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Register a new userNew method of extracting non-Gaussian signals in the CMB
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Jiun-Huei Proty Wu
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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.
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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 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.
The method of weighted addition of multi-frequency maps, more commonly referred to as {it Internal Linear Combination} (ILC), has been extensively employed in the measurement of cosmic microwave background (CMB) anisotropies and its secondaries along with similar application in 21cm data analysis. Here we argue and demonstrate that ILC methods can also be applied to data from absolutely-calibrated CMB experiments to extract average-sky signals in addition to the conventional CMB anisotropies. The performance of the simple ILC method is, however, limited, but can be significantly improved by adding constraints informed by physics and existing empirical information. In recent work, a moment description has been introduced as a technique of carrying out high precision modeling of foregrounds in the presence of inevitable averaging effects. We combine these two approaches to construct a heavily constrained form of the ILC, dubbed milc, which can be used to recover tiny monopolar spectral distortion signals in the presence of realistic foregrounds and instrumental noise. This is a first demonstration for measurements of the monopolar and anisotropic spectral distortion signals using ILC and extended moment methods. We also show that CMB anisotropy measurements can be improved, reducing foreground biases and signal uncertainties when using the milc. While here we focus on CMB spectral distortions, the scope extends to the 21cm monopole signal and $B$-mode analysis. We briefly discuss augmentations that need further study to reach the full potential of the method.
We search the BOOMERanG maps of the anisotropy of the Cosmic Microwave Background (CMB) for deviations from gaussianity. In this paper we focus on analysis techniques in pixel-space, and compute skewness, kurtosis and Minkowski functionals for the BOOMERanG maps and for gaussian simulations of the CMB sky. We do not find any significant deviation from gaussianity in the high galactic latitude section of the 150 GHz map. We do find deviations from gaussianity at lower latitudes and at 410 GHz, and we ascribe them to Galactic dust contamination. Using non-gaussian simulations of instrumental systematic effects, of foregrounds, and of sample non-gaussian cosmological models, we set upper limits to the non-gaussian component of the temperature field in the BOOMERanG maps. For fluctuations distributed as a 1 DOF $chi^2$ mixed to the main gaussian component our upper limits are in the few % range.
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.
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