Statistical Signs of Social Influence on Suicides

Certain currents in sociology consider society as being composed of autonomous individuals with independent psychologies. Others, however, deem our actions as strongly influenced by the accepted standards of social behavior. The later view was central to the positivist conception of society when in 1887 \'Emile Durkheim published his monograph Suicide (Durkheim, 1897). By treating the suicide as a social fact, Durkheim envisaged that suicide rates should be determined by the connections (or the lack of them) between people and society. Under the same framework, Durkheim considered that crime is bound up with the fundamental conditions of all social life and serves a social function. In this sense, and regardless of its extremely deviant nature, crime events are somehow capable to release certain social tensions and so have a purging effect in society. The social effect on the occurrence of homicides has been previously substantiated (Bettencourt et al., 2007; Alves et al., 2013), and confirmed here, in terms of a superlinear scaling relation: by doubling the population of a Brazilian city results in an average increment of 135 % in the number of homicides, rather than the expected isometric increase of 100 %, as found, for example, for the mortality due to car crashes. Here we present statistical signs of the social influence on the suicide occurrence in cities. Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, with allometric power-law exponents, $\beta = 0.836 \pm 0.009$ and $0.870 \pm 0.002$, for all cities in Brazil and US, respectively. The fact that the frequency of suicides is disproportionately small for larger cities reveals a surprisingly beneficial aspect of living and interacting in larger and more complex social networks.Comment: 7 pages, 4 figure

Non-Local Product Rules for Percolation

Despite original claims of a first-order transition in the product rule model proposed by Achlioptas et al. [Science 323, 1453 (2009)], recent studies indicate that this percolation model, in fact, displays a continuous transition. The distinctive scaling properties of the model at criticality, however, strongly suggest that it should belong to a different universality class than ordinary percolation. Here we introduce a generalization of the product rule that reveals the effect of non-locality on the critical behavior of the percolation process. Precisely, pairs of unoccupied bonds are chosen according to a probability that decays as a power-law of their Manhattan distance, and only that bond connecting clusters whose product of their sizes is the smallest, becomes occupied. Interestingly, our results for two-dimensional lattices at criticality shows that the power-law exponent of the product rule has a significant influence on the finite-size scaling exponents for the spanning cluster, the conducting backbone, and the cutting bonds of the system. In all three cases, we observe a continuous variation from ordinary to (non-local) explosive percolation exponents.Comment: 5 pages, 4 figure

Canalizing Kauffman networks: non-ergodicity and its effect on their critical behavior

Boolean Networks have been used to study numerous phenomena, including gene regulation, neural networks, social interactions, and biological evolution. Here, we propose a general method for determining the critical behavior of Boolean systems built from arbitrary ensembles of Boolean functions. In particular, we solve the critical condition for systems of units operating according to canalizing functions and present strong numerical evidence that our approach correctly predicts the phase transition from order to chaos in such systems.Comment: to be published in PR

Transport on exploding percolation clusters

We propose a simple generalization of the explosive percolation process [Achlioptas et al., Science 323, 1453 (2009)], and investigate its structural and transport properties. In this model, at each step, a set of q unoccupied bonds is randomly chosen. Each of these bonds is then associated with a weight given by the product of the cluster sizes that they would potentially connect, and only that bond among the q-set which has the smallest weight becomes occupied. Our results indicate that, at criticality, all finite-size scaling exponents for the spanning cluster, the conducting backbone, the cutting bonds, and the global conductance of the system, change continuously and significantly with q. Surprisingly, we also observe that systems with intermediate values of q display the worst conductive performance. This is explained by the strong inhibition of loops in the spanning cluster, resulting in a substantially smaller associated conducting backbone.Comment: 4 pages, 4 figure

Global Stationary Phase and the Sign Problem

We present a computational strategy for reducing the sign problem in the evaluation of high dimensional integrals with non-positive definite weights. The method involves stochastic sampling with a positive semidefinite weight that is adaptively and optimally determined during the course of a simulation. The optimal criterion, which follows from a variational principle for analytic actions S(z), is a global stationary phase condition that the average gradient of the phase Im(S) along the sampling path vanishes. Numerical results are presented from simulations of a model adapted from statistical field theories of classical fluids.Comment: 9 pages, 3 figures, submitted for publicatio