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Register a new userComputing Non- Gaussian Maps of the CMB
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We discuss methods to compute maps of the CMB in models featuring active causal sources and in non-Gaussian models ofinflation. We show our large angle results as well as some preliminary results on small angles. We conclude by discussing on-going work.
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We analyze the BOOMERanG 2003 (B03) 145 GHz temperature map to constrain the amplitude of a non Gaussian, primordial contribution to CMB fluctuations. We perform a pixel space analysis restricted to a portion of the map chosen in view of high sensitivity, very low foreground contamination and tight control of systematic effects. We set up an estimator based on the three Minkowski functionals which relies on high quality simulated data, including non Gaussian CMB maps. We find good agreement with the Gaussian hypothesis and derive the first limits based on BOOMERanG data for the non linear coupling parameter f_NL as -300<f_NL<650 at 68% CL and -800<f_NL<1050 at 95% CL.
We present a new method based on the N-point probability distribution (pdf) to study non-Gaussianity in cosmic microwave background (CMB) maps. Likelihood and Bayesian estimation are applied to a local non-linear perturbed model up to third order, characterized by a linear term which is described by a Gaussian N-pdf, and a second and third order terms which are proportional to the square and the cube of the linear one. We also explore a set of model selection techniques (the Akaike and the Bayesian Information Criteria, the minimum description length, the Bayesian Evidence and the Generalized Likelihood Ratio Test) and their application to decide whether a given data set is better described by the proposed local non-Gaussian model, rather than by the standard Gaussian temperature distribution. As an application, we consider the analysis of the WMAP 5-year data at a resolution of around 2 degrees. At this angular scale (the Sachs-Wolfe regime), the non-Gaussian description proposed in this work defaults (under certain conditions) to an approximative local form of the weak non-linear coupling inflationary model (e.g. Komatsu & Spergel 2001) previously addressed in the literature. For this particular case, we obtain an estimation for the non-linear coupling parameter of -94 < F_nl < 154 at 95% CL. Equally, model selection criteria also indicate that the Gaussian hypothesis is favored against the particular local non-Gaussian model proposed in this work. This result is in agreement with previous findings obtained for equivalent non-Gaussian models and with different non-Gaussian estimators. However, our estimator based on the N-pdf is more efficient than previous estimators and, therefore, provides tighter constraints on the coupling parameter at degree angular resolution.
Searching for and charactering the non-Gaussianity (NG) of a given field has been a vital task in many fields of science, because we expect the consequences of different physical processes to carry different statistical properties. Here we propose a new general method of extracting non-Gaussian features in a given field, and then use simulated cosmic microwave background (CMB) as an example to demonstrate its power. In particular, we show its capability of detecting cosmic strings.
We present a method, based on the correlation function of excursion sets above a given threshold, to test the Gaussianity of the CMB temperature fluctuations in the sky. In particular, this method can be applied to discriminate between standard inflationary scenarios and those producing non-Gaussianity such as topological defects. We have obtained the normalized correlation of excursion sets, including different levels of noise, for 2-point probability density functions constructed from the Gaussian, chi_n^2 and Laplace 1-point probability density functions in two different ways. Considering subdegree angular scales, we find that this method can distinguish between different distributions even if the corresponding marginal probability density functions and/or the radiation power spectra are the same.
The forthcoming Planck experiment will provide high sensitivity polarization measurements that will allow us to further tighten the f_NL bounds from the temperature data. Monte Carlo simulations of non-Gaussian CMB maps have been used as a fundamental tool to characterize non-Gaussian signatures in the data, as they allow us to calibrate any statistical estimators and understand the effect of systematics, foregrounds and other contaminants. We describe an algorithm to generate high-angular resolution simulations of non-Gaussian CMB maps in temperature and polarization. We consider non-Gaussianities of the local type, for which the level of non-Gaussianity is defined by the dimensionless parameter, f_NL. We then apply the temperature and polarization fast cubic statistics recently developed by Yadav et al. to a set of non-Gaussian temperature and polarization simulations. We compare our results to theoretical expectations based on a Fisher matrix analysis, test the unbiasedness of the estimator, and study the dependence of the error bars on f_NL. All our results are in very good agreement with theoretical predictions, thus confirming the reliability of both the simulation algorithm and the fast cubic temperature and polarization estimator.
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