Detecting neutral hydrogen at z > 3 in large spectroscopic surveys of quasars

We present a pipeline based on a random forest classifier for the identification of high column-density clouds of neutral hydrogen (i.e. the Lyman limit systems, LLSs) in absorption within large spectroscopic surveys of z>3 quasars. We test the performance of this method on mock quasar spectra that reproduce the expected data quality of the Dark Energy Spectroscopic Instrument (DESI) and the WHT Enhanced Area Velocity Explorer (WEAVE) surveys, finding >90% completeness and purity for N(HI)> 10^17.2 cm^-2 LLSs against quasars of g < 23 mag at z~3.5-3.7. After training and applying our method on 10,000 quasar spectra at z~3.5-4.0 from the Sloan Digital Sky Survey (Data Release 16), we identify ~6600 LLSs with N(HI)>10^17.5 cm^-2 between z~3.1-4.0 with a completeness and purity of >90% for the classification of LLSs. Using this sample, we measure a number of LLSs per unit redshift of 2.32 +/- 0.08 at z=[3.3,3.6]. We also present results on the performance of random forest for the measurement of the LLS redshifts and HI column densities, and for the identification of broad absorption line quasars.

PhotoWeb redshift: boosting photometric redshift accuracy with large spectroscopic surveys

Improving distance measurements in large imaging surveys is a major challenge to better reveal the distribution of galaxies on a large scale and to link galaxy properties with their environments. Photometric redshifts can be efficiently combined with the cosmic web (CW) extracted from overlapping spectroscopic surveys to improve their accuracy. We apply a similar method using a new generation of photometric redshifts based on a convolution neural network (CNN). The CNN is trained on the SDSS images with the main galaxy sample (SDSS-MGS, $r leq 17.8$) and the GAMA spectroscopic redshifts up tor $sim 19.8$. The mapping of the CW is obtained with 680,000 spectroscopic redshifts from the MGS and BOSS surveys. The redshift probability distribution functions (PDF), which are well calibrated (unbiased and narrow, $leq 120$ Mpc), intercept a few CW structure along the line of sight. Combining these PDFs with the density field distribution provides new photometric redshifts, $z_{web}$, whose accuracy is improved by a factor of two (i.e.,${sigma} sim 0.004(1+z)$) for galaxies with $r leq 17.8$. For half of them, the distance accuracy is better than 10 cMpc. The narrower the original PDF, the larger the boost in accuracy. No gain is observed for original PDFs wider than 0.03. The final $z_{web}$ PDFs also appear well calibrated. The method performs slightly better for passive galaxies than star-forming ones, and for galaxies in massive groups since these populations better trace the underlying large-scale structure. Reducing the spectroscopic sampling by a factor of 8 still improves the photometric redshift accuracy by 25%. Extending the method to galaxies fainter than the MGS limit still improves the redshift estimates for 70% of the galaxies, with a gain in accuracy of 20% at low $z$ where the resolution of the CW is the highest.

The GALAH Survey: Non-LTE departure coefficients for large spectroscopic surveys

Massive sets of stellar spectroscopic observations are rapidly becoming available and these can be used to determine the chemical composition and evolution of the Galaxy with unprecedented precision. One of the major challenges in this endeavour involves constructing realistic models of stellar spectra with which to reliably determine stellar abundances. At present, large stellar surveys commonly use simplified models that assume that the stellar atmospheres are approximately in local thermodynamic equilibrium (LTE). To test and ultimately relax this assumption, we have performed non-LTE calculations for $13$ different elements (H, Li, C, N, O, Na, Mg, Al, Si, K, Ca, Mn, and Ba), using recent model atoms that have physically-motivated descriptions for the inelastic collisions with neutral hydrogen, across a grid of $3756$ 1D MARCS model atmospheres that spans $3000leq T_{mathrm{eff}}/mathrm{K}leq8000$, $-0.5leqlog{g/mathrm{cm,s^{-2}}}leq5.5$, and $-5leqmathrm{[Fe/H]}leq1$. We present the grids of departure coefficients that have been implemented into the GALAH DR3 analysis pipeline in order to complement the extant non-LTE grid for iron. We also present a detailed line-by-line re-analysis of $50126$ stars from GALAH DR3. We found that relaxing LTE can change the abundances by between $-0.7,mathrm{dex}$ and $+0.2,mathrm{dex}$ for different lines and stars. Taking departures from LTE into account can reduce the dispersion in the $mathrm{[A/Fe]}$ versus $mathrm{[Fe/H]}$ plane by up to $0.1,mathrm{dex}$, and it can remove spurious differences between the dwarfs and giants by up to $0.2,mathrm{dex}$. The resulting abundance slopes can thus be qualitatively different in non-LTE, possibly with important implications for the chemical evolution of our Galaxy.

Unbiased large spectroscopic surveys of galaxies selected by SPICA using dust bands

The mid-infrared (IR) range contains many spectral features associated with large molecules and dust grains such as polycyclic aromatic hydrocarbons (PAHs) and silicates. These are usually very strong compared to fine-structure gas lines, and thus valuable in studying the spectral properties of faint distant galaxies. In this paper, we evaluate the capability of low-resolution mid-IR spectroscopic surveys of galaxies that could be performed by SPICA. The surveys are designed to address the question how star formation and black hole accretion activities evolved over cosmic time through spectral diagnostics of the physical conditions of the interstellar/circumnuclear media in galaxies. On the basis of results obtained with Herschel far-IR photometric surveys of distant galaxies and Spitzer and AKARI near- to mid-IR spectroscopic observations of nearby galaxies, we estimate the numbers of the galaxies at redshift z > 0.5, which are expected to be detected in the PAH features or dust continuum by a wide (10 deg^2) or deep (1 deg^2) blind survey, both for a given observation time of 600 hours. As by-products of the wide blind survey, we also expect to detect debris disks, through the mid-IR excess above the photospheric emission of nearby main-sequence stars, and we estimate their number. We demonstrate that the SPICA mid-IR surveys will efficiently provide us with unprecedentedly large spectral samples, which can be studied further in the far-IR with SPICA.

A Blueprint for the Milky Ways Stellar Populations: The Power of Large Photometric and Astrometric Surveys

Recent advances from astronomical surveys have revealed spatial, chemical, and kinematical inhomogeneities in the inner region of the stellar halo of the Milky Way Galaxy. In particular, large spectroscopic surveys, combined with Gaia astrometric data, have provided powerful tools for analyzing the detailed abundances and accurate kinematics for individual stars. Despite these noteworthy efforts, however, spectroscopic samples are typically limited by the numbers of stars considered; their analysis and interpretation are also hampered by the complex selection functions that are often employed. Here we present a powerful alternative approach $-$ a synoptic view of the spatial, chemical, and kinematical distributions of stars in the Milky Way based on large photometric survey databases, enabled by a well-calibrated technique for obtaining individual stellar metal abundances from broad-band photometry. We combine metallicities with accurate proper motions from the Gaia mission along the Prime Meridian of the Galaxy, and find that various stellar components are clearly separated from each other in the metallicity versus rotation-velocity space. The observed metallicity distribution of the inner-halo stars deviates from the traditional single-peaked distribution, and exhibits complex substructures comprising varying contributions from individual stellar populations, sometimes with striking double peaks at low metallicities. The substructures revealed from our less-biased, comprehensive maps demonstrate the clear advantages of this approach, which can be built upon by future mixed-band and broad-band photometric surveys, and used as a blueprint for identifying the stars of greatest interest for upcoming spectroscopic studies.