Testing non-Gaussianity in CMB Maps by Morphological Statistic

Details Testing non-Gaussianity in CMB Maps by Morphological Statistic Testing non-Gaussianity in CMB Maps by Morphological Statistic

2001-07-17

arxiv.org/abs/astro-ph/0107319v2

Mon.Not.Roy.Astron.Soc.331:865,2002

Astronomy and Astrophysics

Astrophysics

26 pages, 9 figures

Scientific paper

10.1046/j.1365-8711.2002.05248.x

The assumption of Gaussianity of the primordial perturbations plays an important role in modern cosmology. The most direct test of this hypothesis consists in testing Gaussianity of the CMB maps. Counting the pixels with the temperatures in given ranges and thus estimating the one point probability function of the field is the simplest of all the tests. Other usually more complex tests of Gaussianity generally use a great deal of the information already contained in the probability function. However, the most interesting outcome of such a test would be the signal of non-Gaussianity independent of the probability function. It is shown that the independent information has purely morphological character i.e. it depends on the geometry and topology of the level contours only. As an example we discuss in detail the quadratic model $v=u+\alpha (u^2-1)$ ($u$ is a Gaussian field with $\bar{u}=0$ and $=1$, $\alpha$ is a parameter) which may arise in slow-roll or two-field inflation models. We show that in the limit of small amplitude $\alpha$ the full information about the non-Gaussianity is contained in the probability function. If other tests are performed on this model they simply recycle the same information. A simple procedure allowing to assess the sensitivity of any statistics to the morphological information is suggested. We provide an analytic estimate of the statistical limit for detecting the quadratic non-Gaussianity $\a_c$ as a function of the map size in the ideal situation when the scale of the field is resolved. This estimate is in a good agreement with the results of the Monte Carlo simulations of $256^2$ and $1024^2$ maps. The effect of resolution on the detection quadratic non-Gaussianity is also briefly discussed.

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