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Jamie Tayar

Publications and source records attributed to Jamie Tayar.

At least 19 recordsLinked to original sources

The Open Cluster Chemical Abundances and Mapping Survey: IX. Measuring the Effects of Stellar Diffusion in the Open Clusters NGC 752 and Ruprecht 147 using APOGEE

A growing understanding of stellar processes that alter surface chemical abundances over time has opened new avenues for using these changes as probes of stellar properties. On the main sequence and near the turnoff, stellar surface abundances are affected by gravitational settling and radiative acceleration, collectively known as atomic diffusion. In this work, we use SDSS/APOGEE DR17/DR19 data to investigate atomic diffusion in the open clusters NGC~752 and Ruprecht~147, thereby constraining how these signatures vary with age. From the analysis of Fe, C, N, Na, Mg, Al, Si, S, K, Ca, Ti, V, Cr, Mn, Co, and Ni, we find significant abundance differences between stars near the turnoff and the cooler main-sequence, where warmer stars are depleted relative to the cooler main-sequence stars at the $\geq1\sigma$ level for all elements available in the analysis. These abundance differences are consistent with the signatures expected from atomic diffusion and are further supported by comparisons with stellar models that include diffusion. By fitting the observed $T_{\rm eff}$--[Fe/H] patterns with MIST isochrones, we obtain best-fit ages of 1.0~Gyr for NGC~752 and 2.5--3.2~Gyr for Ruprecht~147. Carbon is a key diagnostic, as it shows both atomic diffusion and extra-mixing signatures associated with first-dredge-up. For NGC~752, the coolest stars in our sample, which provide the best proxy for the initial cluster composition, yield [Fe/H]$_{\rm CS} = 0.01~\pm~0.02(\pm~0.05)$ dex. For Ruprecht~147, we obtain [Fe/H]$_{\rm CS} = 0.17~\pm~0.00(\pm~0.05)$ dex. Our findings further constrain atomic diffusion models, suggesting that atomic diffusion affects age estimates of stars near the main-sequence turnoff.

astro-ph.SR

Evaluating the Sensitivity of the Age Inferences of Red Giant Stars to Machine Learning Methodology

Stellar ages are vital for understanding the formation of our galaxy, but they are among the most challenging parameters to measure. Many authors address this by using machine learning models trained on stars of known age. Here we used data for 351,995 stars from Milky Way Mapper Data Release 19 to explore the sensitivity of the inferred ages to 1) neural network hyperparameters, 2) machine learning architecture, and 3) training set. We find that the resulting ages are generally insensitive to the neural network hyperparameters or the machine learning architecture, but are somewhat sensitive to the training set chosen. We also find that ages for the oldest, coolest, and lowest metallicity stars in the sample are most sensitive to the methodology used and the training set chosen. In general, our analysis suggests that even simple neural network models are sufficient for accurate age inference, but future work expanding the available training sets will be an important component of predicting reliable ages for the full galactic population.

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TESS Asteroseismology of Red Giants in the Old Metal-Rich Open Clusters NGC 188 & NGC 6791

Open clusters are fundamental laboratories for investigating stellar and Galactic evolution, and serve as important benchmarks for asteroseismic analyses. Using a boutique method to analyze TESS photometry, we study red giants in two old metal-rich open clusters: NGC 188 & NGC 6791. By comparing Kepler and TESS observations for NGC 6791, similar oscillation mode frequencies are recovered, however we find a systematic offset of 2.2% with a scatter of 9% in the $\nu_{\text{max}}$ measurements. We attribute this discrepancy to the lower signal-to-noise of the TESS data for these relatively faint stars. For the brighter cluster NGC 188, we present new seismic measurements in 17 red giants. We estimate average seismic masses for the RGB of $M_{\text{RGB,NGC188}} = 1.13\pm0.04$(rand)$^{+0.12}_{-0.19}$(sys) $M_{\odot}$ and RC of $M_{\text{RC,NGC188}} = 1.11\pm0.01$(rand)$^{+0.11}_{-0.19}$(sys) $M_{\odot}$, consistent with independent mass estimates for this cluster and with similar precision to previous Kepler studies. From the difference between the average evolutionary phase masses, we estimate an integrated RGB mass loss of $\Delta M = 0.02 \pm 0.04$(rand)$\pm0.01$(sys) $M_{\odot}$, supporting the evidence for lower mass loss at higher metallicities. Using asteroseismology and chemical abundances, we identify three binary interaction candidates: two under-massive stars and one over-massive star potentially exhibiting dipole-mode suppression. Finally, we derive an average seismic cluster age of $7.0\pm0.9$ Gyrs, in good agreement with previous literature ages. Our analysis demonstrates the strong potential of TESS asteroseismology for open clusters, and motivates extending this investigation to other TESS clusters that span a wider range of ages and metallicities.

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The YREC Stellar Evolution Code: Public Data Release

In this paper we present the public release of the Yale Rotating Evolution Code (YREC). YREC is a stellar evolution code that covers brown dwarfs and stars across a wide range of masses, and evolutionary states from the pre-MS through helium burning. We summarize the key ingredients of the code, document the code performance, and discuss its strengths and limitations. We present libraries of input files, documentation, sample use cases, and scripts. In addition to usage as a research tool, we highlight the utility of the code for educational purposes.

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Thermal Eclipse Observation of the Young Hot Neptune AU Mic b with Spitzer

We present the observation of a secondary eclipse of the young hot Neptune, AU Mic b, in the infrared using the Spitzer Space Telescope. Using a primary transit from Spitzer to constrain the system parameters, we tentatively detect an eclipse centered at $BJD=2458740.848893^{+0.00010}_{-0.000099}$ with an observed depth of $171\pm{29}$ ppm given an uninformed prior. This corresponds to a dayside brightness temperature of $T=1031\pm{58}$ K, which exceeds the calculated equilibrium temperature of $606\pm{19}$ K. We explore some possible explanations for these results, including inefficient heat redistribution, gravitational contraction, stellar pulsations, instrument systematics and choice of eclipse depth prior, but find none of these to be likely explanations for the observed eclipse parameters. We also explore the impact of correlated noise in the systematic trends, and we find that splitting the systematics into low-pass (smoothing) and high-pass trends is required to reach an optimal minimization of the low-frequency systematics in the resulting detrended light curve. Future observations with JWST are needed to confirm our eclipse detection with Spitzer.

astro-ph.EP

Expanding Asteroseismic Studies in Star Clusters Using NASA's TESS and ESA's Gaia Missions

Star clusters have long been central to the study of stellar evolution due to their chemically and chronologically homogeneous populations. Asteroseismology, the analysis of stellar oscillations and pulsations, provides precise information about properties such as masses, radii, and ages of stars in the field. However, these stars lack calibration to an absolute scale, and so this project seeks to utilize the data from NASA's TESS mission and ESA's Gaia mission to identify additional cluster stars suitable for asteroseismic analysis and calibration. In this work we analyze 14 stars belonging to 3 well-populated clusters, 5 additional stars that are the only detected oscillators in their respective clusters, and 3 detected oscillators of unknown cluster membership. By significantly expanding the number of clusters with measured oscillating giants, this project increases the opportunity for cross-validation between classical stellar models and asteroseismic methods, allowing for improvements in both calibration techniques and age estimations across the galaxy.

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The Two-infall Model Revisited: Constraints on Milky Way Bulge Assembly from >30,000 Galactic Chemical Evolution Models and Machine Learning

We constrain the formation history of the Milky Way bulge using a two-infall galactic chemical evolution (GCE) algorithm implemented in the N'OMEGA+ code. We recover a best-fit scenario in which the bulge forms through an early, rapid starburst ($t_1 \sim 0.1$ Gyr, $\tau_1 \sim 0.09$ Gyr, and star formation efficiency (SFE) $\sim 3~\mathrm{Gyr}^{-1}$), followed by a delayed, lower-mass second infall ($t_2 \sim 5.1$ Gyr, $\tau_2 \sim 1.7$ Gyr, and $\sigma_2 \sim 0.69$). Our model adopts mass- and metallicity-dependent nucleosynthetic yields from modern stellar grids and explores a wide GCE parameter space in infall timing, SFE, mass partitioning, initial mass function upper mass, and type Ia supernova normalization, optimized via a hybrid genetic algorithm with Markov Chain Monte Carlo refinement. The later infall features a reduced SFE ($\Delta\mathrm{SFE} \sim 0.72$), reproducing the metal-rich peak of the bulge metallicity distribution function (MDF) and the decline in [$\alpha$/Fe] at high [Fe/H]. Our model naturally favors the M. Joyce et al. age--metallicity relation over the ages in T. Bensby et al. Degeneracy and principal component analyses show that the infall history, SFE, and mass partitioning are strongly covariant---the bulge's observed MDF, abundance trends, and age distribution constrain only their combinations, not each parameter independently. The results support a composite bulge origin---an early, rapid collapse builds the majority of the mass, while a younger component is required to match the late-stage enrichment.

astro-ph.GA

Evolved stars with inconsistent age estimates: Abundance outliers or mass transfer products?

In the Milky Way disk there is a strong trend linking stellar age to surface element abundances. Here we explore this relationship with a dataset of 8,803 red-giant and red-clump stars with both asteroseismic data from NASA Kepler Mission and surface abundances from the SDSS-V MWM. We find, with a k-nearest-neighbors approach, that the [Mg/H] and [Fe/Mg] abundance ratios predict asteroseismic ages to an accuracy of about 2 Gyr for the majority of stars. That said, there are substantial outlier stars whose surface abundances do not match their asteroseismic ages. Because asteroseismic ages for these stars are fundamentally based on density or mass, these outliers are mass-transfer candidates. Stars whose surface abundances predict a younger age (higher mass) than what's seen in the asteroseismology are mass accretor candidates (MAC); stars whose abundances predict an older age (lower mass) than the asteroseismology age are mass donor candidates (MDC). We create precise control samples, matched according to (1) surface abundances and (2) asteroseismic ages, for both the MAC and MDC stars; we use these to find slight differences in rotational velocity, [C/N], and [Na/Mg] between the mass-transfer candidates and their abundance neighbors. We find no drastic differences in kinematics, orbital invariants, UV excess, or other stellar abundances between outliers and their abundance neighbors. We deliver 377 mass-transfer candidates for follow-up observations. This project implicitly suggests a fundamental limit on the reliability of asteroseismic ages, and supports existing evidence that age-abundance outliers are products of binary mass transfer.

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Extending the [C/N]-Age Calibration: Using Globular Clusters to Explore Older and Metal-Poor Populations

In the coming years, detailed chemical abundances from large-scale high-resolution spectroscopic surveys will become available for vast numbers of stars across the Milky Way. Previous work has suggested that abundance ratios from these spectra can allow us to estimate ages from a large number of stars. These data will be leveraged to calibrate chemical clocks to age-date field stars, as reliable stellar ages remain elusive. In this work, we extended our empirical relationship between stellar age and their carbon-to-nitrogen ([C/N]) abundance ratio for evolved stars to older and more metal-poor stars by combining the original open cluster calibration sample and four globular clusters: 47 Tuc, M 71, M 4, and M 5. With this extension, [C/N] can be used as a chemical clock for evolved field stars to investigate not only regions within the metal rich disk, but also more metal-poor regions of our Galaxy. We have established the [C/N]-age relationship for APOGEE DR17 red giant stars, that have experienced the first dredge up but have not yet undergone any extra-mixing, in clusters usable for ages between $8.62 \leq \log(Age[{\rm yr}]) \leq 10.13$ and for metallicites of $-1.2\leq[Fe/H]\leq+0.3$. This relationship can be uniformly applied to these stars within the APOGEE DR17 sample. This measured [C/N]-age APOGEE DR17 relationship is also shown to be consistent with stellar ages derived from asterosiesmic results of APOKASC and APO-K2.

astro-ph.GA

A nearly pristine star from the Large Magellanic Cloud

The first stars formed out of pristine gas, causing them to be so massive that none are expected to have survived until today. If their direct descendants were sufficiently low-mass stars, such stars could exist today and would be recognizable by having the lowest metallicities (abundance of elements heavier than helium). We present the independent identification and detailed chemical analysis of the star SDSS J0715-7334, finding ultra-low elemental abundances of both iron and carbon ([Fe/H] = -4.3, [C/Fe] < -0.2) and total metallicity Z < 7.8 x 10^{-7} (log Z/Zsun < -4.3). The star's orbit indicates that it originates from the halo of the Large Magellanic Cloud. Its heavy element abundance pattern can be explained by a primordial supernova with an initial mass of 30 solar masses. This star is over ten times more chemically pristine than the most extreme high-redshift galaxies currently found by the James Webb Space Telescope. It is sufficiently metal-poor that current models of low-mass star formation require dust cooling to explain its existence.

astro-ph.SR

200,000+ Deep Learning-inferred Periods of Stellar Variability from the All-Sky Automated Survey for Supernovae

Stars exhibit a range of variability periods that depend on their mass, age, and evolutionary stage. For space-based photometric data, convolutional neural networks (CNNs) have demonstrated success in recovering and measuring periodic variability from photometric missions like Kepler and TESS. All-sky ground-based surveys can have similar if not longer baselines than space-based missions; however, these datasets are more challenging to work with due to irregular sampling, more complex systematics, and larger data gaps. In this work, we demonstrate that CNNs can be used to derive variability periods from ground-based surveys. From the All-Sky Automated Survey for Supernovae, we recover 208,260 variability periods between 1 and 30 days, approximately 60% of which are new detections. We recover periods for active RSCVn, anomalous sub-subgiants, and cool dwarfs that are consistent with previously measured rotation periods, while periods for stars above the Kraft break are generally spurious. We also identify periodic signals in tens of thousands of giant stars that correspond to frequencies of stellar oscillations rather than rotation. Our results highlight that CNNs can be used on sparsely sampled ground-based photometry to recover periodicity. We conclude that the findings of our work are very promising for the potential recovery of hundreds of thousands of stellar rotation periods in data from the Vera C. Rubin Observatory's Legacy Survey of Space and Time and the Nancy Grace Roman Space Telescopes Galactic Bulge Time Domain Survey.

astro-ph.SR

TESS Subgiant and Lower Red Giant Asteroseismology in the Continuous Viewing Zones

Asteroseismology, the study of stellar oscillations, and stellar modeling both offer profound insights into the fundamental properties and evolution of stars. With pySYD, a new open-source Python package, we were able to constrain the asteroseismic global parameters, $\nu_{max}$ and $\Delta\nu$, for 82 solar-like oscillating subgiant and lower red giant stars, filling in the region between the Kepler dwarfs and giants. Using asteroseismic scaling relations, we were able to compute seismic masses, radii, and surface gravities for our entire sample with average errors of 0.21 $M_{\bigodot}$, 0.27 $R_{\bigodot}$, and 0.06 dex respectively. Using 4 stellar modeling grids we determine and compare stellar ages for our sample. We find that our age distribution from stellar modeling is consistent with other local star samples. We find small consistent offsets from model predictions across our regime, but offsets were worse at higher gravities (log(g) $\geq$ 3.5 dex), suggesting the need for better calibration. Finally, we discuss our sample in the context of galactic archaeology and show how ages like these could be used to identify and study binary system evolution and galactic evolution in the future. All in all, we show that asteroseismology can be successfully performed with TESS data and can continue to make an impact on our understanding of stellar physics and galactic archaeology.

astro-ph.SR

Mapping the Distant and Metal-Poor Milky Way with SDSS-V

The fifth-generation Sloan Digital Sky Survey (SDSS-V) is conducting the first all-sky low-resolution spectroscopic survey of the Milky Way's stellar halo. We describe the stellar parameter pipeline for the SDSS-V halo survey, which simultaneously models spectra, broadband photometry, and parallaxes to derive stellar parameters, metallicities, alpha abundances, and distances. The resulting BOSS-MINESweeper catalog is validated across a wide range of stellar parameters and metallicities using star clusters and a comparison to high-resolution spectroscopic surveys. We demonstrate several scientific capabilities of this dataset: identifying the most chemically peculiar stars in our Galaxy, discovering and mapping distant halo substructures, and measuring the all--sky dynamics of the Milky Way on the largest scales. The BOSS-MINESweeper catalog for SDSS DR19 is publicly available and will be updated for future data releases.

astro-ph.GA

Anchoring Stellar Age Indicators: A Cross-Calibration of [C/N] and Gyrochronology Ages via the Age-Velocity-Dispersion Relation

Determining stellar ages is challenging, as it depends on other stellar parameters in a non-linear way and often relies on stellar evolution models to infer the underlying relation between these parameters and age. This complexity increases when comparing different age-dating methods, as they rely on distinct indicators and are often applicable to non-overlapping regions of the color-magnitude diagram. Moreover, many empirical calibration methods rely on pre-determined ages, often from open clusters or asteroseismology, which only cover a limited parameter space. Fortunately, the age-velocity-dispersion relation (AVR), in which the velocity dispersion increases with age, is a universal feature among stars of all evolutionary stages. In this paper, we 1) explore the parameter space in which [C/N] and gyrochronology are applicable, extending beyond the domains probed by asteroseismology and open clusters, and 2) assess whether the traditionally assumed [C/N] and gyrochronology relations yield ages on a consistent physical scale, after calibrating both using the same AVR. We find gyrochronology can be applied to all partially convective stars after they have converged onto the slow rotating sequence and before they experience weakened magnetic braking; [C/N] can be used to infer ages for all giants with metallicity > -0.8 dex and [C/N] < -0.05 dex, and can be used as an age-indicator down to [Fe/H] of -1 dex if only selecting the low-$\alpha$ disk. Lastly, ages obtained from [C/N] and gyrochronology agree within uncertainty after accounting for systematic offsets.

astro-ph.SR

SDSS-V Milky Way Mapper (MWM): ASPCAP Stellar Parameters and Abundances in SDSS-V Data Release 19

The goal of this paper is to describe the science verification of Milky Way Mapper (MWM) APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) data products published in Data Release 19 (DR19) of the fifth phase of the Sloan Digital Sky Survey (SDSS-V). We compare MWM ASPCAP atmospheric parameters T$_{\rm eff}$, log g, 24 abundances of 21 elements (carbon, nitrogen, and oxygen have multiple sources for deriving their abundance values) and their uncertainties determined from Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectrograph spectra with those of the literature and evaluate their accuracy and precision. We also test the zero-point calibration of the v$_{\rm rad}$ derived by the APOGEE Data Reduction Pipeline. This data release contains ASPCAP parameters for 964,989 stars, including all APOGEE-2 targets expanded with new observations of 336,511 stars from the Apache Point Observatory observed until 4 July 2023. Overall, the new T$_{\rm eff}$ values show excellent agreement with the IRFM scale, while the surface gravities exhibit slight systematic offsets compared to asteroseisimic gravities. The estimated precision of T$_{\rm eff}$ is between 50 and 70 K for giants and 70$-$100 K for dwarfs, while surface gravities are measured with a precision of 0.07$-$0.09 dex for giants. We achieve an estimated precision of 0.02$-$0.04 dex for multiple elements, including metallicity, $\alpha$, Mg, and Si, while the precision of at least 10 elements is better than 0.1 dex.

astro-ph.SR

New Rotation Periods from the Kepler Bonus Background Light Curves

The Kepler field hosts the best studied sample of field star rotation periods. However, due to Kepler's large 4" pixels, many of its light curves are at high risk of contamination from background sources. The new Kepler Bonus Background light curves are de-blended using a PSF algorithm, providing light curves of over 400,000 new background sources in addition to over 200,000 re-analyzed Kepler prime targets. These light curves provide the opportunity to search for new rotation periods. Here we apply a convolutional neural network trained on synthetic spot-modulated light curves to regress rotation periods from the Kepler Bonus light curves. We obtained periods for 32,159 total sources, 19,650 of which had previously been measured and 9,811 of which are new periods for both Kepler prime and background sources. Our method also detected 608 pulsation frequencies from asteroseismic oscillations in red giants. We validate our Kepler prime periods against literature values and present the full period sample. We find excellent agreement with previously-known literature periods, validating deep learning as a viable class of period determination methods. Comparing the periods and light curves of foreground-background pairs, we find that as many as 63% of periodic background light curves are still blended with the foreground, highlighting limitations of the de-blending technique.

astro-ph.SR

Enhanced magnetic activity in rapidly rotating binary stars

Stellar activity is fundamental to stellar evolution and the formation and habitability of exoplanets. The interaction between convective motions and rotation in cool stars results in a dynamo process that drives magnetic surface activity. In single stars, activity increases with rotation rate until it saturates for stars with rotation periods Prot < 3 - 10 d. However, the mechanism responsible for saturation remains unclear. Observations indicate that red giants in binary systems that are in spin-orbit resonance exhibit stronger chromospheric activity than single stars with similar rotation rates, suggesting that tidal flows can influence surface activity. Here, we investigate the chromospheric activity of main-sequence binary stars to understand the impact of tidal forces on saturation phenomena. For binaries with 0.5 < Prot/d < 1, mainly contact binaries that share a common thermal envelope, we find enhanced activity rather than saturation. This result supports theoretical predictions that a large-scale $\alpha$ - $\omega$ dynamo during common-envelope evolution can generate strong magnetic fields. We also observe supersaturation in chromospheric activity, a phenomenon tentatively noted previously in coronal activity, where activity levels fall below saturation and decrease with shorter rotation periods. Our findings emphasise the importance of studying stellar activity in stars with extreme properties compared to the Sun's.

astro-ph.SR

Asteroseismically Inferred Ages of 132,000 Red Giants with TESS

NASA's TESS mission has identified at least 158,000 oscillating red giants, increasing the known sample by roughly an order of magnitude. After validating that these measurements are reliable to 5% for up to 90% of red giants (Theodoridis & Tayar 2023), we make custom stellar evolution models using MESA in order to estimate ages for ~132,794 of these stars to an average uncertainty of 23%. We show that these ages follow similar distributions to those observed in other samples such as Kepler with small differences likely resulting in the galactic volume probed. We provide these ages to the community to enable future galactic archaeology analyses.

astro-ph.SR