We present an upgraded combined estimator, based on Minkowski Functionals and Neural Networks, with excellent performance in detecting primordial non-Gaussianity in simulated maps that also contain a weighted mixture of Galactic contaminations, besid
es real pixels noise from Planck cosmic microwave background radiation data. We rigorously test the efficiency of our estimator considering several plausible scenarios for residual non-Gaussianities in the foreground-cleaned Planck maps, with the intuition to optimize the training procedure of the Neural Network to discriminate between contaminations with primordial and secondary non-Gaussian signatures. We look for constraints of primordial local non-Gaussianity at large angular scales in the foreground-cleaned Planck maps. For the $mathtt{SMICA}$ map we found ${f}_{rm ,NL} = 33 pm 23$, at $1sigma$ confidence level, in excellent agreement with the WMAP-9yr and Planck results. In addition, for the other three Planck maps we obtain similar constraints with values in the interval ${f}_{rm ,NL} in [33, 41]$, concomitant with the fact that these maps manifest distinct features in reported analyses, like having different pixels noise intensities.
[Abridged.] It is conceivable that no single statistical estimator can be sensitive to all forms and levels of non-Gaussianity that may be present in observed CMB data. In recent works a statistical procedure based upon the calculation of the skewnes
s and kurtosis of the patches of CMB sky-sphere has been proposed and used to find out significant large-angle deviation from Gaussianity in the foreground-reduced WMAP maps. Here we address the question as to how the analysis of Gaussianity of WMAP maps is modified if the foreground-cleaned Planck maps are used, therefore extending and complementing the previous analyses in several regards. We carry out a new analysis of Gaussianity with the available nearly full-sky foreground-cleaned Planck maps. As the foregrounds are cleaned through different component separation procedures, each of the resulting Planck maps is then tested for Gaussianity. We determine quantitatively the effects for Gaussianity of masking the foreground-cleaned Planck maps with the INPMASK, VALMASK, and U73 Planck masks. We show that although the foreground-cleaned Planck maps present significant deviation from Gaussianity of different degrees when the less severe INPMASK and VALMASK are used, they become consistent with Gaussianity as detected by our indicator $S$ when masked with the union U73 mask. A slightly smaller consistency with Gaussianity is found when the $K$ indicator is employed, which seems to be associated with large-angle anomalies reported by the Planck team. Finally, we examine the robustness of the Gaussianity analyses with respect to the noise pixels as given by the Planck team, and show that no appreciable changes arise when is incorporated into the maps. The results of our analyses provide important information about the suitability of the foreground-cleaned Planck maps as Gaussian reconstructions of the CMB sky.
The extensive search for deviations from Gaussianity in cosmic microwave background radiation (CMB) data is very important due to the information about the very early moments of the universe encoded there. Recent analyses from Planck CMB data do not
exclude the presence of non-Gaussianity of small amplitude, although they are consistent with the Gaussian hypothesis. The use of different techniques is essential to provide information about types and amplitudes of non-Gaussianities in the CMB data. In particular, we find interesting to construct an estimator based upon the combination of two powerful statistical tools that appears to be sensitive enough to detect tiny deviations from Gaussianity in CMB maps. This estimator combines the Minkowski functionals with a Neural Network, maximizing a tool widely used to study non-Gaussian signals with a reinforcement of another tool designed to identify patterns in a data set. We test our estimator by analyzing simulated CMB maps contaminated with different amounts of local primordial non-Gaussianity quantified by the dimensionless parameter fNL. We apply it to these sets of CMB maps and find gtrsim 98% of chance of positive detection, even for small intensity local non-Gaussianity like fNL = 38 +/- 18, the current limit from Planck data for large angular scales. Additionally, we test the suitability to distinguish between primary and secondary non-Gaussianities and find out that our method successfully classifies ~ 95% of the tested maps. Furthermore, we analyze the foreground-cleaned Planck maps obtaining constraints for non-Gaussianity at large-angles that are in good agreement with recent constraints. Finally, we also test the robustness of our estimator including cut-sky masks and realistic noise maps measured by Planck, obtaining successful results as well.
A convincing detection of primordial non-Gaussianity in the cosmic background radiation (CMB) is essential to probe the physics of the early universe. Since a single statistical estimator can hardly be suitable to detect the various possible forms of
non-Gaussianity, it is important to employ different statistical indicators to study non-Gaussianity of CMB. This has motivated the proposal of a number statistical tools, including two large-angle indicators based on skewness and kurtosis of spherical caps of CMB sky-sphere. Although suitable to detect fairly large non-Gaussianity they are unable to detect non-Gaussianity within the Planck bounds, and exhibit power spectra with undesirable oscillation pattern. Here we use several thousands simulated CMB maps to examine interrelated problems regarding advances of these spherical patches procedures. We examine whether a change in the choice of the patches could enhance the sensitivity of the procedures well enough to detect large-angle non-Gaussianity within the Planck bounds. To this end, a new statistical procedure with non-overlapping cells is proposed and its capability is established. We also study whether this new procedure is capable to smooth out the undesirable oscillation pattern in the skewness and kurtosis power spectra of the spherical caps procedure. We show that the new procedure solves this problem, making clear this unexpected power spectra pattern does not have a physical origin, but rather presumably arises from the overlapping obtained with the spherical caps approach. Finally, we make a comparative analysis of this new statistical procedure with the spherical caps routine, determine their lower bounds for non-Gaussianity detection, and make apparent their relative strength and sensitivity.
A detection or nondetection of primordial non-Gaussianity by using the cosmic microwave background radiation (CMB) offers a way of discriminating inflationary scenarios and testing alternative models of the early universe. This has motivated the cons
iderable effort that has recently gone into the study of theoretical features of primordial non-Gaussianity and its detection in CMB data. Among such attempts to detect non-Gaussianity, there is a procedure that is based upon two indicators constructed from the skewness and kurtosis of large-angle patches of CMB maps, which have been proposed and used to study deviation from Gaussianity in the WMAP data. Simulated CMB maps equipped with realistic primordial non-Gaussianity are essential tools to test the viability of non-Gaussian indicators in practice, and also to understand the effect of systematics, foregrounds and other contaminants. In this work we extend and complement the results of our previous works by performing an analysis of non-Gaussianity of the high-angular resolution simulated CMB temperature maps endowed with non-Gaussianity of the local type, for which the level of non-Gaussianity is characterized by the dimensionless parameter $f_{rm NL}^{rm local}$
[Abridged] In recent works we have proposed two new large-angle non-Gaussianity indicators based on skewness and kurtosis of patches of CMB sky-sphere, and used them to find out significant deviation from Gaussianity in frequency bands and foreground
-reduced CMB maps. Simulated CMB maps with assigned type and amplitude of primordial non-Gaussianity are important tools to determine the strength, sensitivity and limitations of non-Gaussian estimators. Here we investigate whether and to what extent our non-Gaussian indicators have sensitivity to detect non-Gaussianity of local type, particularly with amplitude within the seven-year WMAP bounds. We make a systematic study by employing our statistical tools to generate maps of skewness and kurtosis from several thousands of simulated maps equipped with non-Gaussianity of local type of various amplitudes. We show that our indicators can be used to detect large-angle local-type non-Gaussianity only for relatively large values of the non-linear parameter $f_{rm NL}^{rm local}$. Thus, our indicators have not enough sensitivity to detect deviation from Gaussianity with the non-linear parameter within the seven-year WMAP bounds. This result along with the outcomes of frequency bands and foreground-reduced analyses suggest that non-Gaussianity captured in the previous works by our indicators is not of primordial origin, although it might have a primordial component. We have also made a comparative study of non-Gaussianity of simulated maps and of the full-sky WMAP foreground-reduced seven-year ILC-7yr map. An outcome of this analysis is that the level of non-Gaussianity of ILC-7yr map is higher than that of the simulated maps for $f_{rm NL}^{rm local}$ within WMAP bounds. This provides quantitative indications on the suitability of the ILC-7yr map as a Gaussian reconstruction of the full-sky CMB.
We investigate the large-scale angular distribution of the short-Gamma ray bursts (SGRBs) from BATSE experiment, using a new coordinates-free method. The analyses performed take into account the angular correlations induced by the non-uniform sky exp
osure during the experiment, and the uncertainty in the measured angular coordinates. Comparising the large-scale angular correlations from the data with those expected from simulations using the exposure function we find similar features. Additionally, confronting the large-angle correlations computed from the data with those obtained from simulated maps produced under the assumption of statistical isotropy we found that they are incompatible at 95% confidence level. However, such differences are restricted to the angular scales 36o - 45o, which are likely to be due to the non-uniform sky exposure. This result strongly suggests that the set of SGRBs from BATSE are intrinsically isotropic. Moreover, we also investigated a possible large-angle correlation of these data with the supergalactic plane. No evidence for such large-scale anisotropy was found.
