Sloan Digital Sky Survey Survey Research Articles

StellarGAN: Classifying Stellar Spectra with Generative Adversarial Networks in SDSS and APOGEE Sky Surveys

Extracting precise stellar labels is crucial for large spectroscopic surveys like the Sloan Digital Sky Survey (SDSS) and APOGEE. In this paper, we report the newest implementation of StellarGAN, a data-driven method based on generative adversarial networks (GANs). Using 1D operators like convolution, the 2D GAN is modified into StellarGAN. This allows it to learn the relevant features of 1D stellar spectra without needing labels for specific stellar types. We test the performance of StellarGAN on different stellar spectra trained on SDSS and APOGEE data sets. Our result reveals that StellarGAN attains the highest overall F1-score on SDSS data sets (F1-score = 0.82, 0.77, 0.74, 0.53, 0.51, 0.61, and 0.55, for O-type, B-type, A-type, F-type, G-type, K-type, and M-type stars) when the signal-to-noise ratio (S/N) is low (90% of the spectra have an S/N < 50), with 1% of labeled spectra used for training. Using 50% of the labeled spectral data for training, StellarGAN consistently demonstrates performance that surpasses or is comparable to that of other data-driven models, as evidenced by the F1-scores of 0.92, 0.77, 0.77, 0.84, 0.84, 0.80, and 0.67. In the case of APOGEE (90% of the spectra have an S/N < 500), our method is also superior regarding its comprehensive performance (F1-score = 0.53, 0.60, 0.56, 0.56, and 0.78 for A-type, F-type, G-type, K-type, and M-type stars) with 1% of labeled spectra for training, manifesting its learning ability out of a limited number of labeled spectra. Our proposed method is also applicable to other types of data that need to be classified (such as gravitational-wave signals, light curves, etc.).

Identifying Symbiotic Stars with Machine Learning

Symbiotic stars are interacting binary systems, making them valuable for studying various astronomical phenomena, such as stellar evolution, mass transfer, and accretion processes. Despite recent progress in the discovery of symbiotic stars, a significant discrepancy between the observed population of symbiotic stars and the number predicted by theoretical models. To bridge this gap, this study utilized machine learning techniques to efficiently identify new symbiotic star candidates. Three algorithms (XGBoost, LightGBM, and Decision Tree) were applied to a data set of 198 confirmed symbiotic stars and the resulting model was then used to analyze data from the LAMOST survey, leading to the identification of 11,709 potential symbiotic star candidates. Out of these potential symbiotic star candidates listed in the catalog, 15 have spectra available in the Sloan Digital Sky Survey (SDSS) survey. Among these 15 candidates, two candidates, namely V* V603 Ori and V* GN Tau, have been confirmed as symbiotic stars. The remaining 11 candidates have been classified as accreting-only symbiotic star candidates. The other two candidates, one of which has been identified as a galaxy by both SDSS and LAMOST surveys, and the other identified as a quasar by SDSS survey and as a galaxy by LAMOST survey.

Automated algorithms to build active galactic nucleus classifiers

ABSTRACT We present a machine learning model to classify active galactic nuclei (AGNs) and galaxies (AGN-galaxy classifier) and a model to identify type 1 (optically unabsorbed) and type 2 (optically absorbed) AGN (type 1/2 classifier). We test tree-based algorithms, using training samples built from the X-ray Multi-Mirror Mission–Newton (XMM–Newton) catalogue and the Sloan Digital Sky Survey (SDSS), with labels derived from the SDSS survey. The performance was tested making use of simulations and of cross-validation techniques. With a set of features including spectroscopic redshifts and X-ray parameters connected to source properties (e.g. fluxes and extension), as well as features related to X-ray instrumental conditions, the precision and recall for AGN identification are 94 and 93 per cent, while the type 1/2 classifier has a precision of 74 per cent and a recall of 80 per cent for type 2 AGNs. The performance obtained with photometric redshifts is very similar to that achieved with spectroscopic redshifts in both test cases, while there is a decrease in performance when excluding redshifts. Our machine learning model trained on X-ray features can accurately identify AGN in extragalactic surveys. The type 1/2 classifier has a valuable performance for type 2 AGNs, but its ability to generalize without redshifts is hampered by the limited census of absorbed AGN at high redshift.

Connecting Optical Morphology, Environment, and H i Mass Fraction for Low-redshift Galaxies Using Deep Learning

Abstract A galaxy’s morphological features encode details about its gas content, star formation history, and feedback processes, which play important roles in regulating its growth and evolution. We use deep convolutional neural networks (CNNs) to learn a galaxy’s optical morphological information in order to estimate its neutral atomic hydrogen (H i) content directly from Sloan Digital Sky Survey (SDSS) gri image cutouts. We are able to accurately predict a galaxy’s logarithmic H i mass fraction, , by training a CNN on galaxies in the Arecibo Legacy Fast ALFA Survey (ALFALFA) 40% sample. Using pattern recognition, we remove galaxies with unreliable estimates. We test CNN predictions on the ALFALFA 100%, extended Galaxy Evolution Explorer Arecibo SDSS Survey, and Nançay Interstellar Baryons Legacy Extragalactic Survey catalogs, and find that the CNN consistently outperforms previous estimators. The H i–morphology connection learned by the CNN appears to be constant in low- to intermediate-density galaxy environments, but it breaks down in the highest-density environments. We also use a visualization algorithm, Gradient-weighted Class Activation Maps, to determine which morphological features are associated with low or high gas content. These results demonstrate that CNNs are powerful tools for understanding the connections between optical morphology and other properties, as well as for probing other variables, in a quantitative and interpretable manner.

Deep learning at scale for the construction of galaxy catalogs in the Dark Energy Survey

The scale of ongoing and future electromagnetic surveys pose formidable challenges to classify astronomical objects. Pioneering efforts on this front include citizen science campaigns adopted by the Sloan Digital Sky Survey (SDSS). SDSS datasets have been recently used to train neural network models to classify galaxies in the Dark Energy Survey (DES) that overlap the footprint of both surveys. Herein, we demonstrate that knowledge from deep learning algorithms, pre-trained with real-object images, can be transferred to classify galaxies that overlap both SDSS and DES surveys, achieving state-of-the-art accuracy ≳99.6%. We demonstrate that this process can be completed within just eight minutes using distributed training. While this represents a significant step towards the classification of DES galaxies that overlap previous surveys, we need to initiate the characterization of unlabelled DES galaxies in new regions of parameter space. To accelerate this program, we use our neural network classifier to label over ten thousand unlabelled DES galaxies, which do not overlap previous surveys. Furthermore, we use our neural network model as a feature extractor for unsupervised clustering and find that unlabelled DES images can be grouped together in two distinct galaxy classes based on their morphology, which provides a heuristic check that the learning is successfully transferred to the classification of unlabelled DES images. We conclude by showing that these newly labelled datasets can be combined with unsupervised recursive training to create large-scale DES galaxy catalogs in preparation for the Large Synoptic Survey Telescope era.

ELUCID. VI. Cosmic Variance of the Galaxy Distribution in the Local Universe

Halo merger trees are constructed from ELUCID, a constrained $N$-body simulation in the Sloan Digital Sky Survey (SDSS) volume. These merger trees are used to populate dark matter halos with galaxies according to an empirical model of galaxy formation. Mock catalogs in the SDSS sky coverage are constructed, which can be used to study the spatial distribution of galaxies in the low-$z$ Universe. These mock catalogs are used to quantify the cosmic variance in the galaxy stellar mass function (GSMF) measured from the SDSS survey. The GSMF estimated from the SDSS magnitude-limited sample can be affected significantly by the presence of the under-dense region at $z<0.03$, so that the low-mass end of the function can be underestimated significantly. Several existing methods designed to deal with the effects of the cosmic variance in the estimate of GSMF are tested, and none is found to be able to fully account for the cosmic variance. We propose a method based on the conditional stellar mass functions in dark matter halos, which can provide an unbiased estimate of the global GSMF. The application of the method to the SDSS data shows that the GSMF has a significant upturn at $M_*< 10^{9.5} h^{-1}{\rm M}_\odot$, which has been missed in many earlier measurements of the local GSMF.

Atomic gas fractions in active galactic nucleus host galaxies

The feedback from an active galactic nucleus (AGN) is frequently invoked as a mechanism through which gas can be heated or removed from a galaxy. However, gas fraction measurements in AGN hosts have yielded mixed support for this scenario. Here, we re-visit the assessment of fgas (=MHI/M*) in z<0.05 AGN hosts in the Sloan Digital Sky Survey (SDSS) using two complementary techniques. First, we investigate fgas for 75 AGN host galaxies in the extended GALEX Arecibo SDSS Survey (xGASS), whose atomic gas fractions are complete to a few percent. Second, we construct HI spectral stacks of 1562 AGN from the Arecibo Legacy Fast ALFA (ALFALFA) survey, which enables us to extend the AGN sample to lower stellar masses. Both techniques find that, at fixed M*, AGN hosts with log M*>10.2 are HI rich by a factor of ~2. However, this gas fraction excess disappears when the control sample is additionally matched in star formation rate (SFR), indicating that these AGN hosts are actually HI normal. At lower stellar mass, the stacking analysis reveals that AGN hosts are HI poor at fixed stellar mass. In the lowest M* regime probed by our sample, 9<log M*<9.6, the HI deficit in AGN hosts is a factor of ~4, and remains at a factor of ~2 even when the control sample is additionally matched in SFR. Our results help reconcile previously conflicting results, by showing that matching control samples by more than just stellar mass is critical for a rigourous comparison.

Enhanced atomic gas fractions in recently merged galaxies: quenching is not a result of post-merger gas exhaustion

We present a detailed assessment of the global atomic hydrogen gas fraction in a sample of post-merger galaxies identified in the Sloan Digital Sky Survey (SDSS). Archival HI measurements of 47 targets are combined with new Arecibo observations of a further 51 galaxies. The stellar mass range of the post-merger sample, our observing strategy, detection thresholds and data analysis procedures replicate those of the extended GALEX Arecibo SDSS Survey (xGASS) which can therefore be used as a control sample. Our principal results are: 1) The post-merger sample shows a ~50 per cent higher HI detection fraction compared with xGASS; 2) Accounting for non-detections, the median atomic gas fraction of the post-merger sample is larger than the control sample by 0.3 -- 0.6 dex; 3) The median atomic gas fraction enhancement (delta fgas), computed on a galaxy-by-galaxy basis at fixed stellar mass, is 0.51 dex. Our results demonstrate that recently merged galaxies are typically a factor of ~3 more HI rich than control galaxies of the same M*. If the control sample is additionally matched in star formation rate, the median HI excess is reduced to delta fgas = 0.2 dex, showing that the enhanced atomic gas fractions in post-mergers are not purely a reflection of changes in star formation activity. We conclude that merger-induced starbursts and outflows do not lead to prompt quenching via exhaustion/expulsion of the galactic gas reservoirs. Instead, we propose that if star formation ceases after a merger, it is more likely due to an enhanced turbulence which renders the galaxy unable to effectively form new stars.

Galaxy pairs in the SDSS – XIII. The connection between enhanced star formation and molecular gas properties in galaxy mergers

We investigate the connection between star formation and molecular gas properties in galaxy mergers at low redshift (z$\leq$0.06). The study we present is based on IRAM 30-m CO(1-0) observations of 11 galaxies with a close companion selected from the Sloan Digital Sky Survey (SDSS). The pairs have mass ratios $\leq$4, projected separations r$_{\mathrm{p}} \leq$30 kpc and velocity separations $\Delta$V$\leq$300 km s$^{-1}$, and have been selected to exhibit enhanced specific star formation rates (sSFR). We calculate molecular gas (H$_{2}$) masses, assigning to each galaxy a physically motivated conversion factor $\alpha_{\mathrm{CO}}$, and we derive molecular gas fractions and depletion times. We compare these quantities with those of isolated galaxies from the extended CO Legacy Data base for the GALEX Arecibo SDSS Survey sample (xCOLDGASS, Saintonge et al. 2017) with gas quantities computed in an identical way. Ours is the first study which directly compares the gas properties of galaxy pairs and those of a control sample of normal galaxies with rigorous control procedures and for which SFR and H$_{2}$ masses have been estimated using the same method. We find that the galaxy pairs have shorter depletion times and an average molecular gas fraction enhancement of 0.4 dex compared to the mass matched control sample drawn from xCOLDGASS. However, the gas masses (and fractions) in galaxy pairs and their depletion times are consistent with those of non-mergers whose SFRs are similarly elevated. We conclude that both external interactions and internal processes may lead to molecular gas enhancement and decreased depletion times.

C IV Broad Absorption Line Variability in QSO Spectra from SDSS Surveys

Broad absorption lines (BALs) in the spectra of quasi-stellar objects (QSOs) are thought to arise from outflowing winds along our line of sight; winds, in turn, are thought to originate from the accretion disk, in the very surroundings of the central supermassive black hole (SMBH), and they likely affect the accretion process onto the SMBH, as well as galaxy evolution. BALs can exhibit variability on timescales typically ranging from months to years. We analyze such variability and, in particular, BAL disappearance, with the aim of investigating QSO physics and structure. We search for disappearing C {\scriptsize{IV}} BALs in the spectra of 1319 QSOs from different programs from the Sloan Digital Sky Survey (SDSS); the analyzed time span covers $0.28-4.9$ yr (rest frame), and the source redshifts are in the range $1.68-4.27$. This is to date the largest sample ever used for such a study. We find 67 sources ($5.1_{-0.6}^{+0.7}$\% of the sample) with 73 disappearing BALs in total ($3.9_{-0.5}^{+0.5}$\% of the total number of C {\scriptsize{IV}} BALs detected; \textbf{some sources have more than one BAL that disappears}). We compare the sample of disappearing BALs to the whole sample of BALs, and investigate the correlation in the variability of multiple troughs in the same spectrum. We also derive estimates of the average lifetime of a BAL trough and of the BAL phase along our line of sight.

Solving the puzzle of discrepant quasar variability on monthly time-scales implied by SDSS and CRTS data sets

We present an improved photometric error analysis for the 7,100 CRTS (Catalina Real-Time Transient Survey) optical light curves for quasars from the SDSS (Sloan Digital Sky Survey) Stripe 82 catalogue. The SDSS imaging survey has provided a time-resolved photometric data set which greatly improved our understanding of the quasar optical continuum variability: Data for monthly and longer time-scales are consistent with a damped random walk (DRW). Recently, newer data obtained by CRTS provided puzzling evidence for enhanced variability, compared to SDSS results, on monthly time-scales. Quantitatively, SDSS results predict about 0.06 mag root-mean-square (rms) variability for monthly time-scales, while CRTS data show about a factor of 2 larger rms, for spectroscopically confirmed SDSS quasars. Our analysis has successfully resolved this discrepancy as due to slightly underestimated photometric uncertainties from the CRTS image processing pipelines. As a result, the correction for observational noise is too small and the implied quasar variability is too large. The CRTS photometric error correction factors, derived from detailed analysis of non-variable SDSS standard stars that were re-observed by CRTS, are about 20-30%, and result in reconciling quasar variability behaviour implied by the CRTS data with earlier SDSS results. An additional analysis based on independent light curve data for the same objects obtained by the Palomar Transient Factory provides further support for this conclusion. In summary, the quasar variability constraints on weekly and monthly time-scales from SDSS, CRTS and PTF surveys are mutually compatible, as well as consistent with DRW model.

The Next Generation Virgo Cluster Survey. XXVIII. Characterization of the Galactic White Dwarf Population

Abstract We use three different techniques to identify hundreds of white dwarf (WD) candidates in the Next Generation Virgo Cluster Survey (NGVS) based on photometry from the NGVS and GUViCS, and proper motions derived from the NGVS and the Sloan Digital Sky Survey (SDSS). Photometric distances for these candidates are calculated using theoretical color–absolute magnitude relations, while effective temperatures are measured by fitting their spectral energy distributions. Disk and halo WD candidates are separated using a tangential velocity cut of 200 km s−1 in a reduced proper motion diagram, which leads to a sample of six halo WD candidates. Cooling ages, calculated for an assumed WD mass of 0.6M ⊙, range between 60 Myr and 6 Gyr, although these estimates depend sensitively on the adopted mass. Luminosity functions for the disk and halo subsamples are constructed and compared to previous results from the SDSS and SuperCOSMOS survey. We compute a number density of (2.81 ± 0.52) × 10−3 pc−3 for the disk WD population—consistent with previous measurements. We find (7.85 ± 4.55) × 10−6 pc−3 for the halo, or 0.3% of the disk. Observed stellar counts are also compared to predictions made by the TRILEGAL and Besançon stellar population synthesis models. The comparison suggests that the TRILEGAL model overpredicts the total number of WDs. The WD counts predicted by the Besançon model agree with the observations, although a discrepancy arises when comparing the predicted and observed halo WD populations; the difference is likely due to the WD masses in the adopted model halo.

GLOBULAR AND OPEN CLUSTERS OBSERVED BY SDSS/SEGUE: THE GIANT STARS

ABSTRACT We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the Sloan Digital Sky Survey (SDSS)/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, we also present a new variable reddening map and a new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from T eff to g–r for giants of near solar abundance, using IRFM T eff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.

The massive end of the stellar mass function

We derive average flux corrections to the \texttt{Model} magnitudes of the Sloan Digital Sky Survey (SDSS) galaxies by stacking together mosaics of similar galaxies in bins of stellar mass and concentration. Extra flux is detected in the outer low surface brightness part of the galaxies, leading to corrections ranging from 0.05 to 0.32 mag for the highest stellar mass galaxies. We apply these corrections to the MPA-JHU (Max-Planck Institute for Astrophysics - John Hopkins University) stellar masses for a complete sample of half a million galaxies from the SDSS survey to derive a corrected galaxy stellar mass function at $z=0.1$ in the stellar mass range $9.5<\log(M_\ast/M_\odot)<12.0$. We find that the flux corrections and the use of the MPA-JHU stellar masses have a significant impact on the massive end of the stellar mass function, making the slope significantly shallower than that estimated by Li \& White (2009), but steeper than derived by Bernardi et al. (2013). This corresponds to a mean comoving stellar mass density of galaxies with stellar masses $\log(M_\ast/M_\odot) \ge 11.0$ that is a factor of 3.36 larger than the estimate by Li \& White (2009), but is 43\% smaller than reported by Bernardi et al. (2013).

A whole sky study of quasars known population starting from the LQAC-2 compiled catalogue

Context. Thanks to huge surveys, such as the Sloan Digital Sky Survey (SDSS), the last decade has shown a dramatic increase in the number of known quasars. In the second release of the general compiled catalogue Large Quasar Astrometric Catalogue (LQAC), 187 504 objects are recorded.Aims. From this catalogue, we carry out statistical studies dealing with several topics: the astrometric accuracy of the quasars, their spatial location, the distribution of the distance to the closest neighbour, the identification of binary quasars, the completness of catalogues at a given magnitude and the estimation of the number of quasars expected to be detected by the astrometric space mission Gaia .Methods. We analyse the astrometric improvements brought by the LQAC-2 in terms of equatorial coordinates off-sets. We plot the bi-dimensional spatial distribution of the LQAC-2 quasars according to their equatorial, galactic, and ecliptic coordinates, thus exploring the anisotropy of the distribution. We compare the observed distribution of closest neighbours with the theoretical values based on a Poisson distribution. Moreover, we perform a comparison between two catalogues, the SDSS and the 2dF inside a huge common field. By extrapolating to the whole sky we deduce the number of quasars that will be detected by Gaia .Results. We show how the equatorial, ecliptic, and galactic distribution of recorded quasars is strongly affected by the galactic extinction as well as by the deficiency of detections in the southern hemisphere. In homogenous zones covered by the SDSS survey we identify a significant excess of closest neighbours at short angular distances, with respect to the theoretical estimation, which is caused by the presence of binary quasars. Moreover, we detail the incompletness of systematic survey catalogues at any magnitude threshold, when comparing two huge surveys such as the SDSS and 2dF. Following this study we deduce the number of quasars detected by Gaia under a given magnitude threshold. For V = 20, this number should be at least 1 million objects.

Multi-wavelength study of 14 000 star-forming galaxies from the Sloan Digital Sky Survey

(abridged) We studied a large sample of ~14000 dwarf star-forming galaxies with strong emission lines selected from the Sloan Digital Sky Survey (SDSS) and distributed in the redshift range of z~0-0.6. We modelled spectral energy distributions (SED) of all galaxies which were based on the SDSS spectra in the visible range of 0.38-0.92 micron and included both the stellar and ionised gas emission. These SEDs were extrapolated to the UV and mid-infrared ranges to cover the wavelength range of 0.1-22 micron. The SDSS spectroscopic data were supplemented by photometric data from the GALEX, SDSS, 2MASS, WISE, IRAS, and NVSS all-sky surveys. We derived global characteristics of the galaxies, such as their element abundances, luminosities, and stellar masses. The luminosities and stellar masses range within the sample over ~5 orders of magnitude, thereby linking low-mass and low-luminosity blue compact dwarf (BCD) galaxies to luminous galaxies, which are similar to high-redshift Lyman-break galaxies (LBGs). The luminosity L(Hbeta) of the Hbeta emission line, a characteristic of the youngest stellar population with an age of a few Myr, is correlated with luminosities in other wavelength ranges. This implies that the most recent burst of star formation makes a significant contribution to the emission in the visible range and dominates in other wavelength ranges. We found 20 galaxies with very red WISE mid-infrared m(3.4micron)-m(4.6micron) colour (>2 mag), which suggests the important contribution of the hot (with a temperature of several hundred degree) dust emission in these galaxies. Our analysis of the balance between the luminosity in the WISE bands that covered a wavelength range of 3.4-22 micron and the luminosity of the emission absorbed at shorter wavelengths showed that the luminosity of the hot dust emission is increased with increasing L(Hbeta) and EW(Hbeta).

THE MULTI-OBJECT, FIBER-FED SPECTROGRAPHS FOR THE SLOAN DIGITAL SKY SURVEY AND THE BARYON OSCILLATION SPECTROSCOPIC SURVEY

We present the design and performance of the multi-object fiber spectrographs for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999 on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II surveys, enabling a wide variety of Galactic and extra-galactic science including the first observation of baryon acoustic oscillations in 2005. The spectrographs were upgraded in 2009 and are currently in use for BOSS, the flagship survey of the third-generation SDSS-III project. BOSS will measure redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-alpha absorption of 160,000 high redshift quasars over 10,000 square degrees of sky, making percent level measurements of the absolute cosmic distance scale of the Universe and placing tight constraints on the equation of state of dark energy. The twin multi-object fiber spectrographs utilize a simple optical layout with reflective collimators, gratings, all-refractive cameras, and state-of-the-art CCD detectors to produce hundreds of spectra simultaneously in two channels over a bandpass covering the near ultraviolet to the near infrared, with a resolving power R = \lambda/FWHM ~ 2000. Building on proven heritage, the spectrographs were upgraded for BOSS with volume-phase holographic gratings and modern CCD detectors, improving the peak throughput by nearly a factor of two, extending the bandpass to cover 360 < \lambda < 1000 nm, and increasing the number of fibers from 640 to 1000 per exposure. In this paper we describe the original SDSS spectrograph design and the upgrades implemented for BOSS, and document the predicted and measured performances.

Galaxy And Mass Assembly (GAMA): the connection between metals, specific SFR and H i gas in galaxies: the Z–SSFR relation

Abstract We study the interplay between gas phase metallicity (Z), specific star formation rate (SSFR) and neutral hydrogen gas (H i) for galaxies of different stellar masses. Our study uses spectroscopic data from Galaxy and Mass Assembly and Sloan Digital Sky Survey (SDSS) star-forming galaxies, as well as H i detection from the Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA) and Galex Arecibo SDSS Survey (GASS) public catalogues. We present a model based on the Z–SSFR relation that shows that at a given stellar mass, depending on the amount of gas, galaxies will follow opposite behaviours. Low-mass galaxies with a large amount of gas will show high SSFR and low metallicities, while low-mass galaxies with small amounts of gas will show lower SSFR and high metallicities. In contrast, massive galaxies with a large amount of gas will show moderate SSFR and high metallicities, while massive galaxies with small amounts of gas will show low SSFR and low metallicities. Using ALFALFA and GASS counterparts, we find that the amount of gas is related to those drastic differences in Z and SSFR for galaxies of a similar stellar mass.

COMPARING Hα AND H I SURVEYS AS MEANS TO A COMPLETE LOCAL GALAXY CATALOG IN THE ADVANCED LIGO/VIRGO ERA

Identifying the electromagnetic counterparts of gravitational wave (GW) sources detected by upcoming networks of advanced ground-based interferometers will be challenging due in part to the large number of unrelated astrophysical transients within the ~10-100 square degree sky localizations. A potential way to greatly reduce the number of such false positives is to limit detailed follow-up to only those candidates near galaxies within the GW sensitivity range of ~200 Mpc for binary neutron star mergers. Such a strategy is currently hindered by the fact that galaxy catalogs are grossly incomplete within this volume. Here we compare two methods for completing the local galaxy catalog: (1) a narrow-band H-alpha imaging survey; and (2) an HI emission line radio survey. Using H-alpha fluxes, stellar masses (M_star), and star formation rates (SFR) from galaxies in the Sloan Digital Sky Survey (SDSS), combined with HI data from the GALEX Arecibo SDSS Survey and the Herschel Reference Survey, we estimate that a H-alpha survey with a luminosity sensitivity of L_H-alpha = 1e40 erg/s at 200 Mpc could achieve a completeness of f_SFR ~ 75% with respect to total SFR, but only f_Mstar ~ 33% with respect to stellar mass (due to lack of sensitivity to early-type galaxies). These numbers are significantly lower than those achieved by an idealized spectroscopic survey due to the loss of H-alpha flux resulting from resolving out nearby galaxies and the inability to correct for the underlying stellar continuum. An HI survey with sensitivity similar to the proposed WALLABY survey on ASKAP could achieve f_SFR ~ 80% and f_Mstar ~ 50%, somewhat higher than that of the H-alpha survey. Finally, both H-alpha and HI surveys should achieve > 50% completeness with respect to the host galaxies of short duration gamma-ray bursts, which may trace the population of binary neutron star mergers.

The GALEX Arecibo SDSS Survey

We present the second data release from the GALEX Arecibo SDSS Survey (GASS), an ongoing large Arecibo program to measure the Hi properties for an unbiased sample of ~1000 galaxies with stellar masses greater than 1010 M⊙ and redshifts 0.025 < z < 0.05. GASS targets are selected from the Sloan Digital Sky Survey (SDSS) spectroscopic and Galaxy Evolution Explorer (GALEX) imaging surveys, and are observed until detected or until a gas mass fraction limit of a few per cent is reached. This second data installment includes new Arecibo observations of 240 galaxies, and marks the 50% of the complete survey. We present catalogs of the Hi, optical and ultraviolet parameters for these galaxies, and their Hi-line profiles. Having more than doubled the size of the sample since the first data release, we also revisit the main scaling relations of the Hi mass fraction with galaxy stellar mass, stellar mass surface density, concentration index, and NUV − r color, as well as the gas fraction plane introduced in our earlier work.