6,829 research outputs found
Acoustic Oscillations in the Early Universe and Today
During its first ~100,000 years, the universe was a fully ionized plasma with
a tight coupling by Thompson scattering between the photons and matter. The
trade--off between gravitational collapse and photon pressure causes acoustic
oscillations in this primordial fluid. These oscillations will leave
predictable imprints in the spectra of the cosmic microwave background and the
present day matter-density distribution. Recently, the BOOMERANG and MAXIMA
teams announced the detection of these acoustic oscillations in the cosmic
microwave background (observed at redshift ~1000). Here, we compare these CMB
detections with the corresponding acoustic oscillations in the matter-density
power spectrum (observed at redshift ~0.1). These consistent results, from two
different cosmological epochs, provide further support for our standard Hot Big
Bang model of the universe.Comment: To appear in the journal Science. 6 pages, 1 color figur
The Interplay of Cluster and Galaxy Evolution
We review here the interplay of cluster and galaxy evolution. As a case
study, we consider the Butcher-Oemler effect and propose that it is the result
of the changing rate of cluster merger events in a hierarchical universe. This
case study highlights the need for new catalogs of clusters and groups that
possess quantified morphologies. We present such a sample here, namely the
Sloan Digital Sky Survey (SDSS) C4 Catalog, which has been objectively-selected
from the SDSS spectroscopic galaxy sample. We outline here the C4 algorithm and
present first results based on the SDSS Early Data Release, including an X-ray
luminosity-velocity dispersion (L_x-sigma) scaling relationship (as a function
of cluster morphology), and the density-SFR relation of galaxies within C4
clusters (Gomez et al. 2003). We also discuss the merger of Coma and the
NGC4839 group, and its effect on the galaxy populations in these systems. We
finish with a brief discussion of a new sample of Hdelta-selected galaxies
(i.e., k+a, post--starburst galaxies) obtained from the SDSS spectroscopic
survey.Comment: Invited review at the JENAM 2002 Workshop on "Galaxy Evolution in
Groups and Clusters", Porto, Sep 5-7 2002, eds. Lobo, Serote-Roos and
Biviano, Kluwer in pres
Detecting the Baryons in Matter Power Spectra
We examine power spectra from the Abell/ACO rich cluster survey and the 2dF
Galaxy Redshift Survey (2dfGRS) for observational evidence of features produced
by the baryons. A non-negligible baryon fraction produces relatively sharp
oscillatory features at specific wavenumbers in the matter power spectrum.
However, the mere existence of baryons will also produce a global suppression
of the power spectrum. We look for both of these features using the false
discovery rate (FDR) statistic. We show that the window effects on the
Abell/ACO power spectrum are minimal, which has allowed for the discovery of
discrete oscillatory features in the power spectrum. On the other hand, there
are no statistically significant oscillatory features in the 2dFGRS power
spectrum, which is expected from the survey's broad window function. After
accounting for window effects, we apply a scale-independent bias to the 2dFGRS
power spectrum, P_{Abell}(k) = b^2P_{2dF}(k) and b = 3.2. We find that the
overall shapes of the Abell/ACO and the biased 2dFGRS power spectra are
entirely consistent over the range 0.02 <= k <= 0.15hMpc^-1. We examine the
range of Omega_{matter} and baryon fraction for which these surveys could
detect significant suppression in power. The reported baryon fractions for both
the Abell/ACO and 2dFGRS surveys are high enough to cause a detectable
suppression in power (after accounting for errors, windows and k-space
sampling). Using the same technique, we also examine, given the best fit baryon
density obtained from BBN, whether it is possible to detect additional
suppression due to dark matter-baryon interaction. We find that the limit on
dark matter cross section/mass derived from these surveys are the same as those
ruled out in a recent study by Chen, Hannestad and Scherrer.Comment: 11 pages of text, 6 figures. Submitted to Ap
Construction and evaluation of classifiers for forensic document analysis
In this study we illustrate a statistical approach to questioned document
examination. Specifically, we consider the construction of three classifiers
that predict the writer of a sample document based on categorical data. To
evaluate these classifiers, we use a data set with a large number of writers
and a small number of writing samples per writer. Since the resulting
classifiers were found to have near perfect accuracy using leave-one-out
cross-validation, we propose a novel Bayesian-based cross-validation method for
evaluating the classifiers.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS379 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Possible Detection of Baryonic Fluctuations in the Large-Scale Structure Power Spectrum
We present a joint analysis of the power spectra of density fluctuations from
three independent cosmological redshift surveys; the PSCz galaxy catalog, the
APM galaxy cluster catalog and the Abell/ACO cluster catalog. Over the range
0.03 <= k <= 0.15 h/Mpc,the amplitudes of these three power spectra are related
through a simple linear biasing model with b = 1.5 and b = 3.6 for Abell/ACO
versus APM and Abell/ACO versus the PSCz respectively. Furthermore, the shape
of these power spectra are remarkably similar despite the fact that they are
comprised of significantly different objects (individual galaxies through to
rich clusters). Individually, each of these surveys show visible evidence for
``valleys'' in their power spectra. We use a newly developed statistical
technique called the False Discovery Rate, to show that these ``valleys'' are
statistically significant. One favored cosmological explanation for such
features in the power spectrum is the presence of a non-negligible baryon
fraction (Omega_b/Omega_m) in the Universe which causes acoustic oscillations
in the transfer function of adiabatic inflationary models. We have performed a
maximum-likelihood marginalization over four important cosmological parameters
of this model (Omega_m, Omega_b, n_s, H_o). We use a prior on H_0 = 69(+/-15),
and find Omega_mh^2 = 0.12(+0.03/-0.02), Omega_bh^2 =0.029(+0.011/-0.015), n_s
= 1.08^(+0.17/-0.20) (2 sigma confidence limits) which are fully consistent
with the favored values of these cosmological parameters from the recent Cosmic
Microwave Background (CMB) experiments. This agreement strongly suggests that
we have detected baryonic oscillations in the power spectrum of matter at a
level expected from a Cold Dark Matter model normalized to fit these CMB
measurements.Comment: 13 pages, 4 figures, ApJ in press. Typos fixed. Replaced Figure 4
with improved versio
Controlling the False Discovery Rate in Astrophysical Data Analysis
The False Discovery Rate (FDR) is a new statistical procedure to control the
number of mistakes made when performing multiple hypothesis tests, i.e. when
comparing many data against a given model hypothesis. The key advantage of FDR
is that it allows one to a priori control the average fraction of false
rejections made (when comparing to the null hypothesis) over the total number
of rejections performed. We compare FDR to the standard procedure of rejecting
all tests that do not match the null hypothesis above some arbitrarily chosen
confidence limit, e.g. 2 sigma, or at the 95% confidence level. When using FDR,
we find a similar rate of correct detections, but with significantly fewer
false detections. Moreover, the FDR procedure is quick and easy to compute and
can be trivially adapted to work with correlated data. The purpose of this
paper is to introduce the FDR procedure to the astrophysics community. We
illustrate the power of FDR through several astronomical examples, including
the detection of features against a smooth one-dimensional function, e.g.
seeing the ``baryon wiggles'' in a power spectrum of matter fluctuations, and
source pixel detection in imaging data. In this era of large datasets and high
precision measurements, FDR provides the means to adaptively control a
scientifically meaningful quantity -- the number of false discoveries made when
conducting multiple hypothesis tests.Comment: 15 pages, 9 figures. Submitted to A
Environmental Dependence of the Fundamental Plane of Galaxy Clusters
Galaxy clusters approximate a planar (FP) distribution in a three-dimensional
parameter space which can be characterized by optical luminosity, half-light
radius, and X-ray luminosity. Using a high-quality catalog of cluster
redshifts, we find the nearest neighbor cluster for those common to an FP study
and the cluster catalog. Examining scatter about the FP, we find 99.2%
confidence that it is dependent on nearest neighbor distance. Our study of
X-Ray clusters finds that those with high central gas densities are
systematically closer to neighbor clusters. If we combine results here with
those of Fritsch and Buchert, we find an explanation for some of our previous
conclusions: Clusters in close proximity to other clusters are more likely to
have massive cooling flows because they are more relaxed and have higher
central gas densities.Comment: Accepted for publication in Astrophysical Journal Letters. Moderate
revisions, including more statistical analysis and discussion. Latex, 7 page
Nonparametric Inference for the Cosmic Microwave Background
The Cosmic Microwave Background (CMB), which permeates the entire Universe,
is the radiation left over from just 380,000 years after the Big Bang. On very
large scales, the CMB radiation field is smooth and isotropic, but the
existence of structure in the Universe - stars, galaxies, clusters of galaxies
- suggests that the field should fluctuate on smaller scales. Recent
observations, from the Cosmic Microwave Background Explorer to the Wilkinson
Microwave Anisotropy Project, have strikingly confirmed this prediction. CMB
fluctuations provide clues to the Universe's structure and composition shortly
after the Big Bang that are critical for testing cosmological models. For
example, CMB data can be used to determine what portion of the Universe is
composed of ordinary matter versus the mysterious dark matter and dark energy.
To this end, cosmologists usually summarize the fluctuations by the power
spectrum, which gives the variance as a function of angular frequency. The
spectrum's shape, and in particular the location and height of its peaks,
relates directly to the parameters in the cosmological models. Thus, a critical
statistical question is how accurately can these peaks be estimated. We use
recently developed techniques to construct a nonparametric confidence set for
the unknown CMB spectrum. Our estimated spectrum, based on minimal assumptions,
closely matches the model-based estimates used by cosmologists, but we can make
a wide range of additional inferences. We apply these techniques to test
various models and to extract confidence intervals on cosmological parameters
of interest. Our analysis shows that, even without parametric assumptions, the
first peak is resolved accurately with current data but that the second and
third peaks are not.Comment: Invited review for "Statistical Science". Accepted for publication in
Feburary 2004 journa
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