arXiv subjects

Andrew R. Casey

Publications and source records attributed to Andrew R. Casey.

At least 19 recordsLinked to original sources

arXiv2026

A Broken Clock Is Right Twice a Day: [Ce/Mg] Is Not a Universal Chemical Clock

The ratio of $s$-process to $\alpha$-element enrichment ($[s/\alpha]$) has been proposed as a ``chemical clock,'' or a means to estimate stellar ages. However, the age--$[s/\alpha]$ relation varies with metallicity and location in the Galaxy, and the observed trends are not well predicted by galactic chemical evolution models. We quantify the age--[Ce/Mg] correlation across the Galactic disk in roughly 100,000 red giant stars observed with APOGEE in the SDSS-V Milky Way Mapper survey. We find that the slope of the correlation varies significantly with metallicity and guiding radius in the chemical thin disk. The trend is steepest in the outer disk and below Solar metallicity, while the most metal-rich stars and those in the inner disk show no correlation with age. In contrast, [Ce/Mg] patterns in the chemical thick disk are consistent across the Galaxy. Halo stars have higher [Ce/Mg] than the chemical thick disk, suggesting that asymptotic giant branch (AGB) enrichment is important even at low metallicity. Overall, patterns in [Ce/Mg] trace both the local star formation history and AGB nucleosynthesis. The complex interplay between [Ce/Mg], age, metallicity, and Galactic position means that [Ce/Mg] (and by extension $[s/\alpha]$) is not a universal chemical clock.

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arXiv2026

They Won't Be Giants: Missing Metal-Rich RGB Stars in Gaia Data Indicate Truncated Stellar Evolution

We investigate the population of luminous red giant branch stars as a function of metallicity using Gaia XP metallicity combined with SDSS-V, GALAH, and LAMOST. After applying uniform selection criteria and extinction corrections, we construct absolute magnitude distributions across metallicity bins spanning [Fe/H] =-1 to >0.4. We find a systematic deficit of luminous giants at high metallicity, while the red clump and lower red giant branch populations remain largely unchanged. This behavior is consistent with enhanced mass loss at high metallicity, arising from either binary interactions or single-star evolution. This trend is robust across multiple surveys and persists within volume-limited subsamples (1-4 kpc), suggesting it is not driven by distance or selection effects. Synthetic stellar populations based on PARSEC isochrones reproduce the overall magnitude distributions but do not predict a decline in luminous giants with metallicity. Tests of potential systematics, including extinction effects and metallicity scale consistency using open clusters, do not account for the observed trend. We also find no evidence that survey-to-survey differences in metallicity drive the observed result. Together, these findings suggest a metallicity-dependent reduction in the number of luminous red giants that is not captured by current models. This result may have implications for stellar evolution at high metallicity, helium white dwarf formation, and the initial mass function as well as the UV upturn in metal-rich galaxies.

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arXiv2026

The Open Cluster Chemical Abundances and Mapping Survey XI. First Gradients from SDSS/MWM BOSS Determined Clusters

The Milky Way Mapper program in the fifth generation of the Sloan Digital Sky Survey (SDSS-V/MWM) has observed millions of stars, thousands of them in open clusters. The Open Cluster Chemical Abundances and Mapping (OCCAM) survey continues to create comprehensive datasets of open clusters and their members in order to constrain Galactic parameters. This eleventh contribution from the OCCAM survey is the first to use stellar parameters from stars observed with the optical Baryon Oscillation Spectroscopic Survey (BOSS) spectrograph to determine cluster membership. We use data from SDSS-V/MWM's 20th Data Release (DR20) and curate a sample of 1883 stars in 111 open clusters, including 95 not in previous OCCAM samples based on infrared data from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectrograph. The sample includes 16 clusters with stars observed using both the BOSS and APOGEE spectrographs, and we find consistent agreement in measurements of both [Fe/H] and [$\alpha/M$]. The BOSS sample includes the majority of the clusters at young ages (Age $< 150$ Myr) that complement the APOGEE sample of primarily older clusters. We use the combined BOSS+APOGEE OCCAM sample to constrain the radial metallicity gradient with respect to $R_{guide}$ ($-0.079 \pm 0.005 \text{ dex kpc}^{-1}$) and $R_{gc}$ ($-0.082 \pm 0.006 \text{ dex kpc}^{-1}$), which agree well with results from previous OCCAM papers using only APOGEE data. Finally, the inclusion of the primarily young BOSS clusters has not changed that the OCCAM open cluster sample indicates no significant evolution of this gradient in different mono-age populations.

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arXiv2026

The Twentieth Data Release of the Sloan Digital Sky Survey: First All-Sky BOSS Spectra, eROSITA-SDSS-V Mapper Coordinated Observations, and a Preview of the Local Volume Mapper

This paper presents the twentieth data release (DR20) from the Sloan Digital Sky Survey, the third data release of its fifth generation (SDSS-V). SDSS-V is a panoptic spectroscopy survey that is mapping the stars, gas, and galaxies through three scientific programs: the Milky Way Mapper (MWM), the Local Volume Mapper (LVM), and the Black Hole Mapper (BHM). DR20 presents the first optical (BOSS) SDSS-V spectra from southern hemisphere for the MWM and BHM surveys; new optical MWM and BHM data from the northern hemisphere are also available, for a total over 3 million spectra of 1.5 million stars and half a million galaxies and quasars, with galactic and extragalactic x-ray targets coordinate with eROSITA DR2. DR20 includes integral field spectroscopy maps from LVM of six targets and 169 tiles, spanning Galactic HII regions, planetary nebulae, and nearby galaxies. Additionally, eighteen value added catalogs are also released with DR20, based on SDSS-V MWM and BHM data, and we present a new LVM visualization tool including an RGB HiPS map as a value added product.

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arXiv2026

Payne4GAIN: NLTE Corrections for Red Giants in Milky Way Mapper using H-Band Neural Network Emulators

The majority of spectroscopic surveys assume local thermodynamic equilibrium (LTE) during the modeling of stellar spectra. This assumption begins to break down for luminous stars, like the red giants targeted by SDSS-V's Milky Way Mapper Survey in its Galactic Genesis program. In this work, we present non-LTE (NLTE) abundances for 360,000 red giant stars in Milky Way Mapper DR19, from infrared APOGEE spectra. We generate NLTE spectra using precomputed departure coefficient grids for Na, Mg, Si, Al, Ca, Ti, Mn, and Ni. To fit APOGEE spectra at scale, we train neural network emulators (NNEs) to synthesize LTE and NLTE H-band spectra. After verifying that the NNEs are accurate, we fit the APOGEE spectra with ASPCAP results that fall within the same parameter range as the training data. We find strong NLTE effects on the order of 0.1\,dex for Al, Mn, and Ti, and smaller effects for Si and Ni. We provide a catalog of the results of our LTE and NLTE fits, as well as NLTE-corrected ASPCAP abundances using a polynomial fit correction.

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arXiv2026

BOSS-CLAM: Utilizing a Constrained Linear Absorption Model to Infer Stellar Parameters from BOSS Spectra

Large spectroscopic surveys require robust pipelines capable of inferring stellar parameters over a wide range of the Hertzsprung-Russell (HR) diagram from data of varying quality. SDSS-V is one such survey, where the data from the lower-resolution, optical BOSS spectrograph will provide a large dataset covering a wide range of Galactic stellar populations. To better analyze these data, we present BOSS-CLAM, a generative, forward modeling pipeline for inferring effective temperature ($T_\mathrm{eff}$), surface gravity ($\log g$), metallicity ($[\mathrm{Fe/H}]$), and $\alpha-$abundance ($[\alpha/\mathrm{M}]$) from continuum-normalized BOSS spectra. BOSS-CLAM maps stellar labels to Non-negative Matrix Factorization (NMF) basis vector weights via a polynomial mapping jointly optimized with the spectral decomposition, which provides a more flexible framework for working with the lower-resolution BOSS data. Additionally, training labels are drawn from four complementary sources (ASPCAP, BOSS-MINESweeper, wide binaries, and a hot star validation sample), which enables coverage from cool M dwarfs through hot OB stars, and across a wide range of metallicity. We infer parameters for 1,708,214 BOSS spectra, with a recommended clean catalog of 915,514 sources. Validation against open and globular clusters demonstrates homogeneous, accurate abundances across a wide range of metallicity. Wide binary tests yield abundance uncertainties of $\sigma_{[\mathrm{Fe/H}]} \approx 0.15$ dex and $\sigma_{[\alpha/\mathrm{M}]} \approx 0.06$ dex at SNR = 10. Finally, we demonstrate that the BOSS-CLAM catalog recovers known chemical structure of the Milky Way disk and is well-suited for Galactic archaeology, chemical tagging, and stellar population modeling. The pipeline, trained model, and catalog are publicly released as part of SDSS-V DR20.

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arXiv2026

A Probabilistic Framework for Population Studies of the Solar Neighborhood: Application to SDSS-V and Gaia

Studies of the Solar Neighborhood require spectroscopic follow-up of stars identified in astrometric surveys to fully characterize their physical properties. The SDSS-V Solar Neighborhood Census (SNC) is a dedicated program to observe stars within 100~pc. However, due to competing observing programs and fiber assignment constraints, the resulting sample carries severe and complex selection effects. A framework is presented for characterizing the selection function of the SDSS-V SNC relative to the Gaia Catalog of Nearby Stars (GCNS), along with a forward modeling method to infer the properties of stellar subpopulations across the GCNS-defined 100 pc sample. The selection function is based on a method that models the selection probability as a function of sky position, Gaia G magnitude, and BP-RP. The resulting detection probabilities faithfully reproduce the known survey planning logic. This work further introduces the concept of a "subpopulation probability" -- a grid of posterior estimates across the Hertzsprung-Russell (HR) diagram representing the likelihood that a GCNS member belongs to a given SDSS-V defined subpopulation. The framework is validated with a mock dataset and its scientific utility is demonstrated through two applications using data from the Data Release 19: mapping H$\alpha$ emission across the HR diagram and measuring the variation of stellar density with mass and metallicity. These results illustrate how statistically robust population studies can be conducted with an incomplete spectroscopic survey when the selection function is well characterized. The code is made publicly available with this work, which will serve as an important tool for future studies.

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arXiv2026

Searching for Stellar Activity Cycles using Flares II: The TESS CVZ

Magnetic activity cycles provide a fundamental constraint on stellar dynamos, but remain difficult to identify beyond the Sun. However, recent studies have shown that flares offer a unique tracer of activity cycle behavior. In this study, we use seven years of short-cadence observations from the Transiting Exoplanet Survey Satellite (TESS) for over 14,000 stars in the Continuous Viewing Zone to search for long-term changes in flare activity. For each star, we perform injection and recovery tests and provide well-characterized completeness limits for flare detection thresholds, and flare finding results. From this search, we identify 17 stars with evidence of long-term variability in flare rate, synonymous with activity cycle behavior. These candidates span a range of effective temperatures, rotation periods, and flare-variability morphologies. One G-type star, TIC 167344043, stands out as the clearest solar-like case, despite rapid rotation and superflare activity. Our results identify candidate activity cycles in stars that are more rapidly rotating and flare-active than the typical stellar-activity-cycle targets in the literature. These systems probe a new regime where stellar dynamos are still evolving, providing critical constraints on when cycle-like magnetic variability first emerges.

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arXiv2026

Robust Heteroskedastic Matrix Factorization: A Generalization of PCA that Flags Outliers and Handles Missing Data

We present Robust Heteroskedastic Matrix Factorization (RHMF), a generalization of Principal Component Analysis (PCA) that is robust to outliers, handles per-feature uncertainties and missing data, and automatically flags per-feature and per-object anomalies. RHMF is useful both in recovering a low-dimensional embedding unspoiled by bad data or anomalies, and in identifying those anomalies. It utilises an iterative reweighting algorithm that implicitly maximizes a Student-t likelihood. This admits an equivalent probabilistic interpretation as fitting a hierarchical model with per-data-point latent variances. We deliver a fast JAX implementation, Robusta-HMF, and practical guidance for users. We demonstrate the ability of the model to identify and mitigate outliers of different classes. Identification accuracy is contingent on the choice of hyperparameters, but we show that these can be set reliably by cross-validation. We also apply RHMF to RVS spectra from Gaia DR3 to find main-sequence stars that are strange relative to their neighbors in color-magnitude space. We highlight specific examples, including a known binary hosting a Be star, and M-dwarfs with subtle emission in the Ca II triplet lines, indicative of accretion or magnetic activity, which would not be obvious to identify by eye.

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arXiv2026

The GALAH Survey: Neutron-Capture Elemental Abundances for 350,000 Gaia-RVS spectra and the Chemodynamics of Accreted Structures

We present a comprehensive data-driven spectroscopic analysis of 357,415 red giant stars using Gaia DR3 Radial Velocity Spectrometer (RVS) spectra (8460-8700 A; $R\approx11,500$), aimed at deriving homogenous stellar parameters and elemental abundances (collectively referred to as stellar labels). We employ The Cannon, a generative model based on 2747 giants in common with GALactic Archaeology with HERMES (GALAH) DR4, adopting GALAH labels ($R\approx28,000$) for training. The resulting model predicts 11 stellar labels for RVS giants: effective temperature ($T_{\rm eff}$), surface gravity ($\log g$), projected rotational velocity ($v\sin i$), and abundances of [Fe/H], [Ca/Fe], [Si/Fe], [Ni/Fe], [Ti/Fe], as well as the neutron-capture elements [Zr/Fe], [Ce/Fe], and [Nd/Fe]. Building on these results, we develop a probabilistic framework to chemically identify debris from the Gaia-Sausage-Enceladus (GSE) accretion event. A logistic regression classifier, optimized via Markov chain Monte Carlo sampling and trained on a small reference sample of GSE members and comparison stars, identifies stars with high GSE membership probabilities based solely on their chemical abundances, with the resulting candidates exhibiting distinctive abundance-ratio patterns, including [Ca/Ti], [Ti/Ce], and [Nd/Zr]. Applying independent kinematic constraints yields a robust sample of GSE candidates, demonstrating that the characteristic chemical signatures remain consistent after applying these constraints. This work demonstrates the potential of data-driven analysis techniques to extract detailed chemical information from medium-resolution spectra and establishes a framework for tracing Galactic accretion events using chemical abundances.

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arXiv2026

Milky Way Mapper decoded abundances -- II: From patterns to paths

The element abundances of Milky Way disc stars encode entangled imprints of multiple enrichment processes, making it difficult to uncover the underlying chemical evolution. Here we re-project 16 stellar abundances for 199,290 red giant stars ([Fe/H]$ > -1$) into a set of (4) shared enrichment patterns, providing a generative framework for learning the organising structure of the Milky Way disc. The relative contributions of these patterns vary systematically across the disc, revealing a low-dimensional enrichment basis that responds coherently to global drivers of disc evolution. By grouping stars according to their pattern contributions, we identify coherent enrichment pathways that exhibit strong chemo-spatial correlations and are stratified in both age and height above the plane, linking radial growth to vertical disc structure. Stars occupying similar positions along these enrichment pathways also show coherent vertical deviations across radius, indicating that the low-dimensional chemical structure captures the disc's response to dynamical perturbations. We identify a transition in enrichment behaviour at approximately 6 Gyr, marking the onset of a more chemically mixed regime with increasing contributions from delayed sources. Within this connected system, the observed $\alpha$-bimodality arises within a shared, low-dimensional abundance structure, with stars populating continuous sequences of changing enrichment fractions that are tightly coupled to spatial, temporal, and orbital coordinates across the Milky Way disc.

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arXiv2026

Milky Way Mapper decoded abundances -- I. Shared disc enrichment patterns

Elemental abundances in the Milky Way disc trace its star-formation and enrichment history, but predicting these abundances from theory is limited by uncertain nucleosynthetic yields and poorly constrained chemical evolution models. Large surveys provide many abundances that enable multi-dimensional insight. However, having so much data available complicates joint visualisation and physical interpretation. Here, we examine the element abundances of 70,057 red giant stars from the Milky Way Mapper survey ([Fe/H] $> -1$), using 16 elements (O,~Mg,~Al,~Si,~S,~K,~Ca,~Ti,~V, ~Cr, Mn,~Fe,~Co,~Ni,~Ce,~Nd). To tackle the challenges of joint-interpretation of these elements, we build a generative data-driven model, expressing each star's abundance vector as a linear combination of a few ($4$) latent nucleosynthetic patterns. These patterns are shared among the population but vary in fraction between stars. The model accurately generates the measured abundances, with $\chi^2 < 3$ (5) for $\sim$ 80\% (95\%) of stars. Model failures, where stars' abundances are not generated by the latent basis reveal accreted material and the role of multiple channels of metal-poor disk enrichment. We associate the recovered patterns, which represent high-precision ($\sigma_P \sim 3$\%) nucleosynthetic channels, with specific enrichment sources; (early and late) core-collapse supernovae, supernovae Type Ia, and asymptotic giant branch stars. We subsequently explore how the dominance of enrichment channels varies across age, metallicity and spatial extent of the disk, and show that enrichment patterns tightly couple to orbital properties. Mean pattern fractions vary smoothly with enrichment, and change rapidly across the valley between the high- and low-$\alpha$ sequences. Our results provide a framework for improving our understanding of Galactic evolution in the Milky Way.

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arXiv2026

Evaluating Classifications of Extremely Metal-poor Candidates Selected from Gaia XP Spectra

Extremely metal-poor stars are intrinsically rare, but emerging methods exist to accurately classify them from all-sky Gaia XP low-resolution spectra. To assess their overall accuracy for targeting metal-poor stars, we present a high-resolution spectroscopic followup of 75 very metal-poor candidates selected from the catalog by R. Andrae, V. Chandra, and H. W. Rix. We discover 2 new extremely metal-poor ($\rm{[Fe / H]}<-3$) stars and 20 new very metal-poor ($\rm{[Fe/H]} < -2$) stars. Abundances of up to 22 elements are derived from 1D local thermodynamic equilibrium analysis and kinematic parameters are derived using Gaia astrometry and spectroscopic radial velocities. The chemodynamical properties are mostly consistent with expectations for halo stars, but we discover an Mg-enhanced CEMP star ($\mathrm{[Mg/Fe]} = 0.89$) and an Mg-poor star from an accreted ultra-faint dwarf galaxy. The Gaia XP metallicity estimates are consistent with our $\rm{[Fe/H]}$ measurements down to $\rm{[Fe/H]}\sim -3.0$, but estimates worsen in highly extincted regions. We find that 4 other XP-based metallicity catalogs succeed in mitigating contaminants and can also classify metal-poor stars robustly to $\rm{[Fe/H]}\sim -3.0$. Our results demonstrate the utility of Gaia XP spectra for identifying the most metal-poor stars across the Galaxy.

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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 $\alpha$-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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arXiv2026

Optimal and Unbiased Fluxes from Up-the-Ramp Detectors under Variable Illumination

Near-infrared (NIR) detectors -- which use non-destructive readouts to measure time-series counts-per-pixel -- play a crucial role in modern astrophysics. Standard NIR flux extraction techniques were developed for space-based observations and assume that source fluxes are constant over an observation. However, ground-based telescopes often see short-timescale atmospheric variations that can dramatically change the number of photons arriving at a pixel. This work presents a new statistical model that shares information between neighboring spectral pixels to characterize time-variable observations and extract unbiased fluxes with optimal uncertainties. We generate realistic synthetic data using a variety of flux and amplitude-of-time-variability conditions to confirm that our model recovers unbiased and optimal estimates of both the true flux and the time-variable signal. We find that the time-variable model should be favored over a constant-flux model when the observed count rates change by more than 3.5%. Ignoring time variability in the data can result in flux-dependent, unknown-sign biases that are as large as ~120% of the flux uncertainty. Using real APOGEE spectra, we find empirical evidence for approximately wavelength-independent, time-dependent variations in count rates with amplitudes much greater than the 3.5% threshold. Our model can robustly measure and remove the time-dependence in real data, improving the quality of data-model comparison. We show several examples where the observed time-dependence quantitatively agrees with independent measurements of observing conditions, such as variable cloud cover and seeing.

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arXiv2025

The Astrometric Resoeccentric Degeneracy: Eccentric Single Planets Mimic 2:1 Resonant Planet Pairs in Astrometry

Detections of long-period giant exoplanets will expand dramatically with Gaia Data Release 4 (DR4), but interpreting these signals will require care. We derive the astrometric resoeccentric degeneracy: an astrometric analogue of the well-known radial velocity degeneracy in which a single eccentric planet can mimic two circular planets near a 2:1 period ratio. To first order in eccentricity, the sky-projected motion of a single eccentric orbit decomposes into a fundamental mode and first harmonic with an amplitude proportional to that eccentricity. A pair of coplanar, circular planets in a 2:1 orbital resonance produces the same harmonic structure: the outer planet sets the fundamental mode, while the inner planet supplies an apparent first harmonic. We present a mapping between the harmonic amplitudes and effective eccentricity ($e_\mathrm{eff}$) of a single planet that mimics a 2:1 configuration, demonstrating that $e_\mathrm{eff} = \, 2^{1/3}(M_{p,2}/M_{p,1})$, the masses of the inner and outer planets, respectively. Using simulated Gaia data we show that (1) coplanar 2:1 systems are statistically indistinguishable from a single eccentric planet and (2) mutual inclination can break this degeneracy. This bias favors detecting mutually inclined systems, often fingerprints of a dynamically hot history -- traces for processes such as planet-planet scattering or secular chaos. Determining the planetary architectures in which this degeneracy holds will be essential for measuring cool-giant occurrence rates with Gaia and for inferring their dynamical evolution histories.

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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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