29,074 research outputs found
On The Validity of the Streaming Model for the Redshift-Space Correlation Function in the Linear Regime
The relation between the galaxy correlation function in real and
redshift-space is derived in the linear regime by an appropriate averaging of
the joint probability distribution of density and velocity. The derivation
recovers the familiar linear theory result on large scales but has the
advantage of clearly revealing the dependence of the redshift distortions on
the underlying peculiar velocity field; streaming motions give rise to
distortions of while variations in the anisotropic
velocity dispersion yield terms of order . This
probabilistic derivation of the redshift-space correlation function is similar
in spirit to the derivation of the commonly used ``streaming'' model, in which
the distortions are given by a convolution of the real-space correlation
function with a velocity distribution function. The streaming model is often
used to model the redshift-space correlation function on small, highly
non-linear, scales. There have been claims in the literature, however, that the
streaming model is not valid in the linear regime. Our analysis confirms this
claim, but we show that the streaming model can be made consistent with linear
theory {\it provided} that the model for the streaming has the functional form
predicted by linear theory and that velocity distribution is chosen to be a
Gaussian with the correct linear theory dispersion.Comment: 14 pages, no figures, uuencoded compressed postscrip
Constraints onOmega from the IRAS Redshift Surveys
We measure the anisotropy of the redshift-space power spectrum in the 1.2-Jy
and QDOT redshift surveys of IRAS-selected galaxies. On large scales, this
anisotropy is caused by coherent peculiar motions, and gravitational
instability theory predicts a distortion of the power spectrum that depends
only on the ratio , where
Omega is the cosmological density parameter and is the bias parameter. On
small scales, the distortion is dominated by the random velocity dispersion in
non-linear structures. We fit the observed anisotropy with an analytic model
that incorporates two parameters, beta, and a small-scale velocity dispersion
sigma_v. Tests on N-body simulations show that this model recovers beta quite
accurately on the scales accessible to the existing IRAS redshift surveys.
Applying our procedure to the 1.2-Jy and QDOT surveys, we find beta=0.52 +/-
0.13 and beta=0.54 +/- 0.3, respectively. These results imply Omega
approximately 0.35 if galaxies trace mass, or a bias factor of about 2 if
Omega=1.Comment: uufiles postscript here or plain postscript at
ftp://dust0.dur.ac.uk/pub/preprints/cole_rsd.p
A Spherical Harmonic Approach to Redshift Distortion and a Measurement of Omega from the 1.2 Jy IRAS Redshift Survey
We present a formalism for analysing redshift distortions based on a
spherical harmonic expansion of the density field. We use a maximum likelihood
estimator for the combination of density and bias parameters, .
We test the method with -body simulations and apply it to the 1.2 Jy IRAS
redshift survey.Comment: 8 pages--uuencoded postscript fil
Essential Strangeness in Nucleon Magnetic Moments
Effective quark magnetic moments are extracted from experimental measurements
as a function of the strangeness magnetic moment of the nucleon. Assumptions
made in even the most general quark model analyses are ruled out by this
investigation. Ab initio QCD calculations demand a non-trivial role for strange
quarks in the nucleon. The effective moments from QCD calculations are
reproduced for a strangeness magnetic moment contribution to the proton of 0.11
, which corresponds to .Comment: HYP '94 presentation. File is a uuencoded postscript file of a 2 page
manuscript including figures. Also available via anonymous ftp from
pacific.mps.ohio-state.edu in pub/NTG/Leinweber as StrQrkNmom.ps(.gz) OSU PP
#94-063
The HELP inequality on trees
We establish analogues of Hardy and Littlewood's integro-differential equation for Schrödinger-type operators on metric and discrete trees, based on a generalised strong limit-point property of the graph Laplacian
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