CMB Maps (cmb + map)

Distribution by Scientific Domains
Physics and Astronomy100%

Selected Abstracts

Combining maximum-entropy and the Mexican hat wavelet to reconstruct the microwave sky

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2001
P. Vielva
We present a maximum-entropy method (MEM) and ,Mexican hat' wavelet (MHW) joint analysis to recover the different components of the microwave sky from simulated observations by the ESA Planck Surveyor satellite in a small patch of the sky . This combined method allows one to improve the CMB, Sunyaev,Zel'dovich and Galactic foregrounds separation achieved by the MEM technique alone. In particular, the reconstructed CMB map is free from any bright point-source contamination. The joint analysis also produces point-source catalogues at each Planck frequency that are more complete and accurate than those obtained by either method on its own. The results are especially improved at high frequencies where infrared galaxies dominate the point-source contribution. Although this joint technique has been performed on simulated Planck data, it could easily be applied to other multifrequency CMB experiments, such as the forthcoming NASA MAP satellite or the recently-performed BOOMERANG and MAXIMA experiments. [source]

Foreground removal from Planck Sky Model temperature maps using a MLP neural network

ASTRONOMISCHE NACHRICHTEN, Issue 8 2009
H.U. Nørgaard-Nielsen
Abstract Unfortunately, the Cosmic Microwave Background (CMB) radiation is contaminated by emission originating in the Milky Way (synchrotron, free-free and dust emission). Since the cosmological information is statistically in nature, it is essential to remove this foreground emission and leave the CMB with no systematic errors. To demonstrate the feasibility of a simple multilayer perceptron (MLP) neural network for extracting the CMB temperature signal, we have analyzed a specific data set, namely the Planck Sky Model maps, developed for evaluation of different component separation methods before including them in the Planck data analysis pipeline. It is found that a MLP neural network can provide a CMB map of about 80 % of the sky to a very high degree uncorrelated with the foreground components. Also the derived power spectrum shows little evidence for systematic errors (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

Error analysis in cross-correlation of sky maps: application to the Integrated Sachs,Wolfe detection

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 4 2007
Anna Cabré
ABSTRACT Constraining cosmological parameters from measurements of the Integrated Sachs,Wolfe effect requires developing robust and accurate methods for computing statistical errors in the cross-correlation between maps. This paper presents a detailed comparison of such error estimation applied to the case of cross-correlation of cosmic microwave background (CMB) and large-scale structure data. We compare theoretical models for error estimation with Monte Carlo simulations where both the galaxy and the CMB maps vary around a fiducial autocorrelation and cross-correlation model which agrees well with the current concordance , cold dark matter cosmology. Our analysis compares estimators both in harmonic and configuration (or real) space, quantifies the accuracy of the error analysis and discusses the impact of partial sky survey area and the choice of input fiducial model on dark energy constraints. We show that purely analytic approaches yield accurate errors even in surveys that cover only 10 per cent of the sky and that parameter constraints strongly depend on the fiducial model employed. Alternatively, we discuss the advantages and limitations of error estimators that can be directly applied to data. In particular, we show that errors and covariances from the jackknife method agree well with the theoretical approaches and simulations. We also introduce a novel method in real space that is computationally efficient and can be applied to real data and realistic survey geometries. Finally, we present a number of new findings and prescriptions that can be useful for analysis of real data and forecasts, and present a critical summary of the analyses done to date. [source]

Foreground contamination of the WMAP CMB maps from the perspective of the matched circle test

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2006
H. Then
ABSTRACT Wilkinson Microwave Anisotropy Probe has provided cosmic microwave background (CMB) maps of the full sky. The raw data are subject to foreground contamination, in particular near to the Galactic plane. Foreground-cleaned maps have been derived, e.g. the internal linear combination map of Bennett et al., and the reduced foreground TOH map of Tegmark et al. Using S statistics, we examine whether residual foreground contamination is left over in the foreground-cleaned maps. In particular, we specify which parts of the foreground-cleaned maps are sufficiently accurate for the circle-in-the-sky signature. We generalize the S statistic, called D statistic, such that the circle test can deal with CMB maps in which the contaminated regions of the sky are excluded with masks. [source]

Scalar statistics on the sphere: application to the cosmic microwave background

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 1 2005
C. Monteserín
ABSTRACT A method to compute several scalar quantities of cosmic microwave background (CMB) maps on the sphere is presented. We consider here four type of scalars: the Hessian matrix scalars, the distortion scalars, the gradient-related scalars and the curvature scalars. Such quantities are obtained directly from the spherical harmonic coefficients a,m of the map. We also study the probability density function of these quantities for the case of a homogeneous and isotropic Gaussian field, which are functions of the power spectrum of the initial field. From these scalars it is possible to construct a new set of scalars which are independent of the power spectrum of the field. We test our results using simulations and find good agreement between the theoretical probability density functions and those obtained from simulations. Therefore, these quantities are proposed to investigate the presence of non-Gaussian features in CMB maps. Finally, we show how to compute the scalars in the presence of anisotropic noise and realistic masks. [source]