Future Spectroscopic Surveys Research Articles

High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z > 2, a region only covered so far by Lyman-α forest measurements. In this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83±3%, for a purity of the selected LBG sample of 90±2%. This would deliver a confirmed LBG density of ~ 620 deg-2 in the range 2.3 < z < 3.5 for a r-band limiting magnitude r < 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89±4% efficiency for 97±2% purity. This would provide a confirmed LBG density of ~ 470 deg-2 in the range 2.8 < z < 3.5 for a r-band limiting magnitude r < 24.5. A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b LBG = 3.3 ± 0.2 (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.

Effects of heterogeneous data sets and time-lag measurement techniques on cosmological parameter constraints from Mg ii and C iv reverberation-mapped quasar data

ABSTRACT Previously, we demonstrated that Mg ii and C iv reverberation-mapped quasars (RM QSOs) are standardizable and that the cosmological parameters inferred using the broad-line region radius–luminosity (R–L) relation are consistent with those determined from better-established cosmological probes. With more data expected from ongoing and future spectroscopic and photometric surveys, it is imperative to examine how new QSO data sets of varied quality, with their own specific luminosity and time-delay distributions, can be best used to determine more restrictive cosmological parameter constraints. In this study, we test the effect of adding 25 OzDES Mg ii RM QSOs as well as 25 lower quality SDSS RM C iv QSOs, which increases the previous sample of RM QSOs by $\sim 36{{\ \rm per\ cent}}$. Although cosmological parameter constraints become tighter for some cosmological models after adding these new QSOs, the new combined data sets have increased differences between R–L parameter values obtained in different cosmological models and thus a lower standardizability for the larger Mg ii + C iv compilation. Different time-delay methodologies, particularly the ICCF and CREAM methods used for inferring time delays of SDSS RM QSOs, slightly affect cosmological and R–L relation parameter values, however, the effect is negligible for (smaller) compilations of robust time-delay detections. Our analysis indicates that increasing the sample size is not sufficient for tightening cosmological constraints and a quality cut is necessary to obtain a standardizable RM QSO sample.

Reconstructing Lyα Fields from Low-resolution Hydrodynamical Simulations with Deep Learning

Hydrodynamical cosmological simulations are a powerful tool for accurately predicting the properties of the intergalactic medium (IGM) and for producing mock skies that can be compared against observational data. However, the need to resolve density fluctuation in the IGM puts a stringent requirement on the resolution of such simulations, which in turn limits the volumes that can be modeled, even on the most powerful supercomputers. In this work, we present a novel modeling method that combines physics-driven simulations with data-driven generative neural networks to produce outputs that are qualitatively and statistically close to the outputs of hydrodynamical simulations employing eight times higher resolution. We show that the Lyα flux field, as well as the underlying hydrodynamic fields, have greatly improved statistical fidelity over a low-resolution simulation. Importantly, the design of our neural network allows for sampling multiple realizations from a given input, enabling us to quantify the model uncertainty. Using test data, we demonstrate that this model uncertainty correlates well with the true error of the Lyα flux prediction. Ultimately, our approach allows for training on small simulation volumes and applying it to much larger ones, opening the door to producing accurate Lyα mock skies in volumes of Hubble size, as will be probed with DESI and future spectroscopic sky surveys.

The impact of supernova feedback on the mass–metallicity relations

ABSTRACT Metallicity is a fundamental physical property that strongly constrains galaxy formation and evolution. The formation of stars in galaxies is suppressed by the energy released from supernova explosions and can be enhanced by metal production. In order to understand the impact of this supernova feedback, we compare four different feedback methods, ejecting energy in thermal, kinetic, stochastic, and mechanical forms, into our self-consistent cosmological chemodynamical simulations. To minimize other uncertainties, we use the latest nucleosynthesis yields that can reproduce the observed elemental abundances of stars in the Milky Way. For each method, we predict the evolution of stellar and gas-phase metallicities as a function of galaxy mass, i.e. the mass–metallicity relations. We then find that the mechanical feedback can give the best match to a number of observations up to redshift z ∼ 3, although the predicted gas-phase metallicities seem to be higher than those observed at z ≳ 1. The feedback modelling can be further constrained by the metallicities in distant galaxies with the JWST and those of a large sample with ongoing and future spectroscopic surveys.

High-resolution Chemical Abundances of the Nyx Stream

Nyx is a nearby, prograde, and high-eccentricity stellar stream physically contained in the thick disk, but its origin is unknown. Nyx could be the remnant of a disrupted dwarf galaxy, in which case the associated dark matter substructure could affect terrestrial dark matter direct-detection experiments. Alternatively, Nyx could be a signature of the Milky Way’s disk formation and evolution. To determine the origin of Nyx, we obtained high-resolution spectroscopy of 34 Nyx stars using Keck/HIRES and Magellan/MIKE. A differential chemical abundance analysis shows that most Nyx stars reside in a metal-rich ([Fe/H] > −1) high-α component that is chemically indistinguishable from the thick disk. This rules out the originally suggested scenario that Nyx is the remnant of a single massive dwarf galaxy merger. However, we also identify 5 substantially more metal-poor stars ([Fe/H] ∼ −2.0) whose chemical abundances are similar to those of the metal-weak thick disk. It remains unclear how stars that are chemically identical to the thick disk can be on such prograde, high-eccentricity orbits. We suggest two most likely scenarios: that Nyx is the result of an early minor dwarf galaxy merger, or that it is a record of the early spin-up of the Milky Way disk—although neither perfectly reproduces the chemodynamic observations. The most likely formation scenarios suggest that future spectroscopic surveys should find Nyx-like structures outside of the solar neighborhood.

CN and CO features: key indicators of red giant evolutionary phase in moderate-resolution X-shooter spectra

ABSTRACT Data-driven analysis methods can help to infer physical properties of red giant stars where ‘gold-standard’ asteroseismic data are not available. The study of optical and infrared spectra of red giant stars with data-driven analyses has revealed that differences in oscillation frequencies and their separations are imprinted in said spectra. This makes it possible to confidently differentiate core helium burning red clump (RC) stars from those that are still on their first ascent of the red giant branch (RGB). We extend these studies to a tenfold larger wavelength range of 0.33–2.5 µm with the moderate-resolution VLT/X-shooter spectrograph. Our analysis of 49 stars with asteroseismic data from the K2 mission confirms that CN, CO, and CH features are indeed the primary carriers of spectroscopic information on the evolutionary stages of red giant stars. We report 215 informative features for differentiating the RC from the RGB within the range of 0.33–2.5 µm. This makes it possible for existing and future spectroscopic surveys to optimize their wavelength regions to deliver both a large variety of elemental abundances and reliable age estimates of luminous red giant stars.

Detailed α abundance trends in the inner Galactic bulge

Context. Until now, heavy interstellar extinction has meant that only a few studies of chemical abundances have been possible in the inner Galactic bulge. However, it is crucial to learn more about this structure in order to better understand the formation and evolution of the centre of the Galaxy and galaxies in general. Aims. In this paper, we aim to derive high-precision α-element abundances using CRIRES high-resolution IR spectra of 72 cool M giants of the inner Galactic bulge. Methods. Silicon, magnesium, and calcium abundances were determined by fitting a synthetic spectrum for each star. We also incorporated recent theoretical data into our spectroscopic analysis (i.e. updated K-band line list, better broadening parameter estimation, non-local thermodynamic equilibrium (NLTE) corrections). We compare these inner bulge α abundance trends with those of solar neighbourhood stars observed with IGRINS using the same line list and analysis technique; we also compare our sample to APOGEE DR17 abundances for inner bulge stars. We investigate bulge membership using spectro-photometric distances and orbital simulations. We construct a chemical-evolution model that fits our metallicity distribution function (MDF) and our α-element trends. Results. Among our 72 stars, we find four that are not bulge members. [Si/Fe] and [Mg/Fe] versus [Fe/H] trends show a typical thick disc α-element behaviour, except that we do not see any plateau at supersolar metallicities as seen in other works. The NLTE analysis lowers [Mg/Fe] typically by ∼0.1 dex, resulting in a noticeably lower trend of [Mg/Fe] versus [Fe/H]. The derived [Ca/Fe] versus [Fe/H] trend has a larger scatter than those for Si and Mg, but is in excellent agreement with local thin and thick disc trends. With our updated analysis, we constructed one of the most detailed studies of the α abundance trends of cool M giants in the inner Galactic bulge. We modelled these abundances by adopting a two-infall chemical-evolution model with two distinct gas-infall episodes with timescales of 0.4 Gyr and 2 Gyr, respectively. Conclusions. Based on a very meticulous spectral analysis, we have constructed detailed and precise chemical abundances of Mg, Si, and Ca for cool M giants. The present study can be used as a benchmark for future spectroscopic surveys.

TheGaia-ESO Survey: Preparing the ground for 4MOST and WEAVE galactic surveys

Context.With its origin coming from several sources (Big Bang, stars, cosmic rays) and given its strong depletion during its stellar lifetime, the lithium element is of great interest as its chemical evolution in the Milky Way is not well understood at present. To help constrain stellar and galactic chemical evolution models, numerous and precise lithium abundances are necessary for a large range of evolutionary stages, metallicities, and Galactic volume.Aims.In the age of stellar parametrization on industrial scales, spectroscopic surveys such as APOGEE, GALAH, RAVE, and LAMOST have used data-driven methods to rapidly and precisely infer stellar labels (atmospheric parameters and abundances). To prepare the ground for future spectroscopic surveys such as 4MOST and WEAVE, we aim to apply machine learning techniques to lithium measurements and analyses.Methods.We trained a convolution neural network (CNN), couplingGaia-ESO Survey iDR6 stellar labels (Teff, log(g), [Fe/H], and A(Li)) and GIRAFFE HR15N spectra, to infer the atmospheric parameters and lithium abundances for ∼40 000 stars. The CNN architecture and accompanying notebooks are available online via GitHub.Results.We show that the CNN properly learns the physics of the stellar labels, from relevant spectral features through a broad range of evolutionary stages and stellar parameters. The lithium feature at 6707.8 Å is successfully singled out by our CNN, among the thousands of lines in the GIRAFFE HR15N setup. Rare objects such as lithium-rich giants are found in our sample. This level of performance is achieved thanks to a meticulously built, high-quality, and homogeneous training sample.Conclusions.The CNN approach is very well adapted for the next generations of spectroscopic surveys aimed at studying (among other elements) lithium, such as the 4MIDABLE-LR/HR (4MOST Milky Way disk and bulge low- and high-resolution) surveys. In this context, the caveats of machine-learning applications should be appropriately investigated, along with the realistic label uncertainties and upper limits for abundances.

Deep ALMA redshift search of a z ∼ 12 GLASS-JWST galaxy candidate

ABSTRACT The JWST has discovered a surprising abundance of bright galaxy candidates in the very early universe (≤500 Myr after the Big Bang), calling into question current galaxy formation models. Spectroscopy is needed to confirm the primeval nature of these candidates, as well as to understand how the first galaxies form stars and grow. Here we present deep spectroscopic and continuum ALMA observations towards GHZ2/GLASS-z12, one of the brightest and most robust candidates at z &amp;gt; 10, identified in the GLASS-JWST Early Release Science Program. We detect a 5.8σ line, offset 0${_{.}^{\prime\prime}}$5 from the JWST position of GHZ2/GLASS-z12, that associating it with the [O iii] 88 $\mu {\rm m}$ transition, implies a spectroscopic redshift of z = 12.117 ± 0.001. We verify the detection using extensive statistical tests. The oxygen line luminosity places GHZ2/GLASS-z12 above the [O iii]-SFR relation for metal-poor galaxies, implying an enhancement of [O iii] emission in this system while the JWST-observed emission is likely a lower-metallicity region. The lack of dust emission seen by these observations is consistent with the blue UV slope observed by JWST, which suggest little dust attenuation in galaxies at this early epoch. Further observations will unambiguously confirm the redshift and shed light on the origins of the wide and offset line and physical properties of this early galaxy. This work illustrates the synergy between JWST and ALMA, and paves the way for future spectroscopic surveys of z &amp;gt; 10 galaxy candidates.

Redshift weighted galaxy number counts

In this paper we introduce the 'redshift fluctuation' as a gauge-invariant cosmological observable and give its fully relativistic expression at first order in cosmological perturbation theory. We show that this corresponds effectively to number counts with a radial window function with vanishing mean which therefore resolve smaller scale radial modes than standard number counts. In a detailed analysis of the angular power spectrum of this new variable, we study the relevance of different relativistic contributions, and how it differs from the conventional observable galaxy number count fluctuations. In order to investigate its utility for future spectroscopic surveys, we perform Fisher forecasts for a Euclid-like and an SKAII-like configuration, as examples. Particular focus is placed on the dependence of the results on the size of the redshift bins and on the cutoff in ℓ adopted in the analysis.

The Extended Tidal Tails of NGC 7089 (M2)

Using photometry and proper motions from Gaia Early Data Release 3, we detect a 45° long trailing stellar debris stream associated with the old, metal-poor globular cluster NGC 7089. With a width on the order of 100 pc, the extended stream appears to be as dynamically cold as the coldest known streams found to date. There is some evidence for an extended leading tail extending between 28° and 37° from the cluster, though the greater distance of this tail, combined with proper motions that are virtually indistinguishable from those of foreground stars, make the detection much less certain. The proper motion profile and the path on the sky of the trailing tail are not well matched using a simple Galactic potential composed purely of a disk, bulge, and spherical halo. However, the addition of a moving, massive (M = 1.88 × 1011 M ⊙) Large Magellanic Cloud brings the model predictions into much better agreement with the observables. We provide tables of the most highly ranked candidate stream stars for follow-up by ongoing and future spectroscopic surveys.

Snails across Scales: Local and Global Phase-mixing Structures as Probes of the Past and Future Milky Way

Abstract Signatures of vertical disequilibrium have been observed across the Milky Way’s (MW’s) disk. These signatures manifest locally as unmixed phase spirals in z–v z space (“snails-in-phase”), and globally as nonzero mean z and v z , wrapping around the disk into physical spirals in the x–y plane (“snails-in-space”). We explore the connection between these local and global spirals through the example of a satellite perturbing a test-particle MW-like disk. We anticipate our results to broadly apply to any vertical perturbation. Using a z–v z asymmetry metric, we demonstrate that in test-particle simulations: (a) multiple local phase-spiral morphologies appear when stars are binned by azimuthal action J ϕ , excited by a single event (in our case, a satellite disk crossing); (b) these distinct phase spirals are traced back to distinct disk locations; and (c) they are excited at distinct times. Thus, local phase spirals offer a global view of the MW’s perturbation history from multiple perspectives. Using a toy model for a Sagittarius (Sgr)–like satellite crossing the disk, we show that the full interaction takes place on timescales comparable to orbital periods of disk stars within R ≲ 10 kpc. Hence such perturbations have widespread influence, which peaks in distinct regions of the disk at different times. This leads us to examine the ongoing MW–Sgr interaction. While Sgr has not yet crossed the disk (currently, z Sgr ≈ −6 kpc, v z,Sgr ≈ 210 km s−1), we demonstrate that the peak of the impact has already passed. Sgr’s pull over the past 150 Myr creates a global v z signature with amplitude ∝ M Sgr, which might be detectable in future spectroscopic surveys.

Toward a Better Understanding of Cosmic Chronometers: A New Measurement of H(z) at z ∼ 0.7

Abstract We analyze the stellar ages obtained from a combination of Lick indices in Borghi et al. for 140 massive and passive galaxies selected in the LEGA-C survey at 0.6 &lt; z &lt; 0.9. From their median age–redshift relation, we derive a new direct measurement of H(z) without any cosmological model assumption using the cosmic chronometer approach. We thoroughly study the main systematics involved in this analysis: the choice of the Lick indices combination, the binning method, the assumed stellar population model, and the adopted star formation history; these effects are included in the total error budget. We obtain H(z = 0.75) = 98.8 ± 33.6 km s−1 Mpc−1. In parallel, we also propose a simple framework based on a cosmological model to describe the age–redshift relations in the context of galaxy downsizing. This allows us to derive constraints on the Hubble constant H 0 and the typical galaxy formation time. This new H(z) measurement, whose accuracy is currently limited by the scarcity of the sample analyzed, paves the road for the joint study of the stellar populations of individual passive galaxies and the expansion history of the universe in light of future spectroscopic surveys.

Cosmology at high redshift — a probe of fundamental physics

An observational program focused on the high redshift (2<z<6) Universe has the opportunity to dramatically improve over upcoming LSS and CMB surveys on measurements of both the standard cosmological model and its extensions. Using a Fisher matrix formalism that builds upon recent advances in Lagrangian perturbation theory, we forecast constraints for future spectroscopic and 21-cm surveys on the standard cosmological model, curvature, neutrino mass, relativistic species, primordial features, primordial non-Gaussianity, dynamical dark energy, and gravitational slip. We compare these constraints with those achievable by current or near-future surveys such as DESI and Euclid, all under the same forecasting formalism, and compare our formalism with traditional linear methods. Our Python code FishLSS — used to calculate the Fisher information of the full shape power spectrum, CMB lensing, the cross-correlation of CMB lensing with galaxies, and combinations thereof — is publicly available.

Joint analyses of 2D CMB lensing and 3D galaxy clustering in the spherical Fourier-Bessel basis

Cross-correlating cosmic microwave background (CMB) lensing and galaxy clustering has been shown to greatly improve the constraints on the local primordial non-Gaussianity (PNG) parameter $f_{\rm NL}$ by reducing sample variance and also parameter degeneracies. To model the full use of the 3D information of galaxy clustering, we forecast $f_{\rm NL}$ measurements using the decomposition in the spherical Fourier-Bessel (SFB) basis, which can be naturally cross-correlated with 2D CMB lensing in spherical harmonics. In the meantime, such a decomposition would also enable us to constrain the growth rate of structure, a probe of gravity, through the redshift-space distortion (RSD). As a comparison, we also consider the tomographic spherical harmonic (TSH) analysis of galaxy samples with different bin sizes. Assuming galaxy samples that mimic a few future surveys, we perform Fisher forecasts using linear modes for $f_{\rm NL}$ and the growth rate exponent $\gamma$, marginalized over standard $\Lambda$ cold dark matter ($\Lambda$CDM) cosmological parameters and two nuisance parameters that account for clustering bias and magnification bias. Compared to TSH analysis using only one bin, SFB analysis could improve $\sigma(f_{\rm NL})$ by factors 3 to 12 thanks to large radial modes. With future wide-field and high-redshift photometric surveys like the LSST, the constraint $\sigma(f_{\rm NL}) < 1$ could be achieved using linear angular multipoles up to $\ell_{\rm min}\simeq 20$. Compared to using galaxy auto-power spectra only, joint analyses with CMB lensing could improve $\sigma(\gamma)$ by factors 2 to 5 by reducing degeneracies with other parameters, especially the clustering bias. For future spectroscopic surveys like the DESI or $\textit{Euclid}$, using linear scales, $\gamma$ could be constrained to $3\,\%$ precision assuming the GR fiducial value.

Mapping the cosmic mass distribution with stacked weak gravitational lensing and Doppler lensing

ABSTRACT Dark matter haloes represent the highest density peaks in the matter distribution. Conversely, cosmic voids are underdense patches of the universe. Probing the mass distribution of the universe requires various approaches, including weak gravitational lensing that subtly modifies the shape of distant sources, and Doppler lensing that changes the apparent size and magnitude of objects due to peculiar velocities. In this work, we adopt both gravitational and Doppler lensing effects to study the underlying matter distribution in and around cosmic voids or haloes. We use the relativistic N-body code gevolution, to generate the mass perturbations and develop a new ray-tracing code that relies on the design of the ray bundle method. We consider three categories of halo masses and void radii, and extract the cosmological information by stacking weak-lensing and Doppler lensing signals around voids or haloes. The results of this paper show that the most optimal strategy that combines both gravitational and Doppler lensing effects to map the mass distribution should focus on the redshift range z ≈ 0.3−0.4. The recommendation of this paper is that future spectroscopic surveys should focus on these redshifts and utilize the gravitational and Doppler lensing techniques to extract information about underlying matter distribution across the cosmic web, especially inside cosmic voids. This could provide a complimentary cosmological analysis for ongoing or future low-redshift spectroscopic surveys.

On the AGN nature of broad balmer emission in four low-redshift metal-poor galaxies

ABSTRACT We report on continued, ∼15-yr long, broad Balmer emission lines in three metal-poor dwarf emission-line galaxies selected from Sloan Digital Sky Survey spectroscopy. The persistent luminosity of the broad Balmer emission indicates the galaxies are active galactic nuclei (AGNs) with virial black hole masses of ∼106.7–107.0 M⊙. The lack of observed hard X-ray emission and the possibility that the Balmer emission could be due to a long-lived stellar transient motivated additional follow-up spectroscopy. We also identify a previously unreported blueshifted narrow absorption line in the broad H α feature in one of the AGNs, indicating an AGN-driven outflow with hydrogen column densities of order 1017 cm−2. We also extract light curves from the Catalina Real-Time Transient Survey and the Zwicky Transient Facility. We detect probable AGN-like variability in three galaxies, further supporting the AGN scenario. This also suggests the AGNs are not strongly obscured. This sample of galaxies are among the most metal-poor that host an AGN (Z = 0.05–0.16 Z⊙). We speculate they may be analogues to seed black holes which formed in unevolved galaxies at high redshift. Given the rarity of metal-poor AGNs and small sample size available, we investigate prospects for their identification in future spectroscopic and photometric surveys.

Cosmic filaments in galaxy cluster outskirts: quantifying finding filaments in redshift space

ABSTRACT Inferring line-of-sight distances from redshifts in and around galaxy clusters is complicated by peculiar velocities, a phenomenon known as the ‘Fingers of God’ (FoG). This presents a significant challenge for finding filaments in large observational data sets as these artificial elongations can be wrongly identified as cosmic web filaments by extraction algorithms. Upcoming targeted wide-field spectroscopic surveys of galaxy clusters and their infall regions, such as the WEAVE Wide-Field Cluster Survey, motivate our investigation of the impact of FoG on finding filaments connected to clusters. Using zoom-in resimulations of 324 massive galaxy clusters and their outskirts from the three hundred project, we test methods typically applied to large-scale spectroscopic data sets. This paper describes our investigation of whether a statistical compression of the FoG of cluster centres and galaxy groups can lead to correct filament extractions in the cluster outskirts. We find that within 5R200 (∼15 h−1 Mpc) statistically correcting for FoG elongations of virialized regions does not achieve reliable filament networks compared to reference filament networks based on true positions. This is due to the complex flowing motions of galaxies towards filaments in addition to the cluster infall, which overwhelm the signal of the filaments relative to the volume that we probe. While information from spectroscopic redshifts is still important to isolate the cluster regions, and thereby reduce background and foreground interlopers, we expect future spectroscopic surveys of galaxy cluster outskirts to rely on 2D positions of galaxies to extract cosmic filaments.

Blinded challenge for precision cosmology with large-scale structure: Results from effective field theory for the redshift-space galaxy power spectrum

An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.

The RAdial Velocity Experiment (RAVE): Parameterisation of RAVE spectra based on convolutional neural networks

Context. Data-driven methods play an increasingly important role in the field of astrophysics. In the context of large spectroscopic surveys of stars, data-driven methods are key in deducing physical parameters for millions of spectra in a short time. Convolutional neural networks (CNNs) enable us to connect observables (e.g. spectra, stellar magnitudes) to physical properties (atmospheric parameters, chemical abundances, or labels in general). Aims. We test whether it is possible to transfer the labels derived from a high-resolution stellar survey to intermediate-resolution spectra of another survey by using a CNN. Methods. We trained a CNN, adopting stellar atmospheric parameters and chemical abundances from APOGEE DR16 (resolution R = 22 500) data as training set labels. As input, we used parts of the intermediate-resolution RAVE DR6 spectra (R ∼ 7500) overlapping with the APOGEE DR16 data as well as broad-band ALL_WISE and 2MASS photometry, together with Gaia DR2 photometry and parallaxes. Results. We derived precise atmospheric parameters Teff, log(g), and [M/H], along with the chemical abundances of [Fe/H], [α/M], [Mg/Fe], [Si/Fe], [Al/Fe], and [Ni/Fe] for 420 165 RAVE spectra. The precision typically amounts to 60 K in Teff, 0.06 in log(g) and 0.02−0.04 dex for individual chemical abundances. Incorporating photometry and astrometry as additional constraints substantially improves the results in terms of the accuracy and precision of the derived labels, as long as we operate in those parts of the parameter space that are well-covered by the training sample. Scientific validation confirms the robustness of the CNN results. We provide a catalogue of CNN-trained atmospheric parameters and abundances along with their uncertainties for 420 165 stars in the RAVE survey. Conclusions. CNN-based methods provide a powerful way to combine spectroscopic, photometric, and astrometric data without the need to apply any priors in the form of stellar evolutionary models. The developed procedure can extend the scientific output of RAVE spectra beyond DR6 to ongoing and planned surveys such as Gaia RVS, 4MOST, and WEAVE. We call on the community to place a particular collective emphasis and on efforts to create unbiased training samples for such future spectroscopic surveys.