine-tune the bandwidth for such algorithms in a way that improves both the density estimation accuracy and upsampling results. We demonstrate our upsampling techniques on a neighbourhood of the Solar location in two simulated galaxies: Auriga 6 and h277. Both yield smooth stellar distributions that closely resemble the stellar densities seen in the Gaia DR3 catalogue. Furthermore, we introduce a novel multimodel classifier test to compare the accuracy of different upsampling methods quantitatively. This test confirms that GalaxyFlow more accurately estimates the density of the underlying star particles than methods based on KDE, at the cost of being more computationally intensive.

Galaxy–Galaxy Lensing Data: f(T) Gravity Challenges General Relativity

We use galaxy–galaxy lensing data to test general relativity and f(T) gravity at galaxy scales. We consider an exact spherically symmetric solution of f(T) theory, which is obtained from an approximate quadratic correction, and thus it is expected to hold for every realistic deviation from general relativity. Quantifying the deviation by a single parameter Q, and following the post-Newtonian approximation, we obtain the corresponding deviation in the gravitational potential, shear component, and effective excess surface density profile. We used five stellar mass samples and divided them into blue and red galaxies to test the model dependence on galaxy color, and we modeled the excess surface density profiles using the Navarro–Frenk–White profiles. Based on the group catalog from the Sloan Digital Sky Survey Data Release 7 (SDSS DR7) we finally extract Q=−2.138−0.516+0.952×10−5 Mpc−2 at 1σ confidence. This result indicates that f(T) corrections on top of general relativity are favored. Finally, we apply information criteria, such as the Akaike and Bayesian ones, and although the dependence of f(T) gravity on the off-center effect implies that its optimality needs to be carefully studied, our analysis shows that f(T) gravity is more efficient in fitting the data compared to general relativity and the ΛCDM paradigm, and thus it offers a challenge to the latter.

Statistical relations between spectropolarimetric observables and the polar strength of the stellar dipolar magnetic field

Global magnetic fields of early-type stars are commonly characterised by the mean longitudinal magnetic field 〈Bz〉 and the mean field modulus 〈B〉, derived from the circular polarisation and intensity spectra, respectively. Observational studies often report a root mean square (rms) of 〈Bz〉 and an average value of 〈B〉. In this work, I used numerical simulations to establish statistical relationships between these cumulative magnetic observables and the polar strength, Bd, of a dipolar magnetic field. I show that in the limit of many measurements randomly distributed in rotational phase, 〈Bz〉rms = 0.179−0.043+0.031 Bd and 〈B〉avg = 0.691−0.023+0.020 Bd. The same values can be recovered with only three measurements, provided that the observations are distributed uniformly in the rotational phase. These conversion factors are suitable for ensemble analyses of large stellar samples, where each target is covered by a small number of magnetic measurements.

Detection of extragalactic magnetic massive stars

odot $ leave behind neutron stars and black holes by the end of their evolution. The merging of binary compact remnant systems produces astrophysical transients detectable by gravitational wave observatories. Studies of magnetic fields in massive stars with low metallicities are of particular interest because they provide important information on the role of magnetic fields in the star formation of the early Universe. While several detections of massive Galactic magnetic stars have been reported in the last few decades, the impact of a low-metallicity environment on the occurrence and strength of stellar magnetic fields has not yet been explored. Because of the similarity between Of?p stars in the Magellanic Clouds (MCs) and Galactic magnetic Of?p stars, which possess globally organised magnetic fields, we searched for magnetic fields in Of?p stars in the MCs. Additionally, we observed the massive contact binary Cl$*$ NGC\,346\,SSN7 in the Small Magellanic Cloud to test the theoretical scenario that the origin of magnetic fields involves a merger event or a common envelope evolution. We obtained and analysed measurements of the magnetic field in four massive Of?p stars in the MCs and the binary Cl$*$ NGC\,346\,SSN7 using the ESO/VLT FORS2 spectrograph in spectropolarimetric mode. We detected kilogauss-scale magnetic fields in two Of?p-type stars and in the contact binary Cl$*$ NGC\,346\,SSN7. These results suggest that the impact of low metallicity on the occurrence and strength of magnetic fields in massive stars is low. However, because the explored stellar sample is very small, additional observations of massive stars in the MCs are necessary.

Investigating Mass Segregation of the Binary Stars in the Open Cluster NGC 6819

We search for mass segregation in the intermediate-aged open cluster NGC 6819 within a carefully identified sample of probable cluster members. Using photometry from Gaia, Pan-STARRS, and the Two Micron All Sky Survey as inputs for a Bayesian statistics software suite, BASE-9, we identify a rich population of (photometric) binaries and derive posterior distributions for the cluster age, distance, metallicity, and reddening, as well as star-by-star photometric membership probabilities, masses, and mass ratios (for binaries). Within our entire sample, we identify 2632 cluster members and 777 binaries. We then select a main-sequence “primary sample” with 14.85 <G < 19.5, containing 1342 cluster members and 250 binaries with mass ratios q > 0.5, to investigate mass segregation. Within this primary sample, we find the binary radial distribution is significantly shifted toward the cluster center as compared to the single stars, resulting in a binary fraction that increases significantly toward the cluster core. Furthermore, we find that within the binary sample, more massive binaries have more centrally concentrated radial distributions than less massive binaries. The same is true for the single stars. We verify the expectation of mass segregation for this stellar sample in NGC 6819 through both relaxation time arguments and by investigating a sophisticated N-body model of the cluster. Importantly, this is the first study to investigate mass segregation of the binaries in the open cluster NGC 6819.

Age Determination of LAMOST Red Giant Branch Stars Based on the Gradient Boosting Decision Tree Method

In this study, we estimate the stellar ages of LAMOST DR8 red giant branch (RGB) stars based on the gradient boosting decision tree (GBDT) algorithm. We used 2643 RGB stars extracted from the APOKASC-2 asteroseismological catalog as the training data set. After selecting the parameters ([α/Fe], [C/Fe], T eff, [N/Fe], [C/H], log g) highly correlated with age using GBDT, we apply the same GBDT method to the new catalog of more than 590,000 stars classified as RGB stars. The test data set shows that the median relative error is around 11.6% for the method. We also compare the predicted ages of RGB stars with other studies (e.g., based on APOGEE) and find some systematic differences. The final uncertainty is about 15%–30% compared to the ages of open clusters. Then, we present the spatial distribution of the RGB sample with an age determination, which could recreate the expected result, and discuss systematic biases. All these diagnostics show that one can apply the GBDT method to other stellar samples to estimate atmospheric parameters and age.

CatNorth: An Improved Gaia DR3 Quasar Candidate Catalog with Pan-STARRS1 and CatWISE

A complete and pure sample of quasars with accurate redshifts is crucial for quasar studies and cosmology. In this paper, we present CatNorth, an improved Gaia Data Release 3 (Gaia DR3) quasar candidate catalog with more than 1.5 million sources in the 3π sky built with data from Gaia, Pan-STARRS1, and CatWISE2020. The XGBoost algorithm is used to reclassify the original Gaia DR3 quasar candidates as stars, galaxies, and quasars. To construct training/validation data sets for the classification, we carefully built two different master stellar samples in addition to the spectroscopic galaxy and quasar samples. An ensemble classification model is obtained by averaging two XGBoost classifiers trained with different master stellar samples. Using a probability threshold of p QSO_mean > 0.95 in our ensemble classification model and an additional cut on the logarithmic probability density of zero proper motion, we retrieved 1,545,514 reliable quasar candidates from the parent Gaia DR3 quasar candidate catalog. We provide photometric redshifts for all candidates with an ensemble regression model. For a subset of 89,100 candidates, accurate spectroscopic redshifts are estimated with the convolutional neural network from the Gaia BP/RP spectra. The CatNorth catalog has a high purity of ∼90%, while maintaining high completeness, which is an ideal sample to understand the quasar population and its statistical properties. The CatNorth catalog is used as the main source of input catalog for the Large Sky Area Multi-Object Fiber Spectroscopic Telescope phase III quasar survey, which is expected to build a highly complete sample of bright quasars with i < 19.5.

Cluster cosmology without cluster finding

ABSTRACT We propose that observations of supermassive galaxies contain cosmological statistical constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a fiducial spectroscopic and stellar mass complete sample of galaxies drawn from the Dark Energy Spectroscopic Instrument (DESI) and forecast how constraints on Ωm–σ8 from this sample will compare with those from number counts of clusters based on richness λ. At fixed number density, we find that massive galaxies offer similar constraints to galaxy clusters. However, a mass-complete galaxy sample from DESI has the potential to probe lower halo masses than standard optical cluster samples (which are typically limited to λ ≳ 20 and Mhalo ≳ 1013.5 M⊙ h−1); additionally, it is straightforward to cleanly measure projected galaxy clustering wp for such a DESI sample, which we show can substantially improve the constraining power on Ωm. We also compare the constraining power of M*-limited samples to those from larger but mass-incomplete samples [e.g. the DESI Bright Galaxy Survey (BGS) sample]; relative to a lower number density M*-limited samples, we find that a BGS-like sample improves statistical constraints by 60 per cent for Ωm and 40 per cent for σ8, but this uses small-scale information that will be harder to model for BGS. Our initial assessment of the systematics associated with supermassive galaxy cosmology yields promising results. The proposed samples have a ∼10 per cent satellite fraction, but we show that cosmological constraints may be robust to the impact of satellites. These findings motivate future work to realize the potential of supermassive galaxies to probe lower halo masses than richness-based clusters and to potentially avoid persistent systematics associated with optical cluster finding.

Predicted asteroseismic detection yield for solar-like oscillating stars with PLATO

Aims.In this work, we determine the expected yield of detections of solar-like oscillations for the targets of the foreseen PLATO ESA mission. Our estimates are based on a study of the detection probability, which takes into account the properties of the target stars, using the information available in the PIC 1.1.0, including the current best estimate of the signal-to-noise ratio (S/N). The stellar samples, as defined for this mission, include those with the lowest noise level (P1 and P2 samples) and the P5 sample, which has a higher noise level. For the P1 and P2 samples, the S/N is high enough (by construction) that we can assume that the individual mode frequencies can be measured. For these stars, we estimate the expected uncertainties in mass, radius, and age due to statistical errors induced by uncertainties from the observations only.Methods.We used a formulation from the literature to calculate the detection probability. We validated this formulation and the underlying assumptions withKeplerdata. Once validated, we applied this approach to the PLATO samples. Using againKeplerdata as a calibration set, we also derived relations to estimate the uncertainties of seismically inferred stellar mass, radius, and age. We then applied those relations to the main sequence stars with masses equal to or below 1.2M⊙belonging to the PLATO P1 and P2 samples and for which we predict a positive seismic detection.Results.We found that we can expect positive detections of solar-like oscillations for more than 15 000 FGK stars in one single field after a two-year observation run. Among them, 1131 main sequence stars with masses of ≤1.2 M⊙satisfy the PLATO requirements for the uncertainties of the seismically inferred stellar masses, radii, and ages. The baseline observation programme of PLATO consists of observing two fields of similar size (one in the southern hemisphere and one in the northern hemisphere) for two years apiece. Accordingly, the expected seismic yields of the mission amount to over 30 000 FGK dwarfs and subgiants, with positive detections of solar-like oscillations. This sample of expected solar-like oscillating stars is large enough to enable the PLATO mission’s stellar objectives to be amply satisfied.Conclusions.The PLATO mission is expected to produce a catalog sample of extremely well seismically characterized stars of a quality that is equivalent to theKeplerLegacy sample, but containing a number that is about 80 times greater, when observing two PLATO fields for two years apiece. These stars are a gold mine that will make it possible to make significant advances in stellar modelling.

Investigating APOKASC Red Giant Stars with Abnormal Carbon-to-nitrogen Ratios

The success of galactic archeology and the reconstruction of the formation history of our Galaxy relies critically on precise ages for large populations of stars. For evolved stars in the red clump and red giant branch, the carbon-to-nitrogen ratio ([C/N]) has recently been identified as a powerful diagnostic of mass and age that can be applied to stellar samples from spectroscopic surveys such as Sloan Digital Sky Survey/APOGEE. Here, we show that at least 10% of red clump stars and red giant branch stars deviate from the standard relationship between [C/N] and mass. We use the APOGEE–Kepler (APOKASC) overlap sample to show that binary interactions are responsible for the majority of these outliers and that stars with indicators of current or previous binarity should be excluded from galactic archeology analyses that rely on [C/N] abundances to infer stellar masses. We also show that the Data Release 14 APOGEE analysis overestimates the surface gravities for even moderately rotating giants (vsini > 2 km s−1).

Planet formation throughout the Milky Way

As stellar compositions evolve over time in the Milky Way, so will the resulting planet populations. In order to place planet formation in the context of Galactic chemical evolution, we made use of a large (N = 5325) stellar sample representing the thin and thick discs, defined chemically, and the halo, and we simulated planet formation by pebble accretion around these stars. We built a chemical model of their protoplanetary discs, taking into account the relevant chemical transitions between vapour and refractory minerals, in order to track the resulting compositions of formed planets. We find that the masses of our synthetic planets increase on average with increasing stellar metallicity [Fe/H] and that giant planets and super-Earths are most common around thin-disc (α-poor) stars since these stars have an overall higher budget of solid particles. Giant planets are found to be very rare (≲1%) around thick-disc (α-rich) stars and nearly non-existent around halo stars. This indicates that the planet population is more diverse for more metal-rich stars in the thin disc. Water-rich planets are less common around low-metallicity stars since their low metallicity prohibits efficient growth beyond the water ice line. If we allow water to oxidise iron in the protoplanetary disc, this results in decreasing core mass fractions with increasing [Fe/H]. Excluding iron oxidation from our condensation model instead results in higher core mass fractions, in better agreement with the core-mass fraction of Earth, that increase with increasing [Fe/H]. Our work demonstrates how the Galactic chemical evolution and stellar parameters, such as stellar mass and chemical composition, can shape the resulting planet population.