Large deviation principles for nongradient weakly asymmetric stochastic lattice gases

We consider a lattice gas on the discrete d-dimensional torus $(\mathbb{Z}/N\mathbb{Z})^d$ with a generic translation invariant, finite range interaction satisfying a uniform strong mixing condition. The lattice gas performs a Kawasaki dynamics in the presence of a weak external field E/N. We show that, under diffusive rescaling, the hydrodynamic behavior of the lattice gas is described by a nonlinear driven diffusion equation. We then prove the associated dynamical large deviation principle. Under suitable assumptions on the external field (e.g., E constant), we finally analyze the variational problem defining the quasi-potential and characterize the optimal exit trajectory. From these results we deduce the asymptotic behavior of the stationary measures of the stochastic lattice gas, which are not explicitly known. In particular, when the external field E is constant, we prove a stationary large deviation principle for the empirical density and show that the rate function does not depend on E.Comment: Published in at http://dx.doi.org/10.1214/11-AAP805 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Large deviations of the empirical flow for continuous time Markov chains

We consider a continuous time Markov chain on a countable state space and prove a joint large deviation principle for the empirical measure and the empirical flow, which accounts for the total number of jumps between pairs of states. We give a direct proof using tilting and an indirect one by contraction from the empirical process.Comment: Minor revision, to appear on Annales de l'Institut Henri Poincare (B) Probability and Statistic

Large deviations for a stochastic model of heat flow

We investigate a one dimensional chain of $2N$ harmonic oscillators in which neighboring sites have their energies redistributed randomly. The sites $-N$ and $N$ are in contact with thermal reservoirs at different temperature $\tau_-$ and $\tau_+$. Kipnis, Marchioro, and Presutti \cite{KMP} proved that this model satisfies {}Fourier's law and that in the hydrodynamical scaling limit, when $N \to \infty$, the stationary state has a linear energy density profile $\bar \theta(u)$, $u \in [-1,1]$. We derive the large deviation function $S(\theta(u))$ for the probability of finding, in the stationary state, a profile $\theta(u)$ different from $\bar \theta(u)$. The function $S(\theta)$ has striking similarities to, but also large differences from, the corresponding one of the symmetric exclusion process. Like the latter it is nonlocal and satisfies a variational equation. Unlike the latter it is not convex and the Gaussian normal fluctuations are enhanced rather than suppressed compared to the local equilibrium state. We also briefly discuss more general model and find the features common in these two and other models whose $S(\theta)$ is known.Comment: 28 pages, 0 figure

An analytical framework to nowcast well-being using mobile phone data

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly "nowcast" the well-being and the socio-economic development of a territory

Large deviations for diffusions: Donsker-Varadhan meet Freidlin-Wentzell

We consider a diffusion process on $\mathbb R^n$ and prove a large deviation principle for the empirical process in the joint limit in which the time window diverges and the noise vanishes. The corresponding rate function is given by the expectation of the Freidlin-Wentzell functional per unit of time. As an application of this result, we obtain a variational representation of the rate function for the Gallavotti-Cohen observable in the small noise and large time limits

Congenital Chagas disease in a Bolivian newborn in Bergamo (Italy)

Chagas disease (CD) is an uncommon disease in Europe. Its epidemiology has changed because of mass migration from Latin America to Europe. Herein we describe a congenital case of CD in a Bolivian newborn in Bergamo, the main city of residence for the Bolivian community in Italy. At delivery, serological analyses evidenced IgG antibodies against Trypanosoma cruzi both in the child and mother, as expected. Hemoscopic analyses on peripheral blood were repeatedly negative during the first months of life. Eventually, thanks to T. cruzi Real Time polymerase chain reaction (RT-PCR) positivity on peripheral blood and development of progressive anemia in the following weeks, congenital Chagas disease was diagnosed and benznidazole-based therapy started. A progressive antibodies' index decrease was observed till negativity (306 days apart). RT-PCR was negative at the end of treatment. Our case is instructive and management of congenital CD is discussed from the perspective of a non-endemic country

Fronteras en movimiento. Migraciones hacia la Unión Europea en el contexto mediterráneo

Ricard Zapata-Barrero y Xavier Ferrer-Gallardo (eds.). Barcelona: Edicions Bellaterra, 2012, 345 pp

Flows, currents, and cycles for Markov chains: Large deviation asymptotics

We consider a continuous time Markov chain on a countable state space. We prove a joint large deviation principle (LDP) of the empirical measure and current in the limit of large time interval. The proof is based on results on the joint large deviations of the empirical measure and flow obtained in Bertini et al. (in press). By improving such results we also show, under additional assumptions, that the LDP holds with the strong L1 topology on the space of currents. We deduce a general version of the Gallavotti–Cohen (GC) symmetry for the current field and show that it implies the so-called fluctuation theorem for the GC functional. We also analyze the large deviation properties of generalized empirical currents associated to a fundamental basis in the cycle space, which, as we show, are given by the first class homological coefficients in the graph underlying the Markov chain. Finally, we discuss in detail some examples

Geography of science: competitiveness and inequality

We characterize the temporal dynamics of Scientific Fitness, as defined by the Economic Fitness and Complexity (EFC) framework, and R&D expenditures at the geographic scale of nations. Our analysis highlights common patterns across similar research systems, and shows how develop-ing nations (China in particular) are quickly catching up with the developed world. This paints the picture of a general growth of scientific and technical capabilities of nations induced by the spreading of information typical of the scientific environment. Shifting the focus of the analysis to the regional level, we find that even developed nations display a considerable level of inequal-ity in the Scientific Fitness of their internal regions. Further, we assess comparatively how the competitiveness of each geographic region is distributed over the spectrum of research sectors. Overall, the Scientific Fitness represents the first high quality estimation of the scientific strength of nations and regions, opening new policy-making applications for better allocating resources, filling inequality gaps and ultimately promoting innovation