Resistance distance, information centrality, node vulnerability and vibrations in complex networks

We discuss three seemingly unrelated quantities that have been introduced in different fields of science for complex networks. The three quantities are the resistance distance, the information centrality and the node displacement. We first prove various relations among them. Then we focus on the node displacement, showing its usefulness as an index of node vulnerability.We argue that the node displacement has a better resolution as a measure of node vulnerability than the degree and the information centrality

Hard Thermal Loops and Chiral Lagrangians

Chiral symmetry is used as the guiding principle to derive hard thermal loop effects in chiral perturbation theory. This is done by using a chiral invariant background field method for the non-linear sigma model and the Wess-Zumino-Witten lagrangian, with and without external vector and axial vector sources. It is then shown that the n-point hard thermal loop is the leading thermal correction for the Green function of n point vector soft quark currents.Comment: 15 pages, Revtex, references added, typos corrected, final version to appear in Phys. Rev.

Statistically derived contributions of diverse human influences to twentieth-century temperature changes

The warming of the climate system is unequivocal as evidenced by an increase in global temperatures by 0.8 °C over the past century. However, the attribution of the observed warming to human activities remains less clear, particularly because of the apparent slow-down in warming since the late 1990s. Here we analyse radiative forcing and temperature time series with state-of-the-art statistical methods to address this question without climate model simulations. We show that long-term trends in total radiative forcing and temperatures have largely been determined by atmospheric greenhouse gas concentrations, and modulated by other radiative factors. We identify a pronounced increase in the growth rates of both temperatures and radiative forcing around 1960, which marks the onset of sustained global warming. Our analyses also reveal a contribution of human interventions to two periods when global warming slowed down. Our statistical analysis suggests that the reduction in the emissions of ozone-depleting substances under the Montreal Protocol, as well as a reduction in methane emissions, contributed to the lower rate of warming since the 1990s. Furthermore, we identify a contribution from the two world wars and the Great Depression to the documented cooling in the mid-twentieth century, through lower carbon dioxide emissions. We conclude that reductions in greenhouse gas emissions are effective in slowing the rate of warming in the short term.F.E. acknowledges financial support from the Consejo Nacional de Ciencia y Tecnologia (http://www.conacyt.gob.mx) under grant CONACYT-310026, as well as from PASPA DGAPA of the Universidad Nacional Autonoma de Mexico. (CONACYT-310026 - Consejo Nacional de Ciencia y Tecnologia; PASPA DGAPA of the Universidad Nacional Autonoma de Mexico

CONSTRUCTAL DESIGN APPLIED TO INVESTIGATE THE INFLUENCE OF GEOMETRY ON THE MASS FLOW RATE OF AN INCLINED PASSIVE WALL SOLAR CHIMNEY ATTACHED TO A ROOM

The present work aims to analyze the turbulent flow in an inclined passive wall solar chimney attached to a room, evaluating the influence of its geometry on the thermal performance of the building (measured by the mass flow rate in the chimney exit) by means of Constructal Design. The flow is considered turbulent, incompressible, under natural convection heat transfer, transient and in a two-dimensional domain that simulates a solar chimney attached to a room. Time-averaged conservation equations of mass, momentum, and energy are numerically solved with the finite volume method using the commercial package FLUENT. For closure modeling of turbulence, it is employed the standard k – ε model. Chimney and room areas are the problem constraints. Moreover, the problem is subjected to three degrees of freedom: the ratio between the inlet opening size and chimney height (Hi/Ha) (which is maintained constant in the present investigations, Hi/Ha = 0.05); ratio between the width of inferior base of the chimney and its height (Wg/Ha); and the ratio between the exit air gap and the inferior base widths of the chimney (We/Wg). The latter two degrees of freedom are varied. Results showed that the degrees of freedom analyzed have a strong influence on the mass flow rate of the air in the building, confirming that the geometrical configuration of solar chimney can be important for the improvement of thermal conditions on the attached building

CONSTRUCTAL DESIGN AND SIMULATED ANNEALING EMPLOYED FOR GEOMETRIC OPTIMIZATION OF A Y-SHAPED CAVITY INTRUDED INTO CONDUCTIVE WALL

he problem study here is concerned with the geometrical evaluation of an isothermal Y-shaped cavity intruded into conducting solid wall with internal heat generation. The cavity acts as a sink of the heat generated into the solid. The main purpose here is to minimize the maximal excess of temperature (θmax) in the solid. Constructal Design, which is based on the objective and constraints principle, is employed to evaluate the geometries of Y-shaped cavity. Meanwhile, Simulated Annealing (SA) algorithm is employed as optimization method to seek for the best shapes. To validate the SA methodology, the results obtained with SA are compared with those achieved with Genetic Algorithm (GA) and Exaustive Search (ES) in recent studies of literature. The comparison between the optimization methods (SA, GA and ES) showed that Simulated Annealing is highly effective in the search for the optimal shapes of the studied case

Escort mean values and the characterization of power-law-decaying probability densities

Escort mean values (or $q$-moments) constitute useful theoretical tools for describing basic features of some probability densities such as those which asymptotically decay like {\it power laws}. They naturally appear in the study of many complex dynamical systems, particularly those obeying nonextensive statistical mechanics, a current generalization of the Boltzmann-Gibbs theory. They recover standard mean values (or moments) for $q=1$. Here we discuss the characterization of a (non-negative) probability density by a suitable set of all its escort mean values together with the set of all associated normalizing quantities, provided that all of them converge. This opens the door to a natural extension of the well known characterization, for the $q=1$ instance, of a distribution in terms of the standard moments, provided that {\it all} of them have {\it finite} values. This question would be specially relevant in connection with probability densities having {\it divergent} values for all nonvanishing standard moments higher than a given one (e.g., probability densities asymptotically decaying as power-laws), for which the standard approach is not applicable. The Cauchy-Lorentz distribution, whose second and higher even order moments diverge, constitutes a simple illustration of the interest of this investigation. In this context, we also address some mathematical subtleties with the aim of clarifying some aspects of an interesting non-linear generalization of the Fourier Transform, namely, the so-called $q$-Fourier Transform.Comment: 20 pages (2 Appendices have been added

Googling the brain: discovering hierarchical and asymmetric network structures, with applications in neuroscience

Hierarchical organisation is a common feature of many directed networks arising in nature and technology. For example, a well-defined message-passing framework based on managerial status typically exists in a business organisation. However, in many real-world networks such patterns of hierarchy are unlikely to be quite so transparent. Due to the nature in which empirical data is collated the nodes will often be ordered so as to obscure any underlying structure. In addition, the possibility of even a small number of links violating any overall “chain of command” makes the determination of such structures extremely challenging. Here we address the issue of how to reorder a directed network in order to reveal this type of hierarchy. In doing so we also look at the task of quantifying the level of hierarchy, given a particular node ordering. We look at a variety of approaches. Using ideas from the graph Laplacian literature, we show that a relevant discrete optimization problem leads to a natural hierarchical node ranking. We also show that this ranking arises via a maximum likelihood problem associated with a new range-dependent hierarchical random graph model. This random graph insight allows us to compute a likelihood ratio that quantifies the overall tendency for a given network to be hierarchical. We also develop a generalization of this node ordering algorithm based on the combinatorics of directed walks. In passing, we note that Google’s PageRank algorithm tackles a closely related problem, and may also be motivated from a combinatoric, walk-counting viewpoint. We illustrate the performance of the resulting algorithms on synthetic network data, and on a real-world network from neuroscience where results may be validated biologically

Spectral statistics of random geometric graphs

We use random matrix theory to study the spectrum of random geometric graphs, a fundamental model of spatial networks. Considering ensembles of random geometric graphs we look at short range correlations in the level spacings of the spectrum via the nearest neighbour and next nearest neighbour spacing distribution and long range correlations via the spectral rigidity Delta_3 statistic. These correlations in the level spacings give information about localisation of eigenvectors, level of community structure and the level of randomness within the networks. We find a parameter dependent transition between Poisson and Gaussian orthogonal ensemble statistics. That is the spectral statistics of spatial random geometric graphs fits the universality of random matrix theory found in other models such as Erdos-Renyi, Barabasi-Albert and Watts-Strogatz random graph.Comment: 19 pages, 6 figures. Substantially updated from previous versio

The BES f_0(1810): a new glueball candidate

We analyze the f_0(1810) state recently observed by the BES collaboration via radiative J/\psi decay to a resonant \phi\omega spectrum and confront it with DM2 data and glueball theory. The DM2 group only measured \omega\omega decays and reported a pseudoscalar but no scalar resonance in this mass region. A rescattering mechanism from the open flavored KKbar decay channel is considered to explain why the resonance is only seen in the flavor asymmetric \omega\phi branch along with a discussion of positive C parity charmonia decays to strengthen the case for preferred open flavor glueball decays. We also calculate the total glueball decay width to be roughly 100 MeV, in agreement with the narrow, newly found f_0, and smaller than the expected estimate of 200-400 MeV. We conclude that this discovered scalar hadron is a solid glueball candidate and deserves further experimental investigation, especially in the K-Kbar channel. Finally we comment on other, but less likely, possible assignments for this state.Comment: 11 pages, 4 figures. Major substantive additions, including an ab-initio, QCD-based computation of the glueball inclusive decay width, evaluation of final state effects, and enhanced discussion of several alternative possibilities. Our conclusions are unchanged: the BES f_0(1810) is a promising glueball candidat

Distribution of shortest cycle lengths in random networks

We present analytical results for the distribution of shortest cycle lengths (DSCL) in random networks. The approach is based on the relation between the DSCL and the distribution of shortest path lengths (DSPL). We apply this approach to configuration model networks, for which analytical results for the DSPL were obtained before. We first calculate the fraction of nodes in the network which reside on at least one cycle. Conditioning on being on a cycle, we provide the DSCL over ensembles of configuration model networks with degree distributions which follow a Poisson distribution (Erdos-R\'enyi network), degenerate distribution (random regular graph) and a power-law distribution (scale-free network). The mean and variance of the DSCL are calculated. The analytical results are found to be in very good agreement with the results of computer simulations.Comment: 44 pages, 11 figure