Harnack Inequality for a Subelliptic PDE in nondivergence form

We consider subelliptic equations in non divergence form of the type $Lu = \sum a_{ij} X_jX_iu=0$, where $X_j$ are the Grushin vector fields, and the matrix coefficient is uniformly elliptic. We obtain a scale invariant Harnack's inequality on the $X_j$'s CC balls for nonnegative solutions under the only assumption that the ratio between the maximum and minimum eigenvalues of the coefficient matrix is bounded. In the paper we first prove a weighted Aleksandrov Bakelman Pucci estimate, and then we show a critical density estimate, the double ball property and the power decay property. Once this is established, Harnack's inequality follows directly from the axiomatic theory developed by Di Fazio, Gutierrez and Lanconelli in [6]

Tight bounds for LDPC and LDGM codes under MAP decoding

A new method for analyzing low density parity check (LDPC) codes and low density generator matrix (LDGM) codes under bit maximum a posteriori probability (MAP) decoding is introduced. The method is based on a rigorous approach to spin glasses developed by Francesco Guerra. It allows to construct lower bounds on the entropy of the transmitted message conditional to the received one. Based on heuristic statistical mechanics calculations, we conjecture such bounds to be tight. The result holds for standard irregular ensembles when used over binary input output symmetric channels. The method is first developed for Tanner graph ensembles with Poisson left degree distribution. It is then generalized to `multi-Poisson' graphs, and, by a completion procedure, to arbitrary degree distribution.Comment: 28 pages, 9 eps figures; Second version contains a generalization of the previous resul

Estimating Random Variables from Random Sparse Observations

Let X_1,...., X_n be a collection of iid discrete random variables, and Y_1,..., Y_m a set of noisy observations of such variables. Assume each observation Y_a to be a random function of some a random subset of the X_i's, and consider the conditional distribution of X_i given the observations, namely \mu_i(x_i)\equiv\prob\{X_i=x_i|Y\} (a posteriori probability). We establish a general relation between the distribution of \mu_i, and the fixed points of the associated density evolution operator. Such relation holds asymptotically in the large system limit, provided the average number of variables an observation depends on is bounded. We discuss the relevance of our result to a number of applications, ranging from sparse graph codes, to multi-user detection, to group testing.Comment: 22 pages, 1 eps figures, invited paper for European Transactions on Telecommunication

Turbo codes: the phase transition

Turbo codes are a very efficient method for communicating reliably through a noisy channel. There is no theoretical understanding of their effectiveness. In [1] they are mapped onto a class of disordered spin models. The analytical calculations concerning these models are reported here. We prove the existence of a no-error phase and compute its local stability threshold. As a byproduct, we gain some insight into the dynamics of the decoding algorithm.Comment: 26 pages, 3 eps figure

Scale versus heterogeneity: how the economy affects public support for the EU

This paper proposes a simple political economic model of public opinion support for the EU, drawing on the recent economic literature on integration processes. The basic element is the existence of a trade-off between the benefits of centralisation and the costs of harmonising policies in the presence of heterogeneous preferences among countries. Subsequently we test the model with panel data on the EU member countries. The findings broadly confirm that economic benefits and costs do consistently shape citizens’ attitude towards EU membership. Our analysis may thus shed some light also on the awkward process of ratification of the European Constitution.Economic integration; European Union; Panel Data; Political Economy; Public Opinion