arXiv subjects

Guillaume Guiglion

Publications and source records attributed to Guillaume Guiglion.

18 recordsLinked to original sources

arXiv2026

Observational constraints on the origin of the elements. X. Combining NLTE and machine learning for chemical diagnostics of 4 million stars in the 4MIDABLE-HR survey

We present the 4MOST-HR resolution Non-Local Thermal Equilibrium (NLTE) Payne artificial neural network (ANN), trained on $404\,793$ new FGK spectra with 16 elements computed in NLTE. This network will be part of the Stellar Abundances and atmospheric Parameters Pipeline (SAPP), which will analyse 4 million stars during the five year long 4MOST consortium 4: 4MOST MIlky way Disc And BuLgE High-Resolution (4MIDABLE-HR) survey. A fitting algorithm using this ANN is also presented that is able to fully-automatically and self-consistently derive both stellar parameters and elemental abundances. The ANN is validated by fitting 121 observed spectra of low-mass FGKM type stars, including main-sequence dwarf, subgiant and giant stars down to [Fe/H] $\approx -3.3$ degraded to 4MOST-HR resolution of $R\approx20\,000$, and comparing the derived abundances with the output of the classical radiative transfer code TSFitPy. We are able to recover all 18 elemental abundances with a bias~$<0.13$ and spread~$<0.16$\,dex, although the typical values are $<0.09$ dex for most elements. These abundances are compared to the OMEGA+ Galactic Chemical Evolution model, showcasing for the first time, the expected performance and results obtained from high-resolution spectra of the quality expected to be obtained with 4MOST. The expected Galactic trends are recovered, and we highlight the potential of using many chemical elements to constrain the formation history of the Galaxy.

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arXiv2026

A method to derive self-consistent NLTE astrophysical parameters for 4 million high-resolution 4MOST stellar spectra in half a day with invertible neural networks

Modern spectroscopic surveys obtain spectra for millions of stars. However, classical spectroscopic methods can often be computationally expensive, rendering them impractical for the analysis of large datasets. We introduce a novel simulation-based deep-learning approach for the efficient analysis of high-resolution stellar spectra to be obtained with the upcoming high-resolution 4MOST spectrograph. We used a suite of synthetic non-local thermodynamic equilibrium (NLTE) spectra generated with Turbospectrum to mimic 4MOST observations and trained a conditional invertible neural network (cINN) for the purpose of predicting self-consistently stellar surface parameters and chemical abundances. The cINN is a neural network architecture that estimates full posterior distributions for the target stellar properties, providing an intrinsic uncertainty estimate. We evaluated the predictive performance of the trained cINN model on both synthetic data and observed spectra of stars. We found that our new cINN trained on NLTE synthetic spectra is capable of recovering stellar parameters with average errors ($σ$) of $33$ K for $T_\mathrm{eff}$, $0.16$ dex for $\log(g)$, and $0.12$ dex for [Fe/H], $0.1$ dex for [Ca/Fe], $0.11$ for [Mg/Fe], and $0.51$ dex for [Li/Fe], respectively, at a signal to noise ratio of 250 per Angstrom. From the analysis of the observed spectra of Gaia-ESO / 4MOST / PLATO benchmark stars, we verified that our NLTE estimates for stellar parameters and abundances are consistent with results obtained with the independent code TSFitPy. We conclude that the NLTE cINN is robust and can, theoretically, evaluate 4 million high-resolution 4MOST spectra in less than a day, using GPU acceleration.

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arXiv2026

oMEGACat. X. Shedding light on the disrupted dwarf galaxy of Omega Centauri

Omega Centauri ($ω\,$Cen) is the most massive and chemically complex star cluster in the Milky Way and is widely regarded as the surviving nuclear star cluster of an accreted dwarf galaxy. However, its parent host remains uncertain. Here, we investigate a scenario in which Sequoia, Thamnos, and Gaia--Enceladus (GE) are debris from a single disrupted progenitor, the $ω\,$Dwarf, whose nucleus survives today as $ω\,$Cen. Using APOGEE and GALAH abundances together with Gaia astrometry, we reconstruct the chemical structure across this progenitor adopting orbital energy as a proxy for pre-merger radius. We find that the chemically evolved (younger Al-N-He-rich) population is strongly concentrated toward the inner regions, representing a population formed after/during the merger, while the primordial population represents a dwarf-galaxy-like population, supporting a common dwarf-galaxy origin for its components. The metallicity profile shows an inverted U-shaped gradient similar to those observed in present-day nucleated dwarf galaxies. At the same time, the inner regions ($ω\,$Cen+Thamnos) are more $α$-enhanced than the outskirts, pointing to shorter and more efficient star formation and indicating that the nucleus may have assembled through the merger of inspiraling globular clusters. Neutron-capture abundances reveal a Eu-rich, r-process-dominated outskirts and inner regions enhanced in [Ba/Eu] and [La/Eu], requiring delayed enrichment and more complex chemical evolution. Finally, our analysis shows that Sequoia and Thamnos naturally fit an outside-in stripping sequence around $ω\,$Cen, whereas the connection with GE remains unsure.

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arXiv2025

The Spheroidal Bulge of the Milky Way: Chemodynamically Distinct from the Inner-Thick Disc and Bar

Studying the composition and origin of the inner region of our Galaxy -- the "Galactic bulge" -- is crucial for understanding the formation and evolution of the Milky Way and other galaxies. We present new observational constraints based on a sample of around 18,000 stars in the inner Galaxy, combining Gaia DR3 RVS and APOGEE DR17 spectroscopy. Gaia-RVS complements APOGEE by improving sampling of the metallicity, [Fe/H] in the -2.0 to -0.5 dex range. This work marks the first application of Gaia-RVS spectroscopy to the bulge region, enabled by a novel machine learning approach (hybrid-CNN) that derives stellar parameters from intermediate-resolution spectra with precision comparable to APOGEE's infrared data. We performed full orbit integrations using a barred Galactic potential and applied orbital frequency analysis to disentangle the stellar populations in the inner Milky Way. For the first time, traced by the field stars, we are able to robustly identify the long-sought pressure supported bulge. We show this stellar population to be chemically and kinematically distinct from the other main components co-existing in the same region. The spheroidal bulge has a metallicity distribution function (MDF) peak at around -0.70 dex extending to solar value, is dominated by a high-[alpha/Fe] population with almost no dependency on metallicity, consistent with very rapid early formation, predating the thick disc and the bar. We find evidence that the bar has influenced the dynamics of the spheroidal bulge, introducing a mild triaxiality and radial extension. We identify a group of stars on X4 orbits, likely native to the early spheroid, as this population mimics the chemistry of the spheroidal bulge, with a minor contamination from the more metal-poor ([Fe/H] < -1.0) halo. We find the inner-thick disc to be kinematically hotter (mean Vphi ~125 km/s) than the local-thick disc. ...

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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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arXiv2024

Galaxy Spectra neural Network (GaSNet). II. Using Deep Learning for Spectral Classification and Redshift Predictions

Large sky spectroscopic surveys have reached the scale of photometric surveys in terms of sample sizes and data complexity. These huge datasets require efficient, accurate, and flexible automated tools for data analysis and science exploitation. We present the Galaxy Spectra Network/GaSNet-II, a supervised multi-network deep learning tool for spectra classification and redshift prediction. GaSNet-II can be trained to identify a customized number of classes and optimize the redshift predictions for classified objects in each of them. It also provides redshift errors, using a network-of-networks that reproduces a Monte Carlo test on each spectrum, by randomizing their weight initialization. As a demonstration of the capability of the deep learning pipeline, we use 260k Sloan Digital Sky Survey spectra from Data Release 16, separated into 13 classes including 140k galactic, and 120k extragalactic objects. GaSNet-II achieves 92.4% average classification accuracy over the 13 classes (larger than 90% for the majority of them), and an average redshift error of approximately 0.23% for galaxies and 2.1% for quasars. We further train/test the same pipeline to classify spectra and predict redshifts for a sample of 200k 4MOST mock spectra and 21k publicly released DESI spectra. On 4MOST mock data, we reach 93.4% accuracy in 10-class classification and an average redshift error of 0.55% for galaxies and 0.3% for active galactic nuclei. On DESI data, we reach 96% accuracy in (star/galaxy/quasar only) classification and an average redshift error of 2.8% for galaxies and 4.8% for quasars, despite the small sample size available. GaSNet-II can process ~40k spectra in less than one minute, on a normal Desktop GPU. This makes the pipeline particularly suitable for real-time analyses of Stage-IV survey observations and an ideal tool for feedback loops aimed at night-by-night survey strategy optimization.

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arXiv2024

Discovery of the local counterpart of disc galaxies at z > 4: The oldest thin disc of the Milky Way using Gaia-RVS

JWST has recently detected numerous disc galaxies at high-redshifts and there have been observations of cold disc galaxies at z > 4 with ALMA. In the Milky Way, recent studies find metal-poor stars in cold disc orbits, suggesting an ancient disc. We investigated a sample of 565,606 stars from the hybrid-CNN analysis of the Gaia-DR3 RVS stars. The sample contains 8,500 stars with [Fe/H]<-1. For a subset of ~200,000 MSTO and subgiant stars we computed distances and ages using the StarHorse code with a mean precision of 1% and 12%, respectively. First, we confirm the existence of metal-poor stars in thin disc orbits - over 50% are older than 13 Gyr. Second, we report the discovery of the oldest thin disc of the Milky Way(MW), which extends across a wide range of metallicities, from metal-poor to super-solar stars. The metal-poor stars in disc orbits manifest as a readily visible tail of the metallicity distribution. The high-[α/Fe] thick disc exhibits a vertical velocity dispersion of 35 km/s, while the thin disc shows 10 to 15 km/s lower at similar ages. Our old thin disc $σ_{V_z}$ appears similar to those estimated for the high-z disc galaxies. Third, we extend the [Y/Mg] chemical clock to the oldest ages and estimate a slope of -0.038 dex/Gyr. Finally, we confirm our discovery by showing that the splash includes high- and low-[α/Fe] populations that are both old and extends to super-solar [Fe/H]. We find about 6 to 10% of the old thin disc was heated to thick disc orbits with the youngest splashed stars being 9 to 10 Gyrs. We conclude the MW thin disc forms <1 billion years from Big Bang, building up inside-out, preceding earlier estimates by about 4-5 billion years. Considering a massive merger event such as the GSE, a Splash is expected - we find a portion of the old thin disc is heated to thick disc velocities and the Splash extends to super-solar [Fe/H] regimes.

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arXiv2023

Insights from Super-Metal-Rich Stars: Is the Milky Way bar young?

Super-metal-rich (SMR) stars, currently in the solar neighbourhood, are expected to originate only in the inner Galaxy and have definitely migrated. We aim at studying a large sample of SMR stars to provide constraints on the epoch of the bar formation and its impact on the MW disc stellar populations. We investigate a sample of 169,701 MSTO and SGB stars with 6D phase space information and high-quality stellar parameters coming from the hybrid-CNN analysis of the Gaia-DR3 RVS stars. We compute distances and ages using the StarHorse code with a mean precision of 1% and 11%, respectively. From these, 11,848 stars have metallicity ([Fe/H]) above 0.15 dex. We report a metallicity dependence of spatial distribution of stellar orbits shown by the bimodal distribution in the guiding radius at 6.9 and 7.9 kpc, first appearing at [Fe/H]~0.1 dex, becoming very pronounced at larger [Fe/H]. In addition, we've observed a trend where the most metal-rich stars, with [Fe/H]~0.4 dex, are predominantly old (9-12 Gyrs) but show a gradual decline in [Fe/H] with age, reaching around 0.25 dex at about 4 Gyrs ago, followed by a sharp drop around 3 Gyrs ago. Furthermore, our full dataset reveals a clear peak in the age-metallicity relationship during the same period, indicating a SF burst around 3-4 Gyrs ago with slightly sub-solar [Fe/H] and enhanced [$α$/Fe]. We show the SMR stars are good tracers of the bar activity. We interpret the steep decrease in number of SMR stars at around 3 Gyr as the end of the bar formation epoch. In this scenario, the peak of bar activity also coincides with a peak in the SF activity in the disc. Although the SF burst around 3 Gyr ago has been reported previously, its origin was unclear. Here, we suggest the SF burst to have been triggered by the high bar activity, 3-4 Gyr ago. According to these results and interpretation, the MW bar could be young.

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arXiv2023

Observational constraints on the origin of the elements. VI. Origin and evolution of neutron-capture elements as probed by the Gaia-ESO survey

Most heavy elements beyond the iron peak are synthesized via neutron capture processes. The nature of the astrophysical sites of neutron capture processes is still very unclear. In this work we explore the observational constraints of the chemical abundances of s-process and r-process elements on the sites of neutron-capture processes by applying Galactic chemical evolution (GCE) models to the data from Gaia-ESO large spectroscopic stellar survey. For the r-process, the [Eu/Fe]-[Fe/H] distribution suggests a short delay time of the site that produces Eu. Other independent observations (e.g., NS-NS binaries), however, suggest a significant fraction of long delayed ($>1$Gyr) neutron star mergers (NSM). When assuming NSM as the only r-process sites, these two observational constraints are inconsistent at above 1$σ$ level. Including short delayed r-process sites like magneto-rotational supernova can resolve this inconsistency. For the s-process, we find a weak metallicity dependence of the [Ba/Y] ratio, which traces the s-process efficiency. Our GCE model with up-to-date yields of AGB stars qualitatively reproduces this metallicity dependence, but the model predicts a much higher [Ba/Y] ratio compared to the data. This mismatch suggests that the s-process efficiency of low mass AGB stars in the current AGB nucleosynthesis models could be overestimated.

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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.

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arXiv2023

Unveiling the time evolution of chemical abundances across the Milky Way disk with APOGEE

Chemical abundances are an essential tool in untangling the Milky Way's enrichment history. However, the evolution of the interstellar medium abundance gradient with cosmic time is lost as a result of radial mixing processes. For the first time, we quantify the evolution of many observational abundances across the Galactic disk as a function of lookback time and birth radius, $R_\text{birth}$. Using an empirical approach, we derive $R_\text{birth}$ estimates for 145,447 APOGEE DR17 red giant disk stars, based solely on their ages and [Fe/H]. We explore the detailed evolution of 6 abundances (Mg, Ca ($α$), Mn (iron-peak), Al, C (light), Ce (s-process)) across the Milky Way disk using 87,426 APOGEE DR17 red giant stars. We discover that the interstellar medium had three fluctuations in the metallicity gradient $\sim 9$, $\sim 6$, and $\sim4$ Gyr ago. The first coincides with the end of high-$α$ sequence formation around the time of the Gaia-Sausage-Enceladus disruption, while the others are likely related to passages of the Sagittarius dwarf galaxy. A clear distinction is found between present-day observed radial gradients with age and the evolution with lookback time for both [X/Fe] and [X/H], resulting from the significant flattening and inversion in old populations due to radial migration. We find the [Fe/H]--[$α$/Fe] bimodality is also seen as a separation in the $R_\text{birth}$--[X/Fe] plane for the light and $α$-elements. Our results recover the chemical enrichment of the Galactic disk over the past 12 Gyr, providing tight constraints on Galactic disk chemical evolution models.

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arXiv2020

The Sixth Data Release of the Radial Velocity Experiment (RAVE) -- II: Stellar Atmospheric Parameters, Chemical Abundances and Distances

We present part 2 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. In the second of two publications, we present the data products derived from 518387 observations of 451783 unique stars using a suite of advanced reduction pipelines focussing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters (Teff, log(g), and the overall metallicity), enhanced stellar atmospheric parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar atmospheric parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [alpha/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The RAVE DR6 catalogs are cross matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.

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arXiv2020

The Sixth Data Release of the Radial Velocity Experiment (RAVE) -- I: Survey Description, Spectra and Radial Velocities

The Radial Velocity Experiment (RAVE) is a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A). The 6th and final data release (DR6 or FDR) is based on 518387 observations of 451783 unique stars. RAVE observations were taken between 12 April 2003 and 4 April 2013. Here we present the genesis, setup and data reduction of RAVE as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in RAVE DR6. Furthermore, we present derived spectral classification and radial velocities for the RAVE targets, complemented by cross matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km/s, while 95% of the objects have radial velocities better than 4.0 km/s. Stellar atmospheric parameters, abundances and distances are presented in subsequent publication. The data can be accessed via the RAVE Web (http://rave-survey.org) or the Vizier database.

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arXiv2019

Single-lined Spectroscopic Binary Star Candidates from a Combination of the RAVE and Gaia DR2 surveys

The combination of the final version of the RAVE spectroscopic survey data release 6 with radial velocities and astrometry from Gaia DR2 allows us to identify and create a catalog of single lined binary star candidates (SB1), their inferred orbital parameters, and to inspect possible double lined binary stars (SB2). A probability function for the detection of radial velocity (RV) variations is used for identifying SB1 candidates. The estimation of orbital parameters for main sequence dwarfs is performed by matching the measured RVs with theoretical velocity curves sampling the orbital parameter space. The method is verified by studying a mock sample from the SB9 catalogue. Studying the boxiness and asymmetry of the spectral lines allows us to identify possible SB2 candidates, while matching their spectra to a synthetic library indicates probable properties of their components. From the RAVE catalog we select 37,664 stars with multiple RV measurements and identify 3838 stars as SB1 candidates. Joining RAVE and Gaia DR2 yields 450,646 stars with RVs measured by both surveys and 27,716 of them turn out to be SB1 candidates, which is an increase by an order of magnitude over previous studies. For main sequence dwarf candidates we calculate their most probable orbital parameters: orbital periods are not longer than a few years and primary components have masses similar to the Solar mass. All our results are available via Vizier/CDS.

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arXiv2019

The Detailed Science Case for the Maunakea Spectroscopic Explorer, 2019 edition

(Abridged) The Maunakea Spectroscopic Explorer (MSE) is an end-to-end science platform for the design, execution and scientific exploitation of spectroscopic surveys. It will unveil the composition and dynamics of the faint Universe and impact nearly every field of astrophysics across all spatial scales, from individual stars to the largest scale structures in the Universe. Major pillars in the science program for MSE include (i) the ultimate Gaia follow-up facility for understanding the chemistry and dynamics of the distant Milky Way, including the outer disk and faint stellar halo at high spectral resolution (ii) galaxy formation and evolution at cosmic noon, via the type of revolutionary surveys that have occurred in the nearby Universe, but now conducted at the peak of the star formation history of the Universe (iii) derivation of the mass of the neutrino and insights into inflationary physics through a cosmological redshift survey that probes a large volume of the Universe with a high galaxy density. MSE is positioned to become a critical hub in the emerging international network of front-line astronomical facilities, with scientific capabilities that naturally complement and extend the scientific power of Gaia, the Large Synoptic Survey Telescope, the Square Kilometer Array, Euclid, WFIRST, the 30m telescopes and many more.

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arXiv2019

Stellar Astrophysics and Exoplanet Science with the Maunakea Spectroscopic Explorer (MSE)

The Maunakea Spectroscopic Explorer (MSE) is a planned 11.25-m aperture facility with a 1.5 square degree field of view that will be fully dedicated to multi-object spectroscopy. A rebirth of the 3.6m Canada-France-Hawaii Telescope on Maunakea, MSE will use 4332 fibers operating at three different resolving powers (R ~ 2500, 6000, 40000) across a wavelength range of 0.36-1.8mum, with dynamical fiber positioning that allows fibers to match the exposure times of individual objects. MSE will enable spectroscopic surveys with unprecedented scale and sensitivity by collecting millions of spectra per year down to limiting magnitudes of g ~ 20-24 mag, with a nominal velocity precision of ~100 m/s in high-resolution mode. This white paper describes science cases for stellar astrophysics and exoplanet science using MSE, including the discovery and atmospheric characterization of exoplanets and substellar objects, stellar physics with star clusters, asteroseismology of solar-like oscillators and opacity-driven pulsators, studies of stellar rotation, activity, and multiplicity, as well as the chemical characterization of AGB and extremely metal-poor stars.

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arXiv2018

Spectral lines in the CaII triplet region for RAVE DR6 chemical abundance pipeline

The purpose of this research note is to present a reliable list of clean spectral lines in the Calcium Triplet region at medium resolution ~7500, for chemical abundance analysis, in the framework of the RAdial Velocity Experiment (RAVE). Such line lists present a general interest for on-going large spectroscopic survey, such as Gaia-RVS, 4MOST and WEAVE.

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arXiv2018

Dissecting stellar chemical abundance space with t-SNE

In the era of industrial Galactic astronomy and multi-object spectroscopic stellar surveys, the sample sizes and the number of available stellar chemical abundances have reached dimensions in which it has become difficult to process all the available information in an effective manner. In this paper we demonstrate the use of a dimensionality-reduction technique (t-distributed stochastic neighbour embedding; t-SNE) for analysing the stellar abundance-space distribution. While the non-parametric non-linear behaviour of this technique makes it difficult to estimate the significance of found abundance-space substructure, we show that our results depend little on parameter choices and are robust to abundance errors. By reanalysing the high-resolution high-signal-to-noise solar-neighbourhood HARPS-GTO sample with t-SNE, we find clearer chemical separations of the high- and low-[$α$/Fe] disc sequences, hints for multiple populations in the high-[$α$/Fe] population, and indications that the chemical evolution of the high-[$α$/Fe] metal-rich stars is connected with the super-metal-rich stars. We also identify a number of chemically peculiar stars, among them a high-confidence s-process-enhanced abundance-ratio pair (HD91345/HD126681) with very similar ages and $v_X$ and $v_Y$ velocities, which we suggest to have a common birth origin, possibly a dwarf galaxy. Our results demonstrate the potential of abundance-space t-SNE and similar methods for chemical-tagging studies with large spectroscopic surveys.

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