No Arabic abstract
We present an analysis of the foreground emission present in the WMAP 3-year data as determined by the method of Independent Component Analysis. We derived coupling coefficients between the WMAP data and foreground templates which are then used to infer the spectral behaviour for three foreground components -- synchrotron, anomalous dust-correlated emission and free-free. For the first two components, we find values consistent with previous results although slightly steeper. We confirm the inconsistency in the scaling between the Ha template and free-free emission at K- and Ka-bands where an electron temperature of ~ 4000 K is indicated. We also see evidence of significantly flatter spectral behaviour to higher frequencies than expected theoretically and previously noted by Dobler et al.(2008a), but only when analysing the Kp2 sky coverage. We further apply FASTICA iteratively, using data pre-cleaned using foreground templates scaled to the WMAP frequencies by coupling coefficients determined by a prior FASTICA analysis. This multi-frequency analysis allows us to determine the presence of residual foreground emission not traced by the templates. We confirm the existence of a component spatially distributed along the Galactic plane and particularly enhanced near the center (the WMAP haze). This emission is less extended when using the WMAP K-Ka data as the synchrotron template confirming that it can be considered a better template for foreground cleaning of the WMAP data. However its use complicates the physical interpretation of the nature of the foreground emission and residuals. since it contains a mixture of several, physically distinct emission mechanisms.
We present a detailed analysis on the phases of the WMAP foregrounds (synchrotron, free-free and dust emission) of the WMAP K-W bands in order to estimate the significance of the variation of the spectral indices at different components. We first extract the spectral-index varying signals by assuming that the invariant part among different frequency bands have 100% cross-correlation of phases. We then use the minimization of variance, which is normally used for extracting the CMB signals, to extract the frequency independent signals. Such a common signal in each foreground component could play a significant role for any kind of component separation methods, because the methods cannot discriminate frequency independent foregrounds and CMB.
We present a full-sky model of polarized Galactic microwave emission based on three years of observations by the Wilkinson Microwave Anisotropy Probe (WMAP) at frequencies from 23 to 94 GHz. The model compares maps of the Stokes Q and U components from each of the 5 WMAP frequency bands in order to separate synchrotron from dust emission, taking into account the spatial and frequency dependence of the synchrotron and dust components. This simple two-component model of the interstellar medium accounts for at least 97% of the polarized emission in the WMAP maps of the microwave sky. Synchrotron emission dominates the polarized foregrounds at frequencies below 50 GHz, and is comparable to the dust contribution at 65 GHz. The spectral index of the synchrotron component, derived solely from polarization data, is -3.2 averaged over the full sky, with a modestly flatter index on the Galactic plane. The synchrotron emission has mean polarization fraction 2--4% in the Galactic plane and rising to over 20% at high latitude, with prominent features such as the North Galactic Spur more polarized than the diffuse component. Thermal dust emission has polarization fraction 1% near the Galactic center, rising to 6% at the anti-center. Diffuse emission from high-latitude dust is also polarized with mean fractional polarization 0.036 +/- 0.011.
We constrain the amplitude of primordial non-Gaussianity in the CMB data taking into account the presence of foreground residuals in the maps. We generalise the needlet bispectrum estimator marginalizing over the amplitudes of thermal dust, free-free and synchrotron templates. We apply our procedure to WMAP 5 year data, finding fNL= 38pm 47 (1 sigma), while the analysis without marginalization provides fNL= 35pm 42. Splitting the marginalization over each foreground separately, we found that the estimates of fNL are positively cross correlated of 17%, 12% with the dust and synchrotron respectively, while a negative cross correlation of about -10% is found for the free-free component.
We present an application of the fast Independent Component Analysis (FastICA) to the WMAP 3yr data with the goal of extracting the CMB signal. We evaluate the confidence of our results by means of Monte Carlo simulations including CMB, foreground contaminations and instrumental noise specific of each WMAP frequency band. We perform a complete analysis involving all or a subset of the WMAP channels in order to select the optimal combination for CMB extraction, using the frequency scaling of the reconstructed component as a figure of merit. We found that the combination KQVW provides the best CMB frequency scaling, indicating that the low frequency foreground contamination in Q, V and W bands is better traced by the emission in the K band. The CMB angular power spectrum is recovered up to the degree scale, it is consistent within errors for all WMAP channel combination considered, and in close agreement with the WMAP 3yr results. We perform a statistical analysis of the recovered CMB pattern, and confirm the sky asymmetry reported in several previous works with independent techniques.
We present a new method based on phase analysis for the Galaxy and foreground component separation from the cosmic microwave background (CMB) signal. This method is based on a prevailing assumption that the phases of the underlying CMB signal should have no or little correlation with those of the foregrounds. This method takes into consideration all the phases of each multipole mode (l <= 50, -l <= m <=l) from the whole sky without galactic cut, masks or any dissection of the whole sky into disjoint regions. We use cross correlation of the phases to illustrate that significant correlations of the foregrounds manifest themselves in the phases of the WMAP 5 frequency bands, which are used for separation of the CMB from the signals. Our final phase-cleaned CMB map has the angular power spectrum in agreement with both the WMAP result and that from Tegmark, de Oliveira-Costa and Hamilton (TOH), the phases of our derived CMB signal, however, are slightly different from those of the WMAP Internal Linear Combination map and the TOH map.