Evolution of the Angular Correlation Function

For faint photometric surveys our ability to quantify the clustering of galaxies has depended on interpreting the angular correlation function as a function of the limiting magnitude of the data. Due to the broad redshift distribution of galaxies at faint magnitude limits the correlation signal has been extremely difficult to detect and interpret. We introduce a new technique for measuring the evolution of clustering. We utilize photometric redshifts, derived from multicolor surveys, to isolate redshift intervals and calculate the evolution of the amplitude of the angular 2-pt correlation function. Applying these techniques to the the Hubble Deep Field we find that the shape of the correlation function, at z=1, is consistent with a power law with a slope of -0.8. For z>0.4 the best fit to the data is given by a model of clustering evolution with a comoving r0 = 2.37 Mpc and eps = -0.4 +/- 0.5, consistent with published measures of the clustering evolution. To match the canonical value of r0 = 5.4 Mpc, found for the clustering of local galaxies, requires a value of eps = 2.10 +/- 0.5 (significantly more than linear evolution). The log likelihood of this latter fit is 4.15 less than that for the r0 = 2.37 Mpc model. We, therefore, conclude that the parameterization of the clustering evolution of (1+z)^-(3+eps) is not a particularly good fit to the data.Comment: 12 pages (3 figures). Accepted for publication in Ap

The Evolution of the Global Star Formation History as Measured from the Hubble Deep Field

The Hubble Deep Field (HDF) is the deepest set of multicolor optical photometric observations ever undertaken, and offers a valuable data set with which to study galaxy evolution. Combining the optical WFPC2 data with ground-based near-infrared photometry, we derive photometrically estimated redshifts for HDF galaxies with J<23.5. We demonstrate that incorporating the near-infrared data reduces the uncertainty in the estimated redshifts by approximately 40% and is required to remove systematic uncertainties within the redshift range 1<z<2. Utilizing these photometric redshifts, we determine the evolution of the comoving ultraviolet (2800 A) luminosity density (presumed to be proportional to the global star formation rate) from a redshift of z=0.5 to z=2. We find that the global star formation rate increases rapidly with redshift, rising by a factor of 12 from a redshift of zero to a peak at z~1.5. For redshifts beyond 1.5, it decreases monotonically. Our measures of the star formation rate are consistent with those found by Lilly et al. (1996) from the CFRS at z 2, and bridge the redshift gap between those two samples. The overall star formation or metal enrichment rate history is consistent with the predictions of Pei and Fall (1995) based on the evolving HI content of Lyman-alpha QSO absorption line systems.Comment: Latex format, 10 pages, 3 postscript figures. Accepted for publication in Ap J Letter

A Robust Classification of Galaxy Spectra: Dealing with Noisy and Incomplete Data

Over the next few years new spectroscopic surveys (from the optical surveys of the Sloan Digital Sky Survey and the 2 degree Field survey through to space-based ultraviolet satellites such as GALEX) will provide the opportunity and challenge of understanding how galaxies of different spectral type evolve with redshift. Techniques have been developed to classify galaxies based on their continuum and line spectra. Some of the most promising of these have used the Karhunen and Loeve transform (or Principal Component Analysis) to separate galaxies into distinct classes. Their limitation has been that they assume that the spectral coverage and quality of the spectra are constant for all galaxies within a given sample. In this paper we develop a general formalism that accounts for the missing data within the observed spectra (such as the removal of sky lines or the effect of sampling different intrinsic rest wavelength ranges due to the redshift of a galaxy). We demonstrate that by correcting for these gaps we can recover an almost redshift independent classification scheme. From this classification we can derive an optimal interpolation that reconstructs the underlying galaxy spectral energy distributions in the regions of missing data. This provides a simple and effective mechanism for building galaxy spectral energy distributions directly from data that may be noisy, incomplete or drawn from a number of different sources.Comment: 20 pages, 8 figures. Accepted for publication in A

Can Baryonic Features Produce the Observed 100 Mpc Clustering?

We assess the possibility that baryonic acoustic oscillations in adiabatic models may explain the observations of excess power in large-scale structure on 100h^-1 Mpc scales. The observed location restricts models to two extreme areas of parameter space. In either case, the baryon fraction must be large (Omega_b/Omega_0 > 0.3) to yield significant features. The first region requires Omega_0 < 0.2h to match the location, implying large blue tilts (n>1.4) to satisfy cluster abundance constraints. The power spectrum also continues to rise toward larger scales in these models. The second region requires Omega_0 near 1, implying Omega_b well out of the range of big bang nucleosynthesis constraints; moreover, the peak is noticeably wider than the observations suggest. Testable features of both solutions are that they require moderate reionization and thereby generate potentially observable (about 1 uK) large-angle polarization, as well as sub-arc-minute temperature fluctuations. In short, baryonic features in adiabatic models may explain the observed excess only if currently favored determinations of cosmological parameters are in substantial error or if present surveys do not represent a fair sample of 100h^-1 Mpc structures.Comment: LaTeX, 7 pages, 5 Postscript figures, submitted to ApJ Letter

Spectral Templates from Multicolor Redshift Surveys

Understanding how the physical properties of galaxies (e.g. their spectral type or age) evolve as a function of redshift relies on having an accurate representation of galaxy spectral energy distributions. While it has been known for some time that galaxy spectra can be reconstructed from a handful of orthogonal basis templates, the underlying basis is poorly constrained. The limiting factor has been the lack of large samples of galaxies (covering a wide range in spectral type) with high signal-to-noise spectrophotometric observations. To alleviate this problem we introduce here a new technique for reconstructing galaxy spectral energy distributions directly from samples of galaxies with broadband photometric data and spectroscopic redshifts. Exploiting the statistical approach of the Karhunen-Loeve expansion, our iterative training procedure increasingly improves the eigenbasis, so that it provides better agreement with the photometry. We demonstrate the utility of this approach by applying these improved spectral energy distributions to the estimation of photometric redshifts for the HDF sample of galaxies. We find that in a small number of iterations the dispersion in the photometric redshifts estimator (a comparison between predicted and measured redshifts) can decrease by up to a factor of 2.Comment: 25 pages, 9 figures, LaTeX AASTeX, accepted for publication in A

The Statistical Approach to Quantifying Galaxy Evolution

Studies of the distribution and evolution of galaxies are of fundamental importance to modern cosmology; these studies, however, are hampered by the complexity of the competing effects of spectral and density evolution. Constructing a spectroscopic sample that is able to unambiguously disentangle these processes is currently excessively prohibitive due to the observational requirements. This paper extends and applies an alternative approach that relies on statistical estimates for both distance (z) and spectral type to a deep multi-band dataset that was obtained for this exact purpose. These statistical estimates are extracted directly from the photometric data by capitalizing on the inherent relationships between flux, redshift, and spectral type. These relationships are encapsulated in the empirical photometric redshift relation which we extend to z ~ 1.2, with an intrinsic dispersion of dz = 0.06. We also develop realistic estimates for the photometric redshift error for individual objects, and introduce the utilization of the galaxy ensemble as a tool for quantifying both a cosmological parameter and its measured error. We present deep, multi-band, optical number counts as a demonstration of the integrity of our sample. Using the photometric redshift and the corresponding redshift error, we can divide our data into different redshift intervals and spectral types. As an example application, we present the number redshift distribution as a function of spectral type.Comment: 40 pages (LaTex), 21 Figures, requires aasms4.sty; Accepted by the Astrophysical Journa