Features in the Primordial Spectrum from WMAP: A Wavelet Analysis

Precise measurements of the anisotropies in the cosmic microwave background enable us to do an accurate study on the form of the primordial power spectrum for a given set of cosmological parameters. In a previous paper (Shafieloo and Souradeep 2004), we implemented an improved (error sensitive) Richardson-Lucy deconvolution algorithm on the measured angular power spectrum from the first year of WMAP data to determine the primordial power spectrum assuming a concordance cosmological model. This recovered spectrum has a likelihood far better than a scale invariant, or, `best fit' scale free spectra (\Delta ln L = 25 w.r.t. Harrison Zeldovich, and, \Delta ln L = 11 w.r.t. power law with n_s=0.95). In this paper we use Discrete Wavelet Transform (DWT) to decompose the local features of the recovered spectrum individually to study their effect and significance on the recovered angular power spectrum and hence the likelihood. We show that besides the infra-red cut off at the horizon scale, the associated features of the primordial power spectrum around the horizon have a significant effect on improving the likelihood. The strong features are localised at the horizon scale.Comment: 8 pages, 4 figures, uses Revtex4, matches version accepted to Phys. Rev. D, main results and conclusions unchanged, references adde

The Small Scale Velocity Dispersion of Galaxies: A Comparison of Cosmological Simulations

The velocity dispersion of galaxies on small scales ($r\sim1h^{-1}$ Mpc), $\sigma_{12}(r)$, can be estimated from the anisotropy of the galaxy-galaxy correlation function in redshift space. We apply this technique to ``mock-catalogs'' extracted from N-body simulations of several different variants of Cold Dark Matter dominated cosmological models to obtain results which may be consistently compared to similar results from observations. We find a large variation in the value of $\sigma_{12}(1 h^{-1} Mpc)$ in different regions of the same simulation. We conclude that this statistic should not be considered to conclusively rule out any of the cosmological models we have studied. We attempt to make the statistic more robust by removing clusters from the simulations using an automated cluster-removing routine, but this appears to reduce the discriminatory power of the statistic. However, studying $\sigma_{12}$ as clusters with different internal velocity dispersions are removed leads to interesting information about the amount of power on cluster and subcluster scales. We also compute the pairwise velocity dispersion directly and compare this to the values obtained using the Davis-Peebles method, and find that the agreement is fairly good. We evaluate the models used for the mean streaming velocity and the pairwise peculiar velocity distribution in the original Davis-Peebles method by comparing the models with the results from the simulations.Comment: 20 pages, uuencoded (Latex file + 8 Postscript figures), uses AAS macro

Meeting the Goals of Service Learning in Pharmacy Education through Community Campus Partnerships

Healthy People 2010, published by the US Department of Health and Human Services, is a statement of health objectives for the nation to be achieved by the end of this decade. The goals are to increase quality and years of healthy life and to eliminate health disparities. In 2006, the West Virginia University School of Pharmacy began a revision to its Doctor of Pharmacy curriculum to include pharmacy practice experiences that would provide students with experience in developing disease prevention and health promotion programming in the community. Thus, the School of Pharmacy began a three-semester longitudinal service learning program which focused on advancing the objectives of Healthy People 2010 through service learning. The experiences of the School of Pharmacy service learning program from 2006 to the present are detailed

Large Scale Fluctuations in the X-Ray Background

We present an attempt to measure the large angular scale fluctuations in the X-Ray Background (XRB) from the HEAO1-A2 data, expressed in terms of spherical harmonics. We model the harmonic coefficients assuming a power spectrum and an epoch-dependent bias parameter, and using a phenomenological scenario describing the evolution of the X-ray sources. From the few low-order multipoles detected above shot noise, we estimate the power-spectrum normalization on scales intermediate between those explored by local galaxy redshift surveys (~ 100 Mpc) and by the COBE Microwave Background measurements (~ 1000 Mpc). We find that the HEAO1 harmonics are consistent with present epoch rms fluctuations of the X-ray sources bx(0)sigma8 ~ 1-2 in 8 Mpc spheres. Therefore the observed fluctuations in the XRB are roughly as expected from interpolating between the local galaxy surveys and the COBE CMB experiment. We predict that an X-ray all-sky surface brightness survey resolving sources a factor of 10 fainter than HEAO1, may reveal fluctuations to significantly larger angular scales and therefore more strongly constrain the large scale structure of the Universe on scales of hundreds of Mpcs.Comment: 14 pages, 3 Postscript figures, uses aaspp4.sty and psfig. Revised following referee's report. Accepted for publication in Ap

Percolation Analysis of a Wiener Reconstruction of the IRAS 1.2 Jy Redshift Catalog

We present percolation analyses of Wiener Reconstructions of the IRAS 1.2 Jy Redshift Survey. There are ten reconstructions of galaxy density fields in real space spanning the range $\beta= 0.1$ to $1.0$, where ${\beta}={\Omega^{0.6}}/b$, $\Omega$ is the present dimensionless density and $b$ is the bias factor. Our method uses the growth of the largest cluster statistic to characterize the topology of a density field, where Gaussian randomized versions of the reconstructions are used as standards for analysis. For the reconstruction volume of radius, $R {\approx} 100 h^{-1}$ Mpc, percolation analysis reveals a slight `meatball' topology for the real space, galaxy distribution of the IRAS survey. cosmology-galaxies:clustering-methods:numericalComment: Revised version accepted for publication in The Astrophysical Journal, January 10, 1997 issue, Vol.47