A Periodically Varying Luminous Quasar at z=2 from the Pan-STARRS1 Medium Deep Survey: A Candidate Supermassive Black Hole Binary in the Gravitational Wave-Driven Regime

Supermassive black hole binaries (SMBHBs) should be an inevitable consequence of the hierarchical growth of massive galaxies through mergers, and the strongest sirens of gravitational waves (GWs) in the cosmos. And yet, their direct detection has remained elusive due to the compact (sub-parsec) orbital separations of gravitationally bound SMBHBs. Here we exploit a theoretically predicted signature of a SMBHB in the time domain: periodic variability caused by a mass accretion rate that is modulated by the binarys orbital motion. We report our first significant periodically varying quasar detection from the systematic search in the Pan-STARRS1 (PS1) Medium Deep Survey. Our SMBHB candidate, PSO J334.2028+01.4075, is a luminous radio-loud quasar at $z=2.060$, with extended baseline photometry from the Catalina Real-Time Transient Survey, as well as archival spectroscopy from the FIRST Bright Quasar Survey. The observed period ($542 pm 15$ days) and estimated black hole mass ($log (M_{rm BH}/M_odot) = 9.97 pm 0.50$), correspond to an orbital separation of $7^{+8}_{-4}$ Schwarzschild radii ($sim 0.006^{+0.007}_{-0.003}$ pc), assuming the rest-frame period of the quasar variability traces the orbital period of the binary. This SMBHB candidate, discovered at the peak redshift for SMBH mergers, is in a physically stable configuration for a circumbinary accretion disk, and within the regime of GW-driven orbital decay. Our search with PS1 is a benchmark study for the exciting capabilities of LSST, which will have orders of magnitude larger survey power, and will potentially pinpoint the locations of thousands of SMBHBs in the variable night sky.

The UV-Optical Color Dependence of Galaxy Clustering in the Local Universe

We measure the UV-optical color dependence of galaxy clustering in the local universe. Using the clean separation of the red and blue sequences made possible by the NUV - r color-magnitude diagram, we segregate the galaxies into red, blue and intermediate green classes. We explore the clustering as a function of this segregation by removing the dependence on luminosity and by excluding edge-on galaxies as a means of a non-model dependent veto of highly extincted galaxies. We find that xi (r_p, pi) for both red and green galaxies shows strong redshift space distortion on small scales -- the finger-of-God effect, with green galaxies having a lower amplitude than is seen for the red sequence, and the blue sequence showing almost no distortion. On large scales, xi (r_p, pi) for all three samples show the effect of large-scale streaming from coherent infall. On scales 1 Mpc/h < r_p < 10 Mpc/h, the projected auto-correlation function w_p(r_p) for red and green galaxies fits a power-law with slope gamma ~ 1.93 and amplitude r_0 ~ 7.5 and 5.3, compared with gamma ~ 1.75 and r_0 ~ 3.9 Mpc/h for blue sequence galaxies. Compared to the clustering of a fiducial L* galaxy, the red, green, and blue have a relative bias of 1.5, 1.1, and 0.9 respectively. The w_p(r_p) for blue galaxies display an increase in convexity at ~ 1 Mpc/h, with an excess of large scale clustering. Our results suggest that the majority of blue galaxies are likely central galaxies in less massive halos, while red and green galaxies have larger satellite fractions, and preferentially reside in virialized structures. If blue sequence galaxies migrate to the red sequence via processes like mergers or quenching that take them through the green valley, such a transformation may be accompanied by a change in environment in addition to any change in luminosity and color.

Cross-Identification Performance from Simulated Detections: GALEX and SDSS

We investigate the quality of associations of astronomical sources from multi-wavelength observations using simulated detections that are realistic in terms of their astrometric accuracy, small-scale clustering properties and selection functions. We present a general method to build such mock catalogs for studying associations, and compare the statistics of cross-identifications based on angular separation and Bayesian probability criteria. In particular, we focus on the highly relevant problem of cross-correlating the ultraviolet Galaxy Evolution Explorer (GALEX) and optical Sloan Digital Sky Survey (SDSS) surveys. Using refined simulations of the relevant catalogs, we find that the probability thresholds yield lower contamination of false associations, and are more efficient than angular separation. Our study presents a set of recommended criteria to construct reliable cross-match catalogs between SDSS and GALEX with minimal artifacts.

Studying Large and Small Scale Environments of Ultraviolet Luminous Galaxies

Studying the environments of 0.4<z<1.2 UV-selected galaxies, as examples of extreme star-forming galaxies (with star formation rates in the range of 3-30 M_sol/yr), we explore the relationship between high rates of star-formation, host halo mass and pair fractions. We study the large-scale and small-scale environments of local Ultraviolet Luminous Galaxies (UVLGs) by measuring angular correlation functions. We cross-correlate these systems with other galaxy samples: a volume-limited sample (ALL), a Blue Luminous Galaxy sample (BLG) and a Luminous Red Galaxy sample (LRG). We determine the UVLG comoving correlation length to be r_0=4.8(+11.6/-2.4) h^-1 Mpc at <z> =1.0, which is unable to constrain the halo mass for this sample. However, we find that UVLGs form close (separation < 30 kpc) pairs with the ALL sample, but do not frequently form pairs with LRGs. A rare subset of UVLGs, those with the highest FUV surface brightnesses, are believed to be local analogs of high redshift Lyman Break Galaxies (LBGs) and are called Lyman Break Analogs (LBAs). LBGs and LBAs share similar characteristics (i.e., color, size, surface brightness, specific star formation rates, metallicities, and dust content). Recent HST images of z~0.2 LBAs show disturbed morphologies, signs of mergers and interactions. UVLGs may be influenced by interactions with other galaxies and we discuss this result in terms of other high star-forming, merging systems.

Spatial Clustering from GALEX-SDSS samples: Star Formation History and large-scale clustering

We measure the projected spatial correlation function w_p(r_p) from a large sample combining GALEX ultraviolet imaging with the SDSS spectroscopic sample. We study the dependence of the clustering strength for samples selected on (NUV - r)_abs color, specific star formation rate (SSFR), and stellar mass. We find that there is a smooth transition in the clustering of galaxies as a function of this color from weak clustering among blue galaxies to stronger clustering for red galaxies. The clustering of galaxies within the green valley has an intermediate strength, and is consistent with that expected from galaxy groups. The results are robust to the correction for dust extinction. The comparison with simple analytical modeling suggests that the halo occupation number increases with older star formation epochs. When splitting according to SSFR, we find that the SSFR is a more sensitive tracer of environment than stellar mass.

Photometric Redshift Estimation on SDSS Data Using Random Forests

Given multiband photometric data from the SDSS DR6, we estimate galaxy redshifts. We employ a Random Forest trained on color features and spectroscopic redshifts from 80,000 randomly chosen primary galaxies yielding a mapping from color to redshift such that the difference between the estimate and the spectroscopic redshift is small. Our methodology results in tight RMS scatter in the estimates limited by photometric errors. Additionally, this approach yields an error distribution that is nearly Gaussian with parameter estimates giving reliable confidence intervals unique to each galaxy photometric redshift.

Clustering Properties of restframe UV selected galaxies I: the correlation length derived from GALEX data in the local Universe

We present the first measurements of the angular correlation function of galaxies selected in the far (1530 A) and near (2310 A) Ultraviolet from the GALEX survey fields overlapping SDSS DR5 in low galactic extinction regions. The area used covers 120 sqdeg (GALEX - MIS) down to magnitude AB = 22, yielding a total of 100,000 galaxies. The mean correlation length is ~ 3.7 pm 0.6 Mpc and no significant trend is seen for this value as a function of the limiting apparent magnitude or between the GALEX bands. This estimate is close to that found from samples of blue galaxies in the local universe selected in the visible, and similar to that derived at z ~ 3 for LBGs with similar rest frame selection criteria. This result supports models that predict anti-biasing of star forming galaxies at low redshift, and brings an additional clue to the downsizing of star formation at z<1.

Clustering Properties of restframe UV selected galaxies II: Migration of Star Formation sites with cosmic time from GALEX and CFHTLS

We analyze the clustering properties of ultraviolet selected galaxies by using GALEX-SDSS data at z<0.6 and CFHTLS deep u imaging at z=1. These datasets provide a unique basis at z< 1 which can be directly compared with high redshift samples built with similar selection criteria. We discuss the dependence of the correlation function parameters (r0, delta) on the ultraviolet luminosity as well as the linear bias evolution. We find that the bias parameter shows a gradual decline from high (b > 2) to low redshift (b ~ 0.79^{+0.1}_{-0.08}). When accounting for the fraction of the star formation activity enclosed in the different samples, our results suggest that the bulk of star formation migrated from high mass dark matter halos at z>2 (10^12 < M_min < 10^13 M_sun, located in high density regions), to less massive halos at low redshift (M_min < 10^12 M_sun, located in low density regions). This result extends the ``downsizing picture (shift of the star formation activity from high stellar mass systems at high z to low stellar mass at low z) to the dark matter distribution.