The Power Spectrum of the PSC Redshift Survey

We measure the redshift-space power spectrum P(k) for the recently completed IRAS Point Source Catalogue (PSC) redshift survey, which contains 14500 galaxies over 84% of the sky with 60 micron flux >= 0.6 Jansky. Comparison with simulations shows that our estimated errors on P(k) are realistic, and that systematic errors due to the finite survey volume are small for wavenumbers k >~ 0.03 h Mpc^-1. At large scales our power spectrum is intermediate between those of the earlier QDOT and 1.2 Jansky surveys, but with considerably smaller error bars; it falls slightly more steeply to smaller scales. We have fitted families of CDM-like models using the Peacock-Dodds formula for non-linear evolution; the results are somewhat sensitive to the assumed small-scale velocity dispersion \sigma_V. Assuming a realistic \sigma_V \approx 300 km/s yields a shape parameter \Gamma ~ 0.25 and normalisation b \sigma_8 ~ 0.75; if \sigma_V is as high as 600 km/s then \Gamma = 0.5 is only marginally excluded. There is little evidence for any `preferred scale' in the power spectrum or non-Gaussian behaviour in the distribution of large-scale power.Comment: Latex, uses mn.sty, 14 pages including 11 Postscript figures. Accepted by MNRA

Is the Lambda CDM Model Consistent with Observations of Large-Scale Structure?

The claim that large-scale structure data independently prefers the Lambda Cold Dark Matter model is a myth. However, an updated compilation of large-scale structure observations cannot rule out Lambda CDM at 95% confidence. We explore the possibility of improving the model by adding Hot Dark Matter but the fit becomes worse; this allows us to set limits on the neutrino mass.Comment: To appear in Proceedings of "Sources and Detection of Dark Matter/Energy in the Universe", ed. D. B. Cline. 6 pages, including 2 color figure

Pituitary Lesions, Obesity, and Mesenteric Lipomas in Insulin-Resistant Horses

The aim of the current study was to identify associations between pituitary lesions, body condition scores, and mesenteric lipomas in horses with insulin resistance. Necropsy examinations were performed following euthanasia in 30 adult horses designated as insulin resistant (n = 11) or insulin sensitive (n = 19). Insulin sensitivity was determined using the insulin-modified frequently sampled intravenous glucose tolerance test and resting insulin concentrations. At necropsy, mesenteric lipomas were measured. The pituitary and adrenal glands, pancreas, and liver were evaluated histologically; pituitary glands were scored based on published criteria. Insulin-resistant horses had significantly higher pituitary scores (p = 0.0035) and body condition scores (p = 0.0001), even when adjusting for age, and a greater frequency of mesenteric lipomas (p = 0.014) and greater lipoma area (p = 0.0332) than insulin-sensitive horses. Regardless of insulin status, horses with pituitary scores ≥3 (diffuse hyperplasia; n = 25) had higher body condition scores (p = 0.0313) and a greater frequency of mesenteric lipomas (p \u3c 0.0002) than those with lower pituitary scores. High body condition score was not correlated to an increased frequency of mesenteric lipomas. Detection of higher pituitary scores in insulin-resistant horses suggested an association between insulin resistance and pituitary morphology. Horses in the insulin-resistant group and those with high pituitary scores had higher body condition scores and a greater frequency of mesenteric lipomas. These horses might be at increased risk for lipoma-associated colic

Steps toward the power spectrum of matter. I.The mean spectrum of galaxies

We calculate the mean power spectrum of galaxies using published power spectra of galaxies and clusters of galaxies. On small scales we use the power spectrum derived from the 2-dimensional distribution of APM galaxies, on large scales we use power spectra derived from 3-dimensional data for galaxy and cluster samples. Spectra are reduced to real space and to the amplitude of the power spectrum of APM galaxies. Available data indicate the presence of two different populations in the nearby Universe. Clusters of galaxies sample a relatively large region in the Universe where rich, medium and poor superclusters are well represented. Their mean power spectrum has a spike on scale 120 h^{-1}Mpc, followed by an approximate power-law spectrum of index n = -1.9 towards small scales. The power spectrum found from LCRS and IRAS 1.2 Jy surveys is flatter around the maximum, which may represent regions of the Universe with medium-rich and poor superclusters.Comment: LaTex (sty files added), 35 pages, 5 PostScript figures and Table with mean power spectrum embedded, Astrophysical Journal (accepted

An Inversion Method for Measuring Beta in Large Redshift Surveys

A precision method for determining the value of Beta= Omega_m^{0.6}/b, where b is the galaxy bias parameter, is presented. In contrast to other existing techniques that focus on estimating this quantity by measuring distortions in the redshift space galaxy-galaxy correlation function or power spectrum, this method removes the distortions by reconstructing the real space density field and determining the value of Beta that results in a symmetric signal. To remove the distortions, the method modifies the amplitudes of a Fourier plane-wave expansion of the survey data parameterized by Beta. This technique is not dependent on the small-angle/plane-parallel approximation and can make full use of large redshift survey data. It has been tested using simulations with four different cosmologies and returns the value of Beta to +/- 0.031, over a factor of two improvement over existing techniques.Comment: 16 pages including 6 figures Submitted to The Astrophysical Journa

Toward High-Precision Measures of Large-Scale Structure

I review some results of estimation of the power spectrum of density fluctuations from galaxy redshift surveys and discuss advances that may be possible with the Sloan Digital Sky Survey. I then examine the realities of power spectrum estimation in the presence of Galactic extinction, photometric errors, galaxy evolution, clustering evolution, and uncertainty about the background cosmology.Comment: 24 pages, including 11 postscript figures. Uses crckapb.sty (included in submission). To appear in ``Ringberg Workshop on Large-Scale Structure,'' ed D. Hamilton (Kluwer, Amsterdam), p. 39