1,308 research outputs found
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
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