[en] We present a data-driven method—heteroscedastic matrix factorization, a kind of probabilistic factor analysis—for modeling or performing dimensionality reduction on observed spectra or other high-dimensional data with known but non-uniform observational uncertainties. The method uses an iterative inverse-variance-weighted least-squares minimization procedure to generate a best set of basis functions. The method is similar to principal components analysis (PCA), but with the substantial advantage that it uses measurement uncertainties in a responsible way and accounts naturally for poorly measured and missing data; it models the variance in the noise-deconvolved data space. A regularization can be applied, in the form of a smoothness prior (inspired by Gaussian processes) or a non-negative constraint, without making the method prohibitively slow. Because the method optimizes a justified scalar (related to the likelihood), the basis provides a better fit to the data in a probabilistic sense than any PCA basis. We test the method on Sloan Digital Sky Survey (SDSS) spectra, concentrating on spectra known to contain two redshift components: these are spectra of gravitational lens candidates and massive black hole binaries. We apply a hypothesis test to compare one-redshift and two-redshift models for these spectra, utilizing the data-driven model trained on a random subset of all SDSS spectra. This test confirms 129 of the 131 lens candidates in our sample and all of the known binary candidates, and turns up very few false positives.

[en] The two-point correlation function (2pcf) is the key statistic in structure formation; it measures the clustering of galaxies or other density field tracers. Estimators of the 2pcf, including the standard Landy–Szalay (LS) estimator, evaluate the 2pcf in hard-edged separation bins, which is scientifically inappropriate and results in a poor trade-off between bias and variance. We present a new 2pcf estimator, the Continuous-Function Estimator, which generalizes LS to a continuous representation and obviates binning in separation or any other pair property. Our estimator, inspired by the mathematics of least-squares fitting, replaces binned pair counts with projections onto basis functions; it outputs the best linear combination of basis functions to describe the 2pcf. The choice of basis can take into account the expected form of the 2pcf, as well as its dependence on pair properties other than separation. We show that the Continuous-Function Estimator with a cubic-spline basis better represents the shape of the 2pcf compared to LS. We also estimate directly the baryon acoustic scale, using a small number of physically motivated basis functions. Critically, this leads to a reduction in the number of mock catalogs required for covariance estimation, which is currently the limiting step in many 2pcf analyses. We discuss further applications of the Continuous-Function Estimator, including determination of the dependence of clustering on galaxy properties and searches for potential inhomogeneities or anisotropies in large-scale structure.

[en] The narrow GD-1 stream of stars, spanning 60⁰ on the sky at a distance of ∼10 kpc from the Sun and ∼15 kpc from the Galactic center, is presumed to be debris from a tidally disrupted star cluster that traces out a test-particle orbit in the Milky Way halo. We combine Sloan Digital Sky Survey (SDSS) photometry, USNO-B astrometry, and SDSS and Calar Alto spectroscopy to construct a complete, empirical six-dimensional (6D) phase-space map of the stream. We find that an eccentric orbit in a flattened isothermal potential describes this phase-space map well. Even after marginalizing over the stream orbital parameters and the distance from the Sun to the Galactic center, the orbital fit to GD-1 places strong constraints on the circular velocity at the Sun's radius V_c = 224 ± 13 km s^-1 and total potential flattening q_Φ = 0.87^+0.07_-0.04. When we drop any informative priors on V_c , the GD-1 constraint becomes V_c = 221 ± 18 km s^-1. Our 6D map of GD-1, therefore, yields the best current constraint on V_c and the only strong constraint on q_Φ at Galactocentric radii near R ∼ 15 kpc. Much, if not all, of the total potential flattening may be attributed to the mass in the stellar disk, so the GD-1 constraints on the flattening of the halo itself are weak: q_Φ,halo > 0.89 at 90% confidence. The greatest uncertainty in the 6D map and the orbital analysis stems from the photometric distances, which will be obviated by GAIA.

[en] We present optical and mid-infrared photometry of a statistically complete sample of 29 dwarf galaxies (M_r > - 15 mag) selected from the Sloan Digital Sky Survey (SDSS) spectroscopic sample and observed in the mid-infrared with Spitzer IRAC. This sample contains nearby (redshift ∼<0.005) galaxies 3 mag fainter than previously studied samples. We compare our sample with other star-forming galaxies that have been observed with both IRAC and SDSS. We examine the relationship of the infrared color, [3.6]-[7.8], sensitive to polycyclic aromatic hydrocarbon (PAH) abundance and also hot dust and stellar continuum, with star formation rates (SFRs), oxygen abundances, and radiation hardness, all estimated by optical emission lines. Consistent with studies of more luminous dwarfs, we find that these dwarf galaxies show much redder [3.6]-[7.8] color than luminous galaxies with similar specific SFRs. Unlike luminous galaxies, we find that these dwarf galaxies show no significant dependence at all of the [3.6]-[7.8] color on SFR, oxygen abundance, or radiation hardness, despite the fact that the sample spans a significant range in all of these quantities. When the dwarfs in our sample are compared with more luminous dwarfs, we find that the [3.6]-[7.8] color, potentially tracing the PAH emission, depends on oxygen abundance and radiation hardness. However, these two parameters are correlated with one another as well; we break this degeneracy by looking at the PAH-oxygen abundance relation at a fixed radiation hardness and the PAH-hardness relation at a fixed oxygen abundance. This test shows that the [3.6]-[7.8] color in dwarf galaxies appears to depend more directly on oxygen abundance based on the data currently available.

[en] The velocity distribution of nearby stars (∼<100 pc) contains many overdensities or 'moving groups', clumps of comoving stars, that are inconsistent with the standard assumption of an axisymmetric, time-independent, and steady-state Galaxy. We study the age and metallicity properties of the low-velocity moving groups based on the reconstruction of the local velocity distribution in Paper I of this series. We perform stringent, conservative hypothesis testing to establish for each of these moving groups whether it could conceivably consist of a coeval population of stars. We conclude that they do not: the moving groups are neither trivially associated with their eponymous open clusters nor with any other inhomogeneous star formation event. Concerning a possible dynamical origin of the moving groups, we test whether any of the moving groups has a higher or lower metallicity than the background population of thin disk stars, as would generically be the case if the moving groups are associated with resonances of the bar or spiral structure. We find clear evidence that the Hyades moving group has higher than average metallicity and weak evidence that the Sirius moving group has lower than average metallicity, which could indicate that these two groups are related to the inner Lindblad resonance of the spiral structure. Further, we find weak evidence that the Hercules moving group has higher than average metallicity, as would be the case if it is associated with the bar's outer Lindblad resonance. The Pleiades moving group shows no clear metallicity anomaly, arguing against a common dynamical origin for the Hyades and Pleiades groups. Overall, however, the moving groups are barely distinguishable from the background population of stars, raising the likelihood that the moving groups are associated with transient perturbations.

[en] An analytic relation between the statistics of photons in pixels and the number counts of multi-photon point sources is used to constrain the distribution of gamma-ray point sources below the Fermi detection limit at energies above 1 GeV and at latitudes below and above 30 deg. The derived source-count distribution is consistent with the distribution found by the Fermi Collaboration based on the first Fermi point-source catalog. In particular, we find that the contribution of resolved and unresolved active galactic nuclei (AGNs) to the total gamma-ray flux is below 20%-25%. In the best-fit model, the AGN-like point-source fraction is 17% ± 2%. Using the fact that the Galactic emission varies across the sky while the extragalactic diffuse emission is isotropic, we put a lower limit of 51% on Galactic diffuse emission and an upper limit of 32% on the contribution from extragalactic weak sources, such as star-forming galaxies. Possible systematic uncertainties are discussed.

[en] We measure the mass growth rate by merging for a wide range of galaxy types. We present the small-scale (0.014 h ^–1₇₀ Mpc < r < 11 h ₇₀^–1 Mpc) projected cross-correlation functions w(r _p) of galaxy subsamples from the spectroscopic sample of the NYU Value-Added Galaxy Catalog (5 × 10⁵ galaxies of redshifts 0.03 < z < 0.15) with galaxy subsamples from the Sloan Digital Sky Survey imaging (4 × 10⁷ galaxies). We use smooth fits to de-project the two-dimensional functions w(r _p) to obtain smooth three-dimensional real-space cross-correlation functions ξ(r) for each of several spectroscopic subsamples with each of several imaging subsamples. Because close pairs are expected to merge, the three-space functions and dynamical evolution time estimates provide galaxy accretion rates. We find that the accretion onto massive blue galaxies and onto red galaxies is dominated by red companions, and that onto small-mass blue galaxies, red and blue galaxies make comparable contributions. We integrate over all types of companions and find that at fixed stellar mass, the total fractional accretion rates onto red galaxies (∼3 h ₇₀ percent per Gyr) are greater than that onto blue galaxies (∼1 h ₇₀ percent per Gyr). These rates are almost certainly overestimates because we have assumed that all close pairs merge as quickly as the merger time that we used. One conclusion of this work is that if the total growth of red galaxies from z = 1 to z = 0 is mainly due to merging, the merger rates must have been higher in the past.

[en] We present a new method for inferring photometric redshifts in deep galaxy and quasar surveys, based on a data-driven model of latent spectral energy distributions (SEDs) and a physical model of photometric fluxes as a function of redshift. This conceptually novel approach combines the advantages of both machine learning methods and template fitting methods by building template SEDs directly from the spectroscopic training data. This is made computationally tractable with Gaussian processes operating in flux–redshift space, encoding the physics of redshifts and the projection of galaxy SEDs onto photometric bandpasses. This method alleviates the need to acquire representative training data or to construct detailed galaxy SED models; it requires only that the photometric bandpasses and calibrations be known or have parameterized unknowns. The training data can consist of a combination of spectroscopic and deep many-band photometric data with reliable redshifts, which do not need to entirely spatially overlap with the target survey of interest or even involve the same photometric bands. We showcase the method on the i -magnitude-selected, spectroscopically confirmed galaxies in the COSMOS field. The model is trained on the deepest bands (from SUBARU and HST ) and photometric redshifts are derived using the shallower SDSS optical bands only. We demonstrate that we obtain accurate redshift point estimates and probability distributions despite the training and target sets having very different redshift distributions, noise properties, and even photometric bands. Our model can also be used to predict missing photometric fluxes or to simulate populations of galaxies with realistic fluxes and redshifts, for example.

[en] Different stellar sub-populations of the Milky Way's stellar disk are known to have different vertical scale heights, their thickness increasing with age. Using SEGUE spectroscopic survey data, we have recently shown that mono-abundance sub-populations, defined in the [α/Fe]-[Fe/H] space, are well described by single-exponential spatial-density profiles in both the radial and the vertical direction; therefore, any star of a given abundance is clearly associated with a sub-population of scale height h_z . Here, we work out how to determine the stellar surface-mass density contributions at the solar radius R₀ of each such sub-population, accounting for the survey selection function, and for the fraction of the stellar population mass that is reflected in the spectroscopic target stars given populations of different abundances and their presumed age distributions. Taken together, this enables us to derive Σ_R0(h_z), the surface-mass contributions of stellar populations with scale height h_z . Surprisingly, we find no hint of a thin-thick disk bi-modality in this mass-weighted scale-height distribution, but a smoothly decreasing function, approximately Σ_R0(h_z)∝ exp(-h_z), from h_z ≈ 200 pc to h_z ≈ 1 kpc. As h_z is ultimately the structurally defining property of a thin or thick disk, this shows clearly that the Milky Way has a continuous and monotonic distribution of disk thicknesses: there is no 'thick disk' sensibly characterized as a distinct component. We discuss how our result is consistent with evidence for seeming bi-modality in purely geometric disk decompositions or chemical abundances analyses. We constrain the total visible stellar surface-mass density at the solar radius to be Σ_R0* = 30 ± 1 M_☉ pc^–2.

[en] We present AGNfitter, a publicly available open-source algorithm implementing a fully Bayesian Markov Chain Monte Carlo method to fit the spectral energy distributions (SEDs) of active galactic nuclei (AGNs) from the sub-millimeter to the UV, allowing one to robustly disentangle the physical processes responsible for their emission. AGNfitter makes use of a large library of theoretical, empirical, and semi-empirical models to characterize both the nuclear and host galaxy emission simultaneously. The model consists of four physical emission components: an accretion disk, a torus of AGN heated dust, stellar populations, and cold dust in star-forming regions. AGNfitter determines the posterior distributions of numerous parameters that govern the physics of AGNs with a fully Bayesian treatment of errors and parameter degeneracies, allowing one to infer integrated luminosities, dust attenuation parameters, stellar masses, and star-formation rates. We tested AGNfitter’s performance on real data by fitting the SEDs of a sample of 714 X-ray selected AGNs from the XMM-COSMOS survey, spectroscopically classified as Type1 (unobscured) and Type2 (obscured) AGNs by their optical–UV emission lines. We find that two independent model parameters, namely the reddening of the accretion disk and the column density of the dusty torus, are good proxies for AGN obscuration, allowing us to develop a strategy for classifying AGNs as Type1 or Type2, based solely on an SED-fitting analysis. Our classification scheme is in excellent agreement with the spectroscopic classification, giving a completeness fraction of $\sim <!--\; ???\; -->86\mathrm{\%<!--\; \%\; -->}$ and $\sim <!--\; ???\; -->70\mathrm{\%<!--\; \%\; -->}$, and an efficiency of $\sim <!--\; ???\; -->80\mathrm{\%<!--\; \%\; -->}$ and $\sim <!--\; ???\; -->77\mathrm{\%<!--\; \%\; -->}$, for Type1 and Type2 AGNs, respectively.