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A Scaling Index Analysis of the WMAP three year data: Signatures of non-Gaussianities and Asymmetries in the CMB

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 Added by Christoph Raeth
 Publication date 2007
  fields Physics
and research's language is English




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Local scaling properties of the co-added foreground-cleaned three-year Wilkinson Microwave Anisotropy Probe (WMAP) data are estimated using weighted scaling indices. The scaling index method (SIM) is - for the first time - adapted and applied to the case of spherical symmetric spatial data. The results are compared with 1000 Monte Carlo simulations based on Gaussian fluctuations with a best fit $Lambda$CDM power spectrum and WMAP-like beam and noise properties. Statistical quantities based on the scaling indices, namely the moments of the distribution and probability-based measures are determined. We find for most of the test statistics significant deviations from the Gaussian hypothesis. We find pronounced asymmetries, which can be interpreted as a global lack of structure in the northern hemisphere, which is consistent with previous findings. Furthermore, we detect a localized anomaly in the southern hemisphere, which gives rise to highly significant signature for non-Gaussianity in the spectrum of scaling indices. We identify this signature as the cold spot, which was also already detected in the first year WMAP data. Our results provide further evidence for both the presence of non-Gaussianities and asymmetries in the WMAP three-year data. More detailed bandand year-wise analyses are needed to elucidate the origin of the detected anomalies. In either case the scaling indices provide powerful nonlinear statistics to analyse CMB maps.



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In the recent years, non-Gaussianity and statistical isotropy of the Cosmic Microwave Background (CMB) was investigated with various statistical measures, first and foremost by means of the measurements of the WMAP satellite. In this Review, we focus on the analyses that were accomplished with a measure of local type, the so-called Scaling Index Method (SIM). The SIM is able to detect structural characteristics of a given data set, and has proven to be highly valuable in CMB analysis. It was used for comparing the data set with simulations as well as surrogates, which are full sky maps generated by randomisation of previously selected features of the original map. During these investigations, strong evidence for non-Gaussianities as well as asymmetries and local features could be detected. In combination with the surrogates approach, the SIM detected the highest significances for non-Gaussianity to date.
We continue the analysis of non-Gaussianities in the CMB by means of the scaling index method (SIM, Raeth, Schuecker & Banday 2007) by applying this method on the 5-year WMAP data. We compare each of the results with 1000 Monte Carlo simulations mimicing the Gaussian properties of the best fit $Lambda CDM$-model. Based on the scaling indices, scale-dependent empirical probability distributions, moments of these distributions and $chi^2$-combinations of them are calculated, obtaining similar results as in the former analysis of the 3-year data: We derive evidence for non-Gaussianity with a probability of up to 97.3% for the mean when regarding the KQ75-masked full sky and summing up over all considered length scales by means of a diagonal $chi^2$-statistics. Looking at only the northern or southern hemisphere, we obtain up to 98.5% or 96.6%, respectively. For the standard deviation, these results appear as 95.6% for the full sky (99.7% north, 89.4% south) and for a $chi^2$-combination of both measurements as 97.4% (99.1% north, 95.5% south). By performing an analysis of rotated hemispheres, we detect an obvious asymmetry in the data. In addition to these investigations, we present a method of filling the mask with Gaussian noise to eliminate boundary effects caused by the mask. With the help of this technique, we identify several local features on the map, of which the most significant one turns out to be the well-known cold spot. When excluding all these spots from the analysis, the deviation from Gaussianity increases, which shows that the discovered local anomalies are not the reason of the global detection of non-Gaussianity, but actually were damping the deviations on average. Our analyses per band and per year suggest, however, that it is very unlikely that the detected anomalies are due to foreground effects.
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 perform a blind multi-component analysis of the WMAP 1 year foreground cleaned maps using SMICA (Spectral Matching Independent Component Analysis). We provide a new estimate of the CMB power spectrum as well as the amplitude of the CMB anisotropies across frequency channels. We show that the CMB anisotropies are compatible with temperature fluctuations as expected from the standard paradigm. The analysis also allows us to identify and separate a weak residual galactic emission present significantly in the Q-band outside of the Kp2 mask limits, and mainly concentrated at low galactic latitudes. We produce a map of this residual component by Wiener filtering using estimated parameters. The level of contamination of CMB data by this component is compatible with the WMAP team estimation of foreground residual contamination. In addition, the multi-component analysis allows us to estimate jointly the power spectrum of unresolved point source emission.
We present a model-independent investigation of the WMAP data with respect to scale- dependent non-Gaussianities (NGs) by employing the method of constrained randomization. For generating so-called surrogate maps a shuffling scheme is applied to the Fourier phases of the original data, which allows to test for the presence of higher order correlations (HOCs) on well-defined scales. Using scaling indices as test statistics we find highly significant signatures for non-Gaussianities when considering all scales. We test for NGs in the bands l = [2,20], l = [20,60], l = [60,120] and l = [120,300]. We find highly significant signatures for non-Gaussianities and ecliptic hemispherical asymmetries for l = [2, 20]. We also obtain highly significant deviations from Gaussianity for the band l = [120,300]. The result for the full l-range can be interpreted as a superposition of the signatures found in the bands l = [2, 20] and l = [120, 300]. We find remarkably similar results when analyzing different ILC-like maps. We perform a set of tests to investigate if the detected anomalies can be explained by systematics. While no test can convincingly rule out the intrinsic nature of the anomalies for the low l case, the ILC map making procedure and/or residual noise in the maps can also lead to NGs at small scales. Our investigations prove that there are phase correlations in the WMAP data of the CMB. In the absence of an explanation in terms of Galactic foregrounds or known systematic artefacts, the signatures at low l must so far be taken to be cosmological at high significance. These findings strongly disagree with predictions of isotropic cosmologies with single field slow roll inflation. The task is now to elucidate the origin of the phase correlations and to understand the physical processes leading to these scale-dependent non-Gaussianities - if systematics as cause for them must be ruled out.
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