Strictly and asymptotically scale-invariant probabilistic models of NN correlated binary random variables having {\em q}--Gaussians as N→∞N\to \infty limiting distributions

In order to physically enlighten the relationship between {\it $q$--independence} and {\it scale-invariance}, we introduce three types of asymptotically scale-invariant probabilistic models with binary random variables, namely (i) a family, characterized by an index $\nu=1,2,3,...$, unifying the Leibnitz triangle ($\nu=1$) and the case of independent variables ($\nu\to\infty$); (ii) two slightly different discretizations of $q$--Gaussians; (iii) a special family, characterized by the parameter $\chi$, which generalizes the usual case of independent variables (recovered for $\chi=1/2$). Models (i) and (iii) are in fact strictly scale-invariant. For models (i), we analytically show that the $N \to\infty$ probability distribution is a $q$--Gaussian with $q=(\nu -2)/(\nu-1)$. Models (ii) approach $q$--Gaussians by construction, and we numerically show that they do so with asymptotic scale-invariance. Models (iii), like two other strictly scale-invariant models recently discussed by Hilhorst and Schehr (2007), approach instead limiting distributions which are {\it not} $q$--Gaussians. The scenario which emerges is that asymptotic (or even strict) scale-invariance is not sufficient but it might be necessary for having strict (or asymptotic) $q$--independence, which, in turn, mandates $q$--Gaussian attractors.Comment: The present version is accepted for publication in JSTA

Functional-differential equations for FqF_q%-transforms of qq-Gaussians

In the paper the question - Is the q-Fourier transform of a q-Gaussian a q'-Gaussian (with some q') up to a constant factor? - is studied for the whole range of $q\in (-\infty, 3)$. This question is connected with applicability of the q-Fourier transform in the study of limit processes in nonextensive statistical mechanics. We prove that the answer is affirmative if and only if q > 1, excluding two particular cases of q<1, namely, q = 1/2 and q = 2/3, which are also out of the theory valid for q \ge 1. We also discuss some applications of the q-Fourier transform to nonlinear partial differential equations such as the porous medium equation.Comment: 14 pages A new section on a related solution of the porous medium equation in comparison with the previous version has been introduc

Deviation from Gaussianity in the cosmic microwave background temperature fluctuations

Recent measurements of the temperature fluctuations of the cosmic microwave background (CMB) radiation from the WMAP satellite provide indication of a non-Gaussian behavior. Although the observed feature is small, it is detectable and analyzable. Indeed, the temperature distribution P^{CMB}(Delta T) of these data can be quite well fitted by the anomalous probability distribution emerging within nonextensive statistical mechanics, based on the entropy S_q = k (1 - \int dx [P(x)]^q)/(q - 1) (where in the limit case q -> 1 we obtain the Boltzmann-Gibbs entropy S_1 = - k \int dx P(x) ln[P(x)]). For the CMB frequencies analysed, \nu= 40.7, 60.8, and 93.5 GHz, P^{CMB}(Delta T) is well described by P_q(Delta T) \propto 1/[1 + (q-1) B(\nu) (Delta T)^2]^{1/(q-1)}, with q = 1.04 \pm 0.01, the strongest non-Gaussian contribution coming from the South-East sector of the celestial sphere. Moreover, Monte Carlo simulations exclude, at the 99% confidence level, P_1(Delta T) \propto e^{- B(\nu) (Delta T)^2} to fit the three-year WMAP data.Comment: 6 pages, 1 figur