arXiv subjects

Andrew R. Casey

Publications and source records attributed to Andrew R. Casey.

At least 37 records · Page 2Linked to original sources

arXiv2026

A constrained linear model for continuum normalization of stellar spectra

Inferring stellar parameters and chemical abundances by forward modeling stellar spectra usually requires a spectral synthesis code, or an emulator constructed from a curated training set. In these situations continuum normalization is often implemented as a pre-processing step that is independent of stellar parameters. This leads to results that are biased, or inconsistent across signal-to-noise ratios. A more justified approach is to forward model spectra with all nuisances simultaneously, but in practice this can be an expensive or non-convex optimization procedure. Here we describe a constrained linear model that can fit stellar absorption, telluric transmission, the joint continuum-instrument response. Stellar absorption and telluric transmission are each modeled by factorizing a grid of rectified theoretical spectra into two non-negative matrices with a chosen number of basis components. This model characterizes all possible spectra in many fewer parameters than comparable data-driven models. The non-negativity constraint ensures basis vectors are strictly additive, which limits rectified flux to less than or equal to unity, such that we can distinguish normalized spectra from the joint instrument-continuum response. The model requires no initial guess, and the linearity ensures that inference is convex, stable, and fast. This model allows us to reliably fit nuisances (e.g., tellurics, continuum), and is readily extensible to radial velocity and rotational broadening, without any prior knowledge about the fundamental stellar properties. We demonstrate our method by fitting ESO/HARPS high-resolution echelle spectra of BAFGKM-type stars. With repeat observations of $α$-Centauri A we present results that are best in class: consistent across time to 0.2% at S/N ~ 100, and to better than 0.5% at S/N ~ 30.

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arXiv2025

Stellar Parameters of BOSS M dwarfs in SDSS-V DR19

We utilized the Stellar LAbel Machine (SLAM), a data-driven model based on Support Vector Regression, to derive stellar parameters ([Fe/H], $T_{\rm eff}$, and $\log{g}$) for SDSS-V M dwarfs using low-resolution optical spectra (R$\sim$2000) obtained with the BOSS spectrographs. These parameters are calibrated using LAMOST F, G or K dwarf companions ([Fe/H]), and APOGEE Net ($T_{\rm eff}$ and $\log{g}$), respectively. Comparisons of SLAM predicted [Fe/H] values between two components of M+M dwarfs wide binaries show no bias but with a scatter of 0.11 dex. Further comparisons with two other works, which also calibrated the [Fe/H] of M dwarfs by using the F/G/K companions, reveal biases of -0.06$\pm$0.16 dex and 0.02$\pm$0.14 dex, respectively. The SLAM-derived effective temperatures agree well with the temperature which is calibrated by using interferometric angular diameters (bias: -27$\pm$92 K) and those of the LAMOST (bias: -34$\pm$65 K), but are systematically lower than those from an empirical relationship between the color index and $T_{\rm eff}$ by 146$\pm$45 K. The SLAM surface gravity aligns well with those of LAMOST (bias: -0.01$\pm$0.07 dex) and those derived from the stellar mass and radius (bias: -0.04$\pm$0.09 dex). Finally, we investigated a bias in [Fe/H] between SLAM and APOGEE ASPCAP. It depends on ASPCAP's [Fe/H] and $T_{\rm eff}$, we provide an equation to correct the ASPCAP metallicities.

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arXiv2025

Looking for Companionship: Radial Velocity Follow-Up of Lithium-Rich Giants with ESPRESSO

Lithium-rich red giants have been a long-standing mystery in stellar astrophysics. A leading theory to explain these chemically peculiar and rare objects is interactions with a close companion. To investigate their companion fraction, we collected high-resolution spectra of 33 Li-rich red giants using ESPRESSO, and used The Joker constrain their orbital parameters. We find an overall companion rate of $27\%$ (9/33). Secondary masses reveal one planetary companion ($ M\sin i \approx 7 \; \rm M_{Jup}$), three brown dwarfs ($ M\sin i=30-33 \; \rm M_{Jup}$), and five stellar-mass companions ($M\sin i= 0.2-0.8 \;\rm M_\odot$). Our findings suggest that Li-rich red giants with lower lithium abundance ($\rm A(Li) \approx 1.5 \; dex$) tend to be in binaries as compared to those with higher lithium abundance, and Li-rich red giants with $\log g = 2-3 \rm \; dex$ have a higher companion rate than those outside of this range. We offer two potential formation mechanisms of our Li-rich sample: (i) the progenitor mass of stellar mass companions suggest that these objects were potentially lithium-producing, intermediate-mass AGB stars; (ii) the sub-stellar companions were initially in multi-planet systems, but dynamical instability caused the tidal dissipation of close-in planets thereby enhancing the red giant in lithium. Extended baselines and dedicated follow-up with Gaia DR4 astrometry are required to confirm the orbital parameters of our systems and distinguish between mechanisms.

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arXiv2025

Unified Spectrospatial Forward Models: Spatially Continuous Maps of Weak Emission Lines in the Rosette Nebula with SDSS-V LVM

Analyses of IFU data are typically performed on a per-spaxel basis, with each spectrum modelled independently. For low signal-to-noise (S/N) features such as weak emission lines, estimating properties is difficult and imprecise. Arbitrary binning schemes boost S/N at the cost of resolution, and risk introducing biases. We present a general forward-modelling approach that assumes spectra close on the sky are more similar than distant ones, and so can be modelled jointly. These "spectrospatial" models exploit spatial correlation to provide robust inferences, while simultaneously providing continuous predictions of line properties like strength and kinematics across the sky. Instrumental and calibration systematics are straightforward to include and infer. The model provides a natural trade-off between spatial resolution and S/N in a data-driven way. We apply this to Sloan Digital Sky Survey V (SDSS-V) Local Volume Mapper (LVM) data of the Rosette Nebula, producing continuous maps of fluxes and kinematics for Balmer, nebular, and auroral lines, as well as weak C II and N II recombination lines, demonstrating the approach across three orders of magnitude in S/N, including in the very low-S/N regime. The method recovers identical morphologies across different lines tracing similar ionisation volumes, at varying resolutions set by the S/N. We additionally provide a general framework for building and fitting such models in JAX, suitable for many applications. The implementation is fast and memory efficient, scales to large data volumes as in LVM, and can be deployed on hardware accelerators.

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arXiv2025

The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V

SDSS-V will obtain 100,000s of medium-resolution, optical spectra of M dwarfs with the BOSS instrument. M dwarfs have complex atmospheres, and their spectra contain many wide and dense, overlapping molecular features, so determining accurate stellar parameters by fitting models has been difficult. To circumvent this, other surveys have employed machine learning methods to transfer measurements of stellar parameters from high-resolution spectra to their medium-resolution counterparts. These methods provide large catalogs of stellar parameters but, if not addressed properly, are plagued by biases which are, in part, due to the normalization of the spectra. Typical spectral normalization removes the continuum but preserves the relative depths of the absorption features, but optical M dwarf spectra are almost entirely made up of molecular absorption, which makes this difficult. Here, we develop a standardization method that instead defines a pseudo-continuum. We use the spectrum's alpha shape to find the points which lie between the absorption features and apply local polynomial regression to find this pseudo-continuum. To tune the hyperparameters of this method, we create BOSS-like spectra from BT-NextGen models to replicate instrumental, signal-to-noise, and reddening effects. We find that in both this generated set and a validation set of the SDSS-V data, our method performs better than alternative standardizations by producing spectra that are both more uniform for M dwarfs with similar stellar parameters and more easily distinguished compared to M dwarfs of differing parameters. These results from our method will be crucial for better determining stellar parameters of M dwarfs using generative models.

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arXiv2025

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.

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arXiv2025

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, $α$, Mg, and Si, while the precision of at least 10 elements is better than 0.1 dex.

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arXiv2025

Sloan Digital Sky Survey-V: Pioneering Panoptic Spectroscopy

The Sloan Digital Sky Survey-V (SDSS-V) is pioneering panoptic spectroscopy: it is the first all-sky, multi-epoch, optical-to-infrared spectroscopic survey. SDSS-V is mapping the sky with multi-object spectroscopy (MOS) at telescopes in both hemispheres (the 2.5-m Sloan Foundation Telescope at Apache Point Observatory and the 100-inch du Pont Telescope at Las Campanas Observatory), where 500 zonal robotic fiber positioners feed light from a wide-field focal plane to an optical (R$\sim 2000$, 500 fibers) and a near-infrared (R$\sim 22,000$, 300 fibers) spectrograph. In addition to these MOS capabilities, the survey is pioneering ultra wide-field ($\sim$ 4000~deg$^2$) integral field spectroscopy enabled by a new dedicated facility (LVM-I) at Las Campanas Observatory, where an integral field spectrograph (IFS) with 1801 lenslet-coupled fibers arranged in a 0.5 degree diameter hexagon feeds multiple R$\sim$4000 optical spectrographs that cover 3600-9800 angstroms. SDSS-V's hardware and multi-year survey strategy are designed to decode the chemo-dynamical history of the Milky Way Galaxy and tackle fundamental open issues in stellar physics in its Milky Way Mapper program, trace the growth physics of supermassive black holes in its Black Hole Mapper program, and understand the self-regulation mechanisms and the chemical enrichment of galactic ecosystems at the energy-injection scale in its Local Volume Mapper program. The survey is well-timed to multiply the scientific output from major all-sky space missions. The SDSS-V MOS programs began robotic operations in 2021; IFS observations began in 2023 with the completion of the LVM-I facility. SDSS-V builds upon decades of heritage of SDSS's pioneering advances in data analysis, collaboration spirit, infrastructure, and product deliverables in astronomy.

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arXiv2025

Probing Binary Architectures of Lithium-Rich Giants in GALAH with COSMIC and Stellar Models

Surface lithium is depleted when a star goes through the first dredge-up phase, yet $1\%$ of red giants are found to be Li-rich. The formation mechanism for these remains uncertain. We combine observational constraints from GALAH Li-rich giants, with the binary population synthesis code COSMIC to investigate system properties of these objects assuming binary mass transfer. By evolving 9 million binary systems, we find that binary histories most consistent with observational constraints are mass transfer from an intermediate-mass AGB donor to a main-sequence star now observed as a Li-rich red giant. In GALAH, $9\%$ of main-sequence stars have $\rm A(Li)=2.5-3.2$ dex making it plausible to create red giants with $\rm A(Li)=1.5-2.2 \; dex$ via main-sequence mass transfer, but cannot explain the more enriched giants $\rm A(Li) \gtrsim 2.2 \; dex$. Nucleosynthetic yields from stellar models show that AGB stars with initial masses of $4.25-5 \; \rm M_\odot$ and $8 \; \rm M_\odot$ contain the most Li in their ejecta. Intermediate-mass AGB stars comprise $29\%$ of COSMIC results, with present-day separations $s=3.3\pm0.5 \rm \; AU$ and mass ratios $q=0.5-1.6$. We achieve $95\%$ agreement in mean enhancements in $\rm (Ba, Y)$ between GALAH observations and stellar models of 6 and $8 \rm \; M_\odot$ AGB, assuming $1\%$ mass transfer efficiency. We find a low mass transfer efficiency best reproduces GALAH observations suggesting that the preferred mass transfer mechanism for Li-enrichment is via wind Roche Lobe Overflow. While we constrain the most plausible binary parameters assuming AGB mass transfer creates Li-rich giants, discrepancies in nucleosynthesis comparisons, and the small fraction of Li-enhanced main-sequence stars suggests additional enrichment mechanisms are likely.

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arXiv2025

The completeness of the open cluster census towards the Galactic anticentre

Open clusters have long been used as tracers of Galactic structure. However, without a selection function to describe the completeness of the cluster census, it is difficult to quantitatively interpret their distribution. We create a method to empirically determine the selection function of a Galactic cluster catalogue. We test it by investigating the completeness of the cluster census in the outer Milky Way, where old and young clusters exhibit different spatial distributions. We develop a method to generate realistic mock clusters as a function of their parameters, in addition to accounting for Gaia's selection function and astrometric errors. We then inject mock clusters into Gaia DR3 data, and attempt to recover them in a blind search using HDBSCAN. We find that the main parameters influencing cluster detectability are mass, extinction, and distance. Age also plays an important role, making older clusters harder to detect due to their fainter luminosity function. High proper motions also improve detectability. After correcting for these selection effects, we find that old clusters are $2.97\pm0.11$ times more common at a Galactocentric radius of 13~kpc than in the solar neighbourhood -- despite positive detection biases in their favour, such as hotter orbits or a higher scale height. The larger fraction of older clusters in the outer Galaxy cannot be explained by an observational bias, and must be a physical property of the Milky Way: young outer-disc clusters are not forming in the outer Galaxy, or at least not with sufficient masses to be identified as clusters in Gaia DR3. We predict that in this region, more old clusters than young ones remain to be discovered. The current presence of old, massive outer-disc clusters could be explained by radial heating and migration, or alternatively by a lower cluster destruction rate in the anticentre.

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arXiv2025

Optical spectroscopic signatures of the red giant evolutionary state

Modern spectroscopic surveys output large data volumes. Theoretical models provide a means to transform the information encoded in these data to measurements of physical stellar properties. However, in detail the models are incomplete and simplified, and prohibit interpretation of the fine details in spectra. Instead, the available data provide an opportunity to use data-driven, differential analysis techniques, as a means towards understanding spectral signatures. We deploy such an analysis to examine core helium-fusing red clump (RC) and shell hydrogen-fusing red giant branch (RGB) stars, to uncover signatures of evolutionary state imprinted in optical stellar spectra. We exploit 786 pairs of RC and RGB stars from the GALAH survey, chosen to minimise spectral differences, with evolutionary state classifications from TESS and K2 asteroseismology. We report sub-percent residual, systematic spectral differences between the two classes of stars, and show that these residuals are significant compared to a reference sample of RC$-$RC and RGB$-$RGB pairs selected using the same criteria. First, we report systematic differences in the Swan ($\rm{C}_2$) band and CN bands caused by stellar evolution and a difference in mass, where RGB stars at similar stellar parameters have higher masses than RC stars. Secondly, we observe systematic differences in the line-width of the H$_α$ and H$_β$ lines caused by a difference in microturbulence, as measured by GALAH, where we measure higher microturbulence in RC stars than RGB stars. This work demonstrates the ability of large surveys to uncover the subtle spectroscopic signatures of stellar evolution using model-free, data-driven methods.

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arXiv2025

exoALMA. VIII. Probabilistic Moment Maps and Data Products using Non-parametric Linear Models

Extracting robust inferences on physical quantities from disk kinematics measured from Doppler-shifted molecular line emission is challenging due to the data's size and complexity. In this paper we develop a flexible linear model of the intensity distribution in each frequency channel, accounting for spatial correlations from the point spread function. The analytic form of the model's posterior enables probabilistic data products through sampling. Our method debiases peak intensity, peak velocity, and line width maps, particularly in disk substructures that are only partially resolved. These are needed in order to measure disk mass, turbulence, pressure gradients, and to detect embedded planets. We analyse HD 135344B, MWC 758, and CQ Tau, finding velocity substructures 50--200 ${\rm m s^{-1}}$ greater than with conventional methods. Additionally, we combine our approach with discminer in a case study of J1842. We find that uncertainties in stellar mass and inclination increase by an order of magnitude due to the more realistic noise model. More broadly, our method can be applied to any problem requiring a probabilistic model of an intensity distribution conditioned on a point spread function.

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arXiv2025

$Lux$: A generative, multi-output, latent-variable model for astronomical data with noisy labels

The large volume of spectroscopic data available now and from near-future surveys will enable high-dimensional measurements of stellar parameters and properties. Current methods for determining stellar labels from spectra use physics-driven models, which are computationally expensive and have limitations in their accuracy due to simplifications. While machine learning methods provide efficient paths toward emulating physics-based pipelines, they often do not properly account for uncertainties and have complex model structure, both of which can lead to biases and inaccurate label inference. Here we present $Lux$: a data-driven framework for modeling stellar spectra and labels that addresses prior limitations. $Lux$ is a generative, multi-output, latent variable model framework built on JAX for computational efficiency and flexibility. As a generative model, $Lux$ properly accounts for uncertainties and missing data in the input stellar labels and spectral data and can either be used in probabilistic or discriminative settings. Here, we present several examples of how $Lux$ can successfully emulate methods for precise stellar label determinations for stars ranging in stellar type and signal-to-noise from the $APOGEE$ surveys. We also show how a simple $Lux$ model is successful at performing label transfer between the $APOGEE$ and $GALAH$ surveys. $Lux$ is a powerful new framework for the analysis of large-scale spectroscopic survey data. Its ability to handle uncertainties while maintaining high precision makes it particularly valuable for stellar survey label inference and cross-survey analysis, and the flexible model structure allows for easy extension to other data types.

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arXiv2025

The GALAH Survey: Stellar parameters and abundances for 800,000 Gaia RVS spectra using GALAH DR4 and The Cannon

Analysing stellar parameters and abundances from nearly one million Gaia Data Release 3 (DR3) Radial Velocity Spectrometer (RVS) spectra poses challenges due to the limited spectral coverage (restricted to the infrared Ca II triplet) and variable signal-to-noise ratios of the data. To address this, we use The Cannon, a data-driven method, to transfer stellar parameters and abundances from the GALAH (GALactic Archaeology with HERMES) DR4 (R ~ 28,000) catalogue to the lower resolution Gaia DR3 RVS spectra (R ~ 11,500). Our model, trained on 14,484 common targets, predicts parameters such as $T_{\text{eff}}$, $\log g$, and $[\text{Fe/H}]$, along with several other elements across approximately 800,000 Gaia RVS spectra. We utilise stars from open and globular clusters present in the Gaia RVS catalogue to validate our predicted mean $[\text{Fe/H}]$ with high precision (~0.02-0.10 dex). Additionally, we recover the bimodal distribution of $[\text{Ti/Fe}]$ versus $[\text{Fe/H}]$, reflecting the high and low $α$-components of Milky Way disc stars, demonstrating The Cannon's capability for accurate stellar abundance determination from medium-resolution Gaia RVS spectra. The methodologies and resultant catalogue presented in this work highlight the remarkable potential of the RVS dataset, which by the end of the Gaia mission will comprise spectra of over 200 million stars.

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arXiv2025

A Data-Driven M Dwarf Model and Detailed Abundances for $\sim$17,000 M Dwarfs in SDSS-V

The cool temperatures of M dwarf atmospheres enable complex molecular chemistry, making robust characterization of M dwarf compositions a long-standing challenge. Recent modifications to spectral synthesis pipelines have enabled more accurate modeling of M dwarf atmospheres, but these methods are too slow for characterizing more than a handful of stars at a time. Data-driven methods such as The Cannon are viable alternatives, and can harness the information content of many M dwarfs from large spectroscopic surveys. Here, we train The Cannon on M dwarfs with FGK binary companions from the Sloan Digital Sky Survey-V/Milky Way Mapper (SDSS-V/MWM), with spectra from the Apache Point Observatory Galactic Evolution Experiment (APOGEE). The FGK-M pairs are assumed to be chemically homogeneous and span $-$0.56 $<$ [Fe/H] $<$ 0.31 dex. The resulting model is capable of inferring M dwarf $T_{\textrm{eff}}$ and elemental abundances for Fe, Mg, Al, Si, C, N, O, Ca, Ti, Cr, and Ni with median uncertainties of 13 K and 0.018$-$0.029 dex, respectively. We test the model by verifying that it reproduces reported abundance values of M dwarfs in open clusters and benchmark M dwarf datasets, as well as expected metallicity trends from stellar evolution. We apply the model to 16,590 M dwarfs in SDSS-V/MWM and provide their detailed abundances in our accompanying catalog.

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arXiv2025

Many Roads Lead to Lithium: Formation Pathways For Lithium-Rich Red Giants

Stellar models predict that lithium (Li) inside a star is destroyed during the first dredge-up phase, yet 1.2% of red giant stars are Li-rich. We aim to uncover possible origins of this population, by analysing 1155 Li-rich giants (A(Li) $\geq$ 1.5) in GALAH DR3. To expose peculiar traits of Li-rich stars, we construct a reference sample of Li-normal (doppelgänger) stars with matched evolutionary state and fiducial supernova abundances. Comparing Li-rich and doppelgänger spectra reveals systematic differences in the H-$α$ and Ca-triplet line profiles associated with the velocity broadening measurement. We also find twice as many Li-rich stars appear to be fast rotators (2% with $v_\textrm{broad} \gtrsim 20$ km s$^{-1}$) compared to doppelgängers. On average, Li-rich stars have higher abundances than their doppelgängers, for a subset of elements, and Li-rich stars at the base of RGB have higher mean $s-$process abundances ($\geq 0.05$ dex for Ba, Y, Zr), relative to their doppelgängers. External mass-transfer from intermediate-mass AGB companions could explain this signature. Additional companion analysis excludes binaries with mass ratios $\gtrsim$ 0.5 at $\gtrsim$ 7 AU. We also discover that highly Ba-enriched stars are missing from the Li-rich population, possibly due to low-mass AGB companions which preclude Li-enrichment. Finally, we confirm a prevalence of Li-rich stars on the red clump that increases with lithium, which supports an evolutionary state mechanism for Li-enhancement. Multiple culprits, including binary spin-up and mass-transfer, are therefore likely mechanisms of Li-enrichment.

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arXiv2024

The realm of Aurora. Density distribution of metal-poor giants in the heart of the Galaxy

The innermost portions of the Milky Way's stellar halo have avoided scrutiny until recently. The lack of wide-area survey data, made it difficult to reconstruct an uninterrupted view of the density distribution of the metal-poor stars inside the Solar radius. In this study, we utilize red giant branch (RGB) stars from Gaia, with metallicities estimated using spectro-photometry from Gaia Data Release 3. Accounting for Gaia's selection function, we examine the spatial distribution of metal-poor ([M/H]<-1.3) RGB stars, from the Galactic centre (r~1 kpc) out to beyond the Solar radius (r~18 kpc). Our best-fitting single-component cored power-law model shows a vertical flattening of ~0.5 and a slope -3.4, consistent with previous studies. Motivated by the mounting evidence for two distinct stellar populations in the inner halo, we additionally test a range of two-component models. One of the components models the tidal debris from the Gaia Sausage/Enceladus merger, while the other captures the Aurora population -- stars that predate the Galactic disk formation. Our best-fit two-component model suggests that both populations contribute equally around the Solar radius, but Aurora dominates the inner halo with a steeper power-law index of -4.5, in agreement with the nitrogen-rich star distribution measured by Horta et al. (2021).

astro-ph.GA↗

arXiv2024

Improving Radial Velocities by Marginalizing over Stars and Sky: Achieving 30 m/s RV Precision for APOGEE in the Plate Era

The radial velocity catalog from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) is unique in its simultaneously large volume and high precision as a result of its decade-long survey duration, multiplexing (600 fibers), and spectral resolution of $R \sim 22,500$. However, previous data reductions of APOGEE have not fully realized the potential radial velocity (RV) precision of the instrument. Here we present an RV catalog based on a new reduction of all 2.6 million visits of APOGEE DR17 and validate it against improved estimates for the theoretical RV performance. The core ideas of the new reduction are the simultaneous modeling of all components in the spectra, rather than a separate subtraction of point estimates for the sky, and a marginalization over stellar types, rather than a grid search for an optimum. We show that this catalog, when restricted to RVs measured with the same fiber, achieves noise-limited precision down to 30 m/s and delivers well-calibrated uncertainties. We also introduce a general method for calibrating fiber-to-fiber constant RV offsets and demonstrate its importance for high RV precision work in multi-fiber spectrographs. After calibration, we achieve 47 m/s RV precision on the combined catalog with RVs measured with different fibers. This degradation in precision relative to measurements with only a single fiber suggests that refining line spread function models should be a focus in SDSS-V to improve the fiber-unified RV catalog.

astro-ph.IM↗