982 research outputs found
Detecting the integrated Sachs-Wolfe effect with stacked voids
The stacking of cosmic microwave background (CMB) patches has been recently
used to detect the integrated Sachs-Wolfe effect (iSW). When focusing on the
locations of superstructures identified in the Sloan Digital Sky Survey (SDSS),
Granett et al. (2008a, Gr08) found a signal with strong significance and an
amplitude reportedly higher than expected within the LambdaCDM paradigm. We
revisit the analysis using our own robust protocol, and extend the study to the
two most recent and largest catalogues of voids publicly available. We quantify
and subtract the level of foreground contamination in the stacked images and
determine the contribution on the largest angular scales from the first
multipoles of the CMB. We obtain the radial temperature and photometry profiles
from the stacked images. Using a Monte Carlo approach, we computed the
statistical significance of the profiles for each catalogue and identified the
angular scale at which the signal-to-noise ratio (S/N) is maximum. We
essentially confirm the signal detection reported by Gr08, but for the other
two catalogues, a rescaling of the voids to the same size on the stacked image
is needed to find any significant signal (with a maximum at ~2.4 sigmas). This
procedure reveals that the photometry peaks at unexpectedly large angles in the
case of the Gr08 voids, in contrast to voids from other catalogues. Conversely,
the photometry profiles derived from the stacked voids of these other
catalogues contain small central hot spots of uncertain origin. We also stress
the importance of a posteriori selection effects that might arise when
intending to increase the S/N, and we discuss the possible impact of void
overlap and alignment effects. We argue that the interpretation in terms of an
iSW effect of any detected signal via the stacking method is far from obvious.Comment: 14 pages, 18 figures, 2 tables. Submitted, accepted and published in
A&A ; Minor changes to match the published version of the pape
Bias in Matter Power Spectra ?
We review the constraints given by the linear matter power spectra data on
cosmological and bias parameters, comparing the data from the PSCz survey
(Hamilton et al., 2000) and from the matter power spectrum infered by the study
of Lyman alpha spectra at z=2.72 (Croft et al., 2000). We consider
flat-- cosmologies, allowing , and to vary, and we
also let the two ratio factors and () vary independently. Using a simple
minimisation technique, we find confidence intervals on our parameters for each
dataset and for a combined analysis. Letting the 5 parameters vary freely gives
almost no constraints on cosmology, but requirement of a universal ratio for
both datasets implies unacceptably low values of and . Adding
some reasonable priors on the cosmological parameters demonstrates that the
power derived by the PSCz survey is higher by a factor compared to
the power from the Lyman forest survey.Comment: Accepted in A&
An Approximation to the Likelihood Function for Band-Power Estimates of CMB Anisotropies
Band-power estimates of cosmic microwave background fluctuations are now
routinely used to place constraints on cosmological parameters. For this to be
done in a rigorous fashion, the full likelihood function of band-power
estimates must be employed. Even for Gaussian theories, this likelihood
function is not itself Gaussian, for the simple reason that band-powers measure
the {\em variance} of the random sky fluctuations. In the context of Gaussian
sky fluctuations, we use an ideal situation to motivate a general form for the
full likelihood function from a given experiment. This form contains only two
free parameters, which can be determined if the 68% and 95% confidence
intervals of the true likelihood function are known. The ansatz works
remarkably well when compared to the complete likelihood function for a number
of experiments. For application of this kind of approach, we suggest that in
the future both 68% and 95% (and perhaps also the 99.7%) confidence intervals
be given when reporting experimental results.Comment: Published versio
- …