arXiv subjects

Andrew R. Casey

Publications and source records attributed to Andrew R. Casey.

At least 55 records · Page 3Linked to original sources

arXiv2024

Nova contributions to the chemical evolution of the Milky Way

Context. The explosive burning that drives nova eruptions results in unique nucleosynthesis that heavily over-produces certain isotopes relative to the solar abundance. However, novae are often ignored when considering the chemical evolution of our Galaxy due to their low ejecta masses. Aims. In this work, we use previously computed synthetic nova populations and the galactic chemical evolution code OMEGA+ to assess the impact that novae have on the evolution of stable elemental and isotopic abundances. Methods. We combine populations of novae computed using the binary population synthesis code binary_c with the galactic chemical evolution code OMEGA+ and detailed, white dwarf mass-dependent nova yields to model the nucleosynthetic contributions of novae to the evolution of the Milky Way. We consider three different nova yield profiles, each corresponding to a different set of nova yield calculations. Results. Despite novae from low-mass white dwarfs (WDs) dominating nova ejecta contributions, we find that novae occurring on massive WDs are still able to contribute significantly to many isotopes, particularly those with high mass numbers. We find that novae can produce up to 35% of the Galactic 13C and 15N mass by the time the model Galaxy reaches [Fe/H] = 0, and earlier in the evolution of the Galaxy (between [Fe/H] = -2 and -1) novae may have been the dominant source of 15N. Predictions for [13C/Fe], [15N/Fe], 12C/13C, and 14N/15N abundances ratios vary by up to 0.2 dex at [Fe/H] = 0 and by up to 0.7 dex in [15N/Fe] and 14N/15N between [Fe/H] = -2 and -1 (corresponding approximately to Galactic ages of 170 Myr and 1 Gyr in our model). The Galactic evolution of other stable isotopes (excluding Li) is not noticeably affected by including novae.

astro-ph.GA↗

arXiv2024

The GALAH survey: Tracing the Milky Way's formation and evolution through RR Lyrae stars

Stellar mergers and accretion events have been crucial in shaping the evolution of the Milky Way (MW). These events have been dynamically identified and chemically characterised using red giants and main-sequence stars. RR Lyrae (RRL) variables can play a crucial role in tracing the early formation of the MW since they are ubiquitous, old (t$\ge$10 Gyr) low-mass stars and accurate distance indicators. We exploited Data Release 3 of the GALAH survey to identify 78 field RRLs suitable for chemical analysis. Using synthetic spectra calculations, we determined atmospheric parameters and abundances of Fe, Mg, Ca, Y, and Ba. Most of our stars exhibit halo-like chemical compositions, with an iron peak around [Fe/H]$\approx -$1.40, and enhanced Ca and Mg content. Notably, we discovered a metal-rich tail, with [Fe/H] values ranging from $-$1 to approximately solar metallicity. This sub-group includes almost ~1/4 of the sample, it is characterised by thin disc kinematics and displays sub-solar $α$-element abundances, marginally consistent with the majority of the MW stars. Surprisingly, they differ distinctly from typical MW disc stars in terms of the s-process elements Y and Ba. We took advantage of similar data available in the literature and built a total sample of 535 field RRLs for which we estimated kinematical and dynamical properties. We found that metal-rich RRLs (1/3 of the sample) likely represent an old component of the MW thin disc. We also detected RRLs with retrograde orbits and provided preliminary associations with the Gaia-Sausage-Enceladus, Helmi, Sequoia, Sagittarius, and Thamnos stellar streams.

astro-ph.GA↗

arXiv2024

Gaia DR3 detectability of unresolved binary systems

Gaia can not individually resolve very close binary systems, however, the collected data can still be used to identify them. A powerful indicator of stellar multiplicity is the sources reported Renormalized Unit Weight Error (ruwe), which effectively captures the astrometric deviations from single-source solutions. We aim to characterise the imprints left on ruwe caused by binarity. By flagging potential binary systems based on ruwe, we aim to characterise which of their properties will contribute the most to their detectability. We develop a model to estimate ruwe values for observations of Gaia sources, based on the biases to the single-source astrometric track arising from the presence of an unseen companion. Then, using the recipes from previous GaiaUnlimited selection functions, we estimate the selection probability of sources with high ruwe, and discuss what binary properties contribute to increasing the sources ruwe. We compute the maximum ruwe value which is compatible with single-source solutions as a function of their location on-sky. We see that binary systems selected as sources with a ruwe higher than this sky-varying threshold have a strong detectability window in their orbital period distribution, which peaks at periods equal to the Gaia observation time baseline. We demonstrate how our sky-varying ruwe threshold provides a more complete sample of binary systems when compared to single sky-averaged values by studying the unresolved binary population in the Gaia Catalogue of Nearby Stars. We provide the code and tools used in this study, as well as the sky-varying ruwe threshold through the GaiaUnlimited Python package

astro-ph.GA↗

arXiv2024

Frizzle: Combining spectra or images by forward modeling

When there are many observations of an astronomical source - many images with different dithers, or many spectra taken at different barycentric velocities - it is standard practice to shift and stack the data, to (for example) make a high signal-to-noise average image or mean spectrum. Bound-saturating measurements are made by manipulating a likelihood function, where the data are treated as fixed, and model parameters are modified to fit the data. Traditional shifting and stacking of data can be converted into a model-fitting procedure, such that the data are not modified, and yet the output is the shift-adjusted mean. The key component of this conversion is a spectral model that is completely flexible but also a continuous function of wavelength (or position in the case of imaging) that can represent any signal being measured by the device after any reasonable translation (or rotation or field distortion). The benefits of a modeling approach are myriad: The sacred data never are modified. Noise maps, data gaps, and bad-data masks don't require interpolation. The output can take the form of an image or spectrum evaluated on a pixel grid, as is traditional. In addition to shifts, the model can account for line-spread or point-spread function variations, world-coordinate-system variations, and calibration or normalization variations. The noise in the output becomes uncorrelated across neighboring pixels as the shifts deliver good coverage in some sense. The only cost is a small increase in computational complexity over that of traditional methods. We demonstrate the method with a small data example and we provide open source sample code for re-use.

astro-ph.IM↗

arXiv2024

Cool and Data-Driven: An Exploration of Optical Cool Dwarf Chemistry with Both Data-Driven and Physical Models

Detailed chemical studies of F/G/K -- or Solar-type -- stars have long been routine in stellar astrophysics, enabling studies in both Galactic chemodynamics, and exoplanet demographics. However, similar understanding of the chemistry of M and late-K dwarfs -- the most common stars in the Galaxy -- has been greatly hampered both observationally and theoretically by the complex molecular chemistry of their atmospheres. Here we present a new implementation of the data-driven \textit{Cannon} model, modelling $T_{\rm eff}$, $\log g$, [Fe/H], and [Ti/Fe] trained on low-medium resolution optical spectra ($4\,000-7\,000\,$\SI{}{\angstrom}) from 103 cool dwarf benchmarks. Alongside this, we also investigate the sensitivity of optical wavelengths to various atomic and molecular species using both data-driven and theoretical means via a custom grid of MARCS synthetic spectra, and make recommendations for where MARCS struggles to reproduce cool dwarf fluxes. Under leave-one-out cross-validation, our \textit{Cannon} model is capable of recovering $T_{\rm eff}$, $\log g$, [Fe/H], and [Ti/Fe] with precisions of 1.4\%, $\pm0.04\,$dex, $\pm0.10\,$dex, and $\pm0.06\,$dex respectively, with the recovery of [Ti/Fe] pointing to the as-yet mostly untapped potential of exploiting the abundant -- but complex -- chemical information within optical spectra of cool stars.

astro-ph.SR↗

arXiv2024

Uniting Gaia and APOGEE to unveil the cosmic chemistry of the Milky Way disc

The spatial distribution of Galactic stars with different chemical abundances encodes information on the processes that drove the formation and evolution of the Milky Way. Survey selection functions are indispensable for analysing astronomical catalogues produced by large-scale surveys. The use of these selection functions in data modelling is more complex when data from different surveys are to be modelled simultaneously. We introduce a procedure for constructing the selection function of a sample of red clump stars that have parallaxes and elemental abundances from the Gaia mission. We separately constructed the selection function of the APOGEE DR17 red clump stars, which depends on very different observables and has a very different spatial coverage. We combined the two surveys and accounted for their joint selection function to provide strong constraints on the radial and vertical density distribution of mono-abundance populations, with Gaia offering a dense coverage of the solar neighbourhood, while APOGEE reaches larger distances near the Galactic plane. We confirm that the radial density profile steepens with increasing metallicity. The combined sample also indicates a metallicity-dependent flaring of the alpha-poor disc. We provide the code for constructing the Gaia selection function we used in this study through the GaiaUnlimited Python package.

astro-ph.GA↗

arXiv2024

Spectacular nucleosynthesis from early massive stars

Stars formed with initial mass over 50 Msun are very rare today, but they are thought to be more common in the early universe. The fates of those early, metal-poor, massive stars are highly uncertain. Most are expected to directly collapse to black holes, while some may explode as a result of rotationally powered engines or the pair-creation instability. We present the chemical abundances of J0931+0038, a nearby low-mass star identified in early followup of SDSS-V Milky Way Mapper, which preserves the signature of unusual nucleosynthesis from a massive star in the early universe. J0931+0038 has relatively high metallicity ([Fe/H] = -1.76 +/- 0.13) but an extreme odd-even abundance pattern, with some of the lowest known abundance ratios of [N/Fe], [Na/Fe], [K/Fe], [Sc/Fe], and [Ba/Fe]. The implication is that a majority of its metals originated in a single extremely metal-poor nucleosynthetic source. An extensive search through nucleosynthesis predictions finds a clear preference for progenitors with initial mass > 50 Msun, making J0931+0038 one of the first observational constraints on nucleosynthesis in this mass range. However the full abundance pattern is not matched by any models in the literature. J0931+0038 thus presents a challenge for the next generation of nucleosynthesis models and motivates study of high-mass progenitor stars impacted by convection, rotation, jets, and/or binary companions. Though rare, more examples of unusual early nucleosynthesis in metal-poor stars should be found in upcoming large spectroscopic surveys.

astro-ph.SR↗

arXiv2023

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or "Mappers": Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

astro-ph.GA↗

arXiv2023

Stellar spots cause measurable variations in atmospheric metallicity

To accurately measure a star's atmospheric parameters and chemical abundances, it is crucial to have high-quality spectra. Analysing the detailed chemical abundances of groups of stars can help us better understand nucleosynthesis, galactic chemical enrichment, and stellar evolution. In this study, we explored whether stellar spots can affect a star's inferred metallicity and, if so, where the impact is the strongest. To investigate this, we created synthetic infrared spectra that included stellar spots for a sample of main-sequence stars younger than the sun. We then applied two models to the data: one that accounted for spots and one that did not. From this, we can determine the bias introduced when fitting spotted spectra with a non-spotted model and how this bias varies with different parameters. Our findings revealed that fitting spotted spectra with a non-spotted model can introduce a scatter of up to 0.05 dex in the inferred metallicity, especially for stars with high levels of spot coverage. This bias is similar in magnitude to other relevant effects, such as atomic diffusion, radiative levitation, or non-local thermodynamic equilibrium. We also found that the effect is most pronounced in young stars and decreases with age. These results suggest that stellar spots can introduce a systematic uncertainty in metallicity that is not currently accounted for in spectroscopic analysis. This could potentially limit scientific inferences for population-level studies of young stars and differential abundance analyses.

astro-ph.SR↗

arXiv2023

Iron-rich Metal-poor Stars and the Astrophysics of Thermonuclear Events Observationally Classified as Type Ia Supernovae. I. Establishing the Connection

The progenitor systems and explosion mechanisms responsible for the thermonuclear events observationally classified as Type Ia supernovae are uncertain and difficult to uniquely constrain using traditional observations of Type Ia supernova host galaxies, progenitors, light curves, and remnants. For the subset of thermonuclear events that are prolific producers of iron, we use published theoretical nucleosynthetic yields to identify a set of elemental abundance ratios infrequently observed in metal-poor stars but shared across a range of progenitor systems and explosion mechanisms: [Na,Mg,Co/Fe]<0. We label stars with this abundance signature ``iron-rich metal-poor'' or IRMP stars. We suggest that IRMP stars formed in environments dominated by thermonuclear nucleosynthesis and consequently that their elemental abundances can be used to constrain both the progenitor systems and explosion mechanisms responsible for thermonuclear explosions. We identify three IRMP in the literature and homogeneously infer their elemental abundances. We find that the elemental abundances of BD+80 245, HE 0533--5340, and SMSS J034249.53--284216.0 are best explained by the (double) detonations of sub-Chandrasekhar mass CO white dwarfs. If our interpretation of IRMP stars is accurate, then they should be very rare in globular clusters and more common in the Magellanic Clouds and dwarf spheroidal galaxies than in the Milky Way's halo. We propose that future studies of IRMP stars will quantify the relative occurrences of different thermonuclear event progenitor systems and explosion mechanisms.

astro-ph.SR↗

arXiv2022

Korg: a modern 1D LTE spectral synthesis package

We present Korg, a new package for 1D LTE (local thermodynamic equilibrium) spectral synthesis of FGK stars, which computes theoretical spectra from the near-ultraviolet to the near-infrared, and implements both plane-parallel and spherical radiative transfer. We outline the inputs and internals of Korg, and compare synthetic spectra from Korg, MOOG, Turbospectrum, and SME. The disagreements between Korg and the other codes are no larger than those between the other codes, although disagreement between codes is substantial. We examine the case of a C$_2$ band in detail, finding that uncertainties on physical inputs to spectral synthesis account for a significant fraction of the disagreement. Korg is 1-100 times faster than other codes in typical use, compatible with automatic differentiation libraries, and easily extensible, making it ideal for statistical inference and parameter estimation applied to large data sets. Documentation and installation instructions are available at https://ajwheeler.github.io/Korg.jl/stable/.

astro-ph.SR↗

arXiv2022

An empirical model of the Gaia DR3 selection function

Interpreting and modelling astronomical catalogues requires an understanding of the catalogues' completeness or selection function: objects of what properties had a chance to end up in the catalogue. Here we set out to empirically quantify the completeness of the overall Gaia DR3 catalogue. This task is not straightforward because Gaia is the all-sky optical survey with the highest angular resolution to date and no consistent ``ground truth'' exists to allow direct comparisons. However, well-characterised deeper imaging enables an empirical assessment of Gaia's $G$-band completeness across parts of the sky. On this basis, we devised a simple analytical completeness model of Gaia as a function of the observed $G$ magnitude and position over the sky, which accounts for both the effects of crowding and the complex Gaia scanning law. Our model only depends on a single quantity: the median magnitude $M_{10}$ in a patch of the sky of catalogued sources with $\texttt{astrometric_matched_transits}$ $\leq 10$. $M_{10}$ reflects elementary completeness decisions in the Gaia pipeline and is computable from the Gaia DR3 catalogue itself and therefore applicable across the whole sky. We calibrate our model using the Dark Energy Camera Plane Survey (DECaPS) and test its predictions against Hubble Space Telescope observations of globular clusters. We find that our model predicts Gaia's completeness values to a few per cent across the sky. We make the model available as a part of the $\texttt{gaiasf}$ Python package built and maintained by the GaiaUnlimited project: $\texttt{https://github.com/gaia-unlimited/gaiaunlimited}$

astro-ph.GA↗

arXiv2022

The GALAH Survey: A New Sample of Extremely Metal-Poor Stars Using A Machine Learning Classification Algorithm

Extremely Metal-Poor (EMP) stars provide a valuable probe of early chemical enrichment in the Milky Way. Here we leverage a large sample of $\sim600,000$ high-resolution stellar spectra from the GALAH survey plus a machine learning algorithm to find 54 candidates with estimated [Fe/H]~$\leq$~-3.0, 6 of which have [Fe/H]~$\leq$~-3.5. Our sample includes $\sim 20 \%$ main sequence EMP candidates, unusually high for \emp surveys. We find the magnitude-limited metallicity distribution function of our sample is consistent with previous work that used more complex selection criteria. The method we present has significant potential for application to the next generation of massive stellar spectroscopic surveys, which will expand the available spectroscopic data well into the millions of stars.

astro-ph.GA↗

arXiv2022

Viability of novae as sources of Galactic lithium

Of all the light elements, the evolution of lithium (Li) in the Milky Way is perhaps the most difficult to explain. Li is difficult to synthesize and is easily destroyed, making most stellar sites unsuitable for producing Li in sufficient quantities to account for the proto-solar abundance. For decades, novae have been proposed as a potential explanation to this 'Galactic Li problem', and the recent detection of 7Be in the ejecta of multiple nova eruptions has breathed new life into this theory. In this work, we assess the viability of novae as dominant producers of Li in the Milky Way. We present the most comprehensive treatment of novae in a galactic chemical evolution code to date, testing theoretical- and observationally-derived nova Li yields by integrating metallicity-dependent nova ejecta profiles computed using the binary population synthesis code binary c with the galactic chemical evolution code OMEGA+. We find that our galactic chemical evolution models which use observationally-derived Li yields account for the proto-solar Li abundance very well, while models relying on theoretical nova yields cannot reproduce the proto-solar observation. A brief exploration of physical uncertainties including single-stellar yields, the metallicity resolution of our nova treatment, common-envelope physics, and nova accretion efficiencies indicates that this result is robust to physical assumptions. Scatter within the observationally-derived Li yields in novae is identified as the primary source of uncertainty, motivating further observations of 7Be in nova ejecta.

astro-ph.SR↗

arXiv2022

The GALAH Survey: Chemical tagging and chrono-chemodynamics of accreted halo stars with GALAH+ DR3 and $Gaia$ eDR3

Since the advent of $Gaia$ astrometry, it is possible to identify massive accreted systems within the Galaxy through their unique dynamical signatures. One such system, $Gaia$-Sausage-Enceladus (GSE), appears to be an early "building block" given its virial mass $> 10^{10}\,\mathrm{M_\odot}$ at infall ($z\sim1-3$). In order to separate the progenitor population from the background stars, we investigate its chemical properties with up to 30 element abundances from the GALAH+ Survey Data Release 3 (DR3). To inform our choice of elements for purely chemically selecting accreted stars, we analyse 4164 stars with low-$α$ abundances and halo kinematics. These are most different to the Milky Way stars for abundances of Mg, Si, Na, Al, Mn, Fe, Ni, and Cu. Based on the significance of abundance differences and detection rates, we apply Gaussian mixture models to various element abundance combinations. We find the most populated and least contaminated component, which we confirm to represent GSE, contains 1049 stars selected via [Na/Fe] vs. [Mg/Mn] in GALAH+ DR3. We provide tables of our selections and report the chrono-chemodynamical properties (age, chemistry, and dynamics). Through a previously reported clean dynamical selection of GSE stars, including $30 < \sqrt{J_R~/~\mathrm{kpc\,km\,s^{-1}}} < 55$, we can characterise an unprecedented 24 abundances of this structure with GALAH+ DR3. Our chemical selection allows us to prevent circular reasoning and characterise the dynamical properties of the GSE, for example mean $\sqrt{J_R~/~\mathrm{kpc\,km\,s^{-1}}} = 26_{-14}^{+9}$. We find only $(29\pm1)\%$ of the GSE stars within the clean dynamical selection region. Our methodology will improve future studies of accreted structures and their importance for the formation of the Milky Way.

astro-ph.GA↗

arXiv2021

Dynamically Tagged Groups of Metal-Poor Stars from the Best \& Brightest Survey

Orbital characteristics based on Gaia Early Data Release 3 astrometric parameters are analyzed for ${\sim} 4000$ metal-poor stars ([Fe/H] $\leq -0.8$) compiled from the Best $\&$ Brightest survey. Selected as metal-poor candidates based on broadband near- and far-IR photometry, $43\%$ of these stars had medium-resolution ($1200 \lesssim R \lesssim 2000$) validation spectra obtained over a seven-year campaign from $2014$ to $2020$ with a variety of telescopes. The remaining stars were chosen based on photometric metallicity determinations from the Huang et al. recalibration of the Sky Mapper Southern Survey. Dynamical clusters of these stars are obtained from the orbital energy and cylindrical actions using the \HDBSCAN ~unsupervised learning algorithm. We identify $52$ Dynamically Tagged Groups (DTGs) with between $5$ and $21$ members; $18$ DTGs have at least $10$ member stars. Milky Way (MW) substructures such as Gaia-Sausage-Enceladus, the Metal-Weak Thick-Disk, Thamnos, the Splashed Disk, and the Helmi Stream are identified. Associations with MW globular clusters are determined for $8$ DTGs; no recognized MW dwarf galaxies were associated with any of our DTGs. Previously identified dynamical groups are also associated with our DTGs, with emphasis placed on their structural determination and possible new identifications. Chemically peculiar stars are identified as members of several DTGs, with $6$ DTGs that are associated with \textit{r}-process-enhanced stars. We demonstrate that the mean carbon and $α$-element abundances of our DTGs are correlated with their mean metallicity in an understandable manner. Similarly, we find that the mean metallicity, carbon, and $α$-element abundances are separable into different regions of the mean rotational-velocity space.

astro-ph.GA↗

arXiv2021

The GALAH Survey: Improving our understanding of confirmed and candidate planetary systems with large stellar surveys

Pioneering photometric, astrometric, and spectroscopic surveys are helping exoplanetary scientists better constrain the fundamental properties of stars within our galaxy, and the planets these stars host. In this study, we use the third data release from the stellar spectroscopic GALAH Survey, coupled with astrometric data of eDR3 from the \textit{Gaia} satellite, and other data from NASA's Exoplanet Archive, to refine our understanding of 279 confirmed and candidate exoplanet host stars and their exoplanets. This homogenously analysed data set comprises 105 confirmed exoplanets, along with 146 K2 candidates, 95 TESS Objects of Interest (TOIs) and 52 Community TOIs (CTOIs). Our analysis significantly shifts several previously (unknown) planet parameters while decreasing the uncertainties for others; Our radius estimates suggest that 35 planet candidates are more likely brown dwarfs or stellar companions due to their new radius values. We are able to refine the radii and masses of WASP-47 e, K2-106 b, and CoRoT-7 b to their most precise values yet, to less than 2.3\% and 8.5\% respectively. We also use stellar rotational values from GALAH to show that most planet candidates will have mass measurements that will be tough to obtain with current ground-based spectrographs. With GALAH's chemical abundances, we show through chemo-kinematics that there are five planet-hosts that are associated with the galaxy's thick disc, including NGTS-4, K2-183 and K2-337. Finally, we show there is no statistical difference between the chemical properties of hot Neptune and hot rocky exoplanet hosts, with the possibility that short-period rocky worlds might be the remnant cores of hotter, gaseous worlds.

astro-ph.EP↗

arXiv2021

The impact of metallicity on nova populations

The metallicity of a star affects its evolution in a variety of ways, changing stellar radii, luminosities, lifetimes, and remnant properties. In this work, we use the population synthesis code binary_c to study how metallicity affects novae in the context of binary stellar evolution. We compute a 16-point grid of metallicities ranging from $Z=10^{-4}$ to 0.03, presenting distributions of nova white dwarf masses, accretion rates, delay-times, and initial system properties at the two extremes of our 16-point metallicity grid. We find a clear anti-correlation between metallicity and the number of novae produced, with the number of novae at $Z=0.03$ roughly half that at $Z=10^{-4}$. The white dwarf mass distribution has a strong systematic variation with metallicity, while the shape of the accretion rate distribution is relatively insensitive. We compute a current nova rate of approximately 33 novae per year for the Milky Way, a result consistent with observational estimates relying on extra-Galactic novae but an under-prediction relative to observational estimates relying on Galactic novae. However, the shape of our predicted Galactic white dwarf mass distribution differs significantly to existing observationally derived distributions, likely due to our underlying physical assumptions. In M31, we compute a current nova rate of approximately 36 novae per year, under-predicting the most recent observational estimate of $65^{+15}_{-16}$. Finally, we conclude that when making predictions about currently observable nova rates in spiral galaxies, or stellar environments where star formation has ceased in the distant past, metallicity can likely be considered of secondary importance compared to uncertainties in binary stellar evolution.

astro-ph.SR↗