Using a sample of 69,919 red giants from the SDSS-III/APOGEE Data Release 12, we measure the distribution of stars in the [α/Fe] versus [Fe/H] plane and the metallicity distribution functions (MDFs) across an unprecedented volume of the Milky Way disk, with radius 3 < R < 15 kpc and height kpc. Stars in the inner disk (R < 5 kpc) lie along a single track in [α/Fe] versus [Fe/H], starting with α-enhanced, metal-poor stars and ending at [α/Fe] ∼ 0 and [Fe/H] ∼ +0.4. At larger radii we find two distinct sequences in [α/Fe] versus [Fe/H] space, with a roughly solar-α sequence that spans a decade in metallicity and a high-α sequence that merges with the low-α sequence at super-solar [Fe/H]. The location of the high-α sequence is nearly constant across the disk; however, there are very few high-α stars at R > 11 kpc. The peak of the midplane MDF shifts to lower metallicity at larger R, reflecting the Galactic metallicity gradient. Most strikingly, the shape of the midplane MDF changes systematically with radius, from a negatively skewed distribution at 3 < R < 7 kpc, to a roughly Gaussian distribution at the solar annulus, to a positively skewed shape in the outer Galaxy. For stars with kpc or [α/Fe] > 0.18, the MDF shows little dependence on R. The positive skewness of the outer-disk MDF may be a signature of radial migration; we show that blurring of stellar populations by orbital eccentricities is not enough to explain the reversal of MDF shape, but a simple model of radial migration can do so.
The MaNGA Survey (Mapping Nearby Galaxies at Apache Point Observatory) is one of three core programs in the Sloan Digital Sky Survey IV. It is obtaining integral field spectroscopy (IFS) for 10K nearby galaxies at a spectral resolution of R~2000 from 3,622-10,354A. The design of the survey is driven by a set of science requirements on the precision of estimates of the following properties: star formation rate surface density, gas metallicity, stellar population age, metallicity, and abundance ratio, and their gradients; stellar and gas kinematics; and enclosed gravitational mass as a function of radius. We describe how these science requirements set the depth of the observations and dictate sample selection. The majority of targeted galaxies are selected to ensure uniform spatial coverage in units of effective radius (Re) while maximizing spatial resolution. About 2/3 of the sample is covered out to 1.5Re (Primary sample), and 1/3 of the sample is covered to 2.5Re (Secondary sample). We describe the survey execution with details that would be useful in the design of similar future surveys. We also present statistics on the achieved data quality, specifically, the point spread function, sampling uniformity, spectral resolution, sky subtraction, and flux calibration. For our Primary sample, the median r-band signal-to-noise ratio is ~73 per 1.4A pixel for spectra stacked between 1-1.5 Re. Measurements of various galaxy properties from the first year data show that we are meeting or exceeding the defined requirements for the majority of our science goals.
We utilize $\sim17000$ bright Luminous Red Galaxies (LRGs) from the novel Dark Energy Spectroscopic Instrument Survey Validation spectroscopic sample, leveraging its deep ($\sim2.5$ hour/galaxy exposure time) spectra to characterize the contribution of recently quenched galaxies to the massive galaxy population at $0.41$) of our sample of recently quenched galaxies represents the largest spectroscopic sample of post-starburst galaxies at that epoch. At $0.411.2$) LRGs by measuring the fraction of stellar mass each galaxy formed in the Gyr before observation, $f_\mathrm{1 Gyr}$. Although galaxies with $f_\mathrm{1 Gyr}>0.1$ are rare at $z\sim0.4$ ($\lesssim 0.5\%$ of the population), by $z\sim0.8$ they constitute $\sim3\%$ of massive galaxies. Relaxing this threshold, we find that galaxies with $f_\mathrm{1 Gyr}>5\%$ constitute $\sim10\%$ of the massive galaxy population at $z\sim0.8$. We also identify a small but significant sample of galaxies at $z=1.1-1.3$ that formed with $f_\mathrm{1 Gyr}>50\%$, implying that they may be analogues to high-redshift quiescent galaxies that formed on similar timescales. Future analysis of this unprecedented sample promises to illuminate the physical mechanisms that drive the quenching of massive galaxies after cosmic noon.
Candidate cluster-scale strongly-lensed quasars from DESI Legacy Survey (DESI QSO targets) and CluMPR DESI Legacy Survey galaxy cluster catalog. Paper decribing the CluMPR galaxy cluster catalogs and candidate lensed quasar catalogs: The CluMPR Galaxy Cluster-Finding Algorithm and DESI Legacy Survey Galaxy Cluster catalogue (M. J. Yantovski-Barth et al.) Description: To search for lensed quasars, we use two Einstein radii: one corresponds to wide angle lensing by the entire cluster (𝑀 = 10^15 𝑀⊙ ), and the other corresponds to lensing by the core of the cluster (𝑀 = 0.25 ∗ 10^15 𝑀⊙ ). We use the colors in bands g-r, g-z, and r-W1 to evaluate candidate lensed quasars. If at least two quasars are within 1 magnitude of each other in all 3 colors, we rate the candidate at Grade C. If at least three quasars are within 1 magnitude of each other in all 3 colors, we rate the the candidate at Grade B. If either 4 quasars or two combinations of 3 quasars are within 1 magnitude of each other in all 3 colors, we rate the candidate as Grade A.
We present Keck/MOSFIRE K-band spectroscopy of the first mass-selected sample of galaxies at $z\sim2.3$. Targets are selected from the 3D-HST Treasury survey. The six detected galaxies have a mean [NII]$\lambda$6584/H$\alpha$ ratio of $0.27\pm0.01$, with a small standard deviation of 0.05. This mean value is similar to that of UV-selected galaxies of the same mass. The mean gas-phase oxygen abundance inferred from the [NII]/H$\alpha$ ratios depends on the calibration method, and ranges from 12+log(O/H)$_{gas}=8.57$ for the {Pettini} & {Pagel} (2004) calibration to 12+log(O/H)$_{gas}= 8.87$ for the {Maiolino} {et~al.} (2008) calibration. Measurements of the stellar oxygen abundance in nearby quiescent galaxies with the same number density indicate 12+log(O/H)$_{stars}= 8.95$, similar to the gas-phase abundances of the $z\sim2.3$ galaxies if the {Maiolino} {et~al.} (2008) calibration is used. This suggests that these high-redshift star forming galaxies may be progenitors of today's massive early-type galaxies. The main uncertainties are the absolute calibration of the gas-phase oxygen abundance and the incompleteness of the $z\sim2.3$ sample: the galaxies with detected H$\alpha$ tend to be larger and have higher star formation rates than the galaxies without detected H$\alpha$, and we may still be missing the most dust-obscured progenitors.
ABSTRACT We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H α, H β, [O ii], and [O iii]) from a galaxy’s rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman’s rank correlation coefficient ρs > 0.87 between predictions and observations for most lines. Using a non-linear dimensionality reduction technique, we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterize and account for biases in the spectroscopic training sets used for training and calibration of photo-z’s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.
Post-starburst galaxies (PSBs) are young quiescent galaxies that have recently experienced a rapid decrease in star formation, allowing us to probe the fast-quenching period of galaxy evolution. In this work, we obtained HST WFC3/F110W imaging to measure the sizes of 171 massive ($\mathrm{log(M_{*}/M_{\odot})\sim\,11)}$ spectroscopically identified PSBs at $1
Abstract A galaxy’s stellar mass is one of its most fundamental properties, but it remains challenging to measure reliably. With the advent of very large optical spectroscopic surveys, efficient methods that can make use of low signal-to-noise spectra are needed. With this in mind, we created a new software package for estimating effective stellar mass-to-light ratios that uses a principal component analysis (PCA) basis set to optimize the comparison between observed spectra and a large library of stellar population synthesis models. In Paper I, we showed that with a set of six PCA basis vectors we could faithfully represent most optical spectra from the Mapping Nearby Galaxies at APO (MaNGA) survey, and we tested the accuracy of our M/L estimates using synthetic spectra. Here, we explore sources of systematic error in our mass measurements by comparing our new measurements to data from the literature. We compare our stellar mass surface density estimates to kinematics-derived dynamical mass surface density measurements from the DiskMass Survey and find some tension between the two that could be resolved if the disk scale heights used in the kinematic analysis were overestimated by a factor of ∼1.5. We formulate an aperture-corrected stellar mass catalog for the MaNGA survey, and compare to previous stellar mass estimates based on multiband optical photometry, finding typical discrepancies of 0.1 dex. Using the spatially resolved MaNGA data, we evaluate the impact of estimating total stellar masses from spatially unresolved spectra, and we explore how the biases that result from unresolved spectra depend upon the galaxy’s dust extinction and star formation rate. Finally, we describe an SDSS Value-Added Catalog that will include both spatially resolved and total (aperture-corrected) stellar masses for MaNGA galaxies.