Generalized connectivity between any two nodes in a complex network

This article focuses on the identification of the number of paths with different lengths between pairs of nodes in complex networks and how these paths can be used for characterization of topological properties of theoretical and real-world complex networks. This analysis revealed that the number of paths can provide a better discrimination of network models than traditional network measurements. In addition, the analysis of real-world networks suggests that the long-range connectivity tends to be limited in these networks and may be strongly related to network growth and organization.

Free-standing urethane/urea elastomer films undoped and doped with ferro-nano-particles

We report on an experimental study of the structures presented by urethane/urea elastomeric films without and with ferromagnetic nanoparticles incorporated. The study is made by using the X-ray diffraction, nuclear magnetic resonance (NMR), optical, atomic and magnetic force (MFM) microscopy techniques, and mechanical assays. The structure of the elastomeric matrix is characterized by a distance of 0.46 nm between neighboring molecular segments, almost independent on the stretching applied. The shear casting performed in order to obtain the elastomeric films tends to orient the molecules parallel to the flow direction thus introducing anisotropy in the molecular network which is reflected on the values obtained for the orientational order parameter and its increase for the stretched films. In the case of nanoparticles-doped samples, the structure remains nearly unchanged although the local order parameter is clearly larger for the undoped films. NMR experiments evidence modifications in the molecular network local ordering. Micrometer size clusters were observed by MFM for even small concentration of magnetic particles.

Two-dimensional supersonic nonlinear Schrodinger flow past an extended obstacle

Supersonic flow of a superfluid past a slender impenetrable macroscopic obstacle is studied in the framework of the two-dimensional (2D) defocusing nonlinear Schroumldinger (NLS) equation. This problem is of fundamental importance as a dispersive analog of the corresponding classical gas-dynamics problem. Assuming the oncoming flow speed is sufficiently high, we asymptotically reduce the original boundary-value problem for a steady flow past a slender body to the one-dimensional dispersive piston problem described by the nonstationary NLS equation, in which the role of time is played by the stretched x coordinate and the piston motion curve is defined by the spatial body profile. Two steady oblique spatial dispersive shock waves (DSWs) spreading from the pointed ends of the body are generated in both half planes. These are described analytically by constructing appropriate exact solutions of the Whitham modulation equations for the front DSW and by using a generalized Bohr-Sommerfeld quantization rule for the oblique dark soliton fan in the rear DSW. We propose an extension of the traditional modulation description of DSWs to include the linear ""ship-wave"" pattern forming outside the nonlinear modulation region of the front DSW. Our analytic results are supported by direct 2D unsteady numerical simulations and are relevant to recent experiments on Bose-Einstein condensates freely expanding past obstacles.

Elliptic and Hexadecapole Flow of Charged Hadrons in Au plus Au Collisions at root s(NN)=200 GeV

Differential measurements of the elliptic (upsilon(2)) and hexadecapole (upsilon(4)) Fourier flow coefficients are reported for charged hadrons as a function of transverse momentum (p(T)) and collision centrality or number of participant nucleons (N(part)) for Au + Au collisions at root s(NN) = 200 GeV/ The upsilon(2,4) measurements at pseudorapidity vertical bar eta vertical bar <= 0.35, obtained with four separate reaction-plane detectors positioned in the range 1.0 < vertical bar eta vertical bar < 3.9, show good agreement, indicating the absence of significant Delta eta-dependent nonflow correlations. Sizable values for upsilon(4)(p(T)) are observed with a ratio upsilon(4)(p(T), N(part))/upsilon(2)(2)(p(T), N(part)) approximate to 0.8 for 50 less than or similar to N(part) less than or similar to 200, which is compatible with the combined effects of a finite viscosity and initial eccentricity fluctuations. For N(part) greater than or similar to 200 this ratio increases up to 1.7 in the most central collisions.

Liquid polymorphism, order-disorder transitions and anomalous behavior: A Monte Carlo study of the Bell-Lavis model for water

The Bell-Lavis model for liquid water is investigated through numerical simulations. The lattice-gas model on a triangular lattice presents orientational states and is known to present a highly bonded low density phase and a loosely bonded high density phase. We show that the model liquid-liquid transition is continuous, in contradiction with mean-field results on the Husimi cactus and from the cluster variational method. We define an order parameter which allows interpretation of the transition as an order-disorder transition of the bond network. Our results indicate that the order-disorder transition is in the Ising universality class. Previous proposal of an Ehrenfest second order transition is discarded. A detailed investigation of anomalous properties has also been undertaken. The line of density maxima in the HDL phase is stabilized by fluctuations, absent in the mean-field solution. (C) 2009 American Institute of Physics. [doi:10.1063/1.3253297]

Systematic studies of elliptic flow measurements in Au plus Au collisions at s(NN)=200 GeV

We present inclusive charged hadron elliptic flow (v(2)) measured over the pseudorapidity range vertical bar eta vertical bar < 0.35 in Au+Au collisions at s(NN)=200 GeV. Results for v(2) are presented over a broad range of transverse momentum (p(T)=0.2-8.0 GeV/c) and centrality (0-60%). To study nonflow effects that are correlations other than collective flow, as well as the fluctuations of v(2), we compare two different analysis methods: (1) the event-plane method from two independent subdetectors at forward (vertical bar eta vertical bar=3.1-3.9) and beam (vertical bar eta vertical bar>6.5) pseudorapidities and (2) the two-particle cumulant method extracted using correlations between particles detected at midrapidity. The two event-plane results are consistent within systematic uncertainties over the measured p(T) and in centrality 0-40%. There is at most a 20% difference in the v(2) between the two event-plane methods in peripheral (40-60%) collisions. The comparisons between the two-particle cumulant results and the standard event-plane measurements are discussed.

Directed flow at midrapidity in event-by-event hydrodynamics

Fluctuations in the initial geometry of a nucleus-nucleus collision have been recently shown to result in a new type of directed flow (v(1)) that, unlike the usual directed flow, is also present at midrapidity. We compute this new v(1) versus transverse momentum and centrality for Au-Au collisions at RHIC using the hydrodynamic code NeXSPheRIO. We find that the event plane of v(1) is correlated with the angle of the initial dipole of the distribution, as predicted, though with a large dispersion. It is uncorrelated with the reaction plane. Our results are in excellent agreement with results inferred from STAR correlation data.

Finding Quasi-Optimal Network Topologies for Information Transmission in Active Networks

This work clarifies the relation between network circuit (topology) and behaviour (information transmission and synchronization) in active networks, e.g. neural networks. As an application, we show how one can find network topologies that are able to transmit a large amount of information, possess a large number of communication channels, and are robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Importance of granular structure in the initial conditions for the elliptic flow

We show the effects of the granular structure of the initial conditions of a hydrodynamic description of high-energy nucleus-nucleus collisions on some observables, especially on the elliptic-flow parameter upsilon(2). Such a structure enhances production of isotropically distributed high-p(T) particles, making upsilon(2) smaller there. Also, it reduces upsilon(2) in the forward and backward regions where the global matter density is smaller and, therefore, where such effects become more efficacious.

Charged and strange hadron elliptic flow in Cu plus Cu collisions at root s(NN)=62.4 and 200 GeV

We present the results of an elliptic flow, v(2), analysis of Cu + Cu collisions recorded with the solenoidal tracker detector (STAR) at the BNL Relativistic Heavy Ion Collider at root s(NN) = 62.4 and 200 GeV. Elliptic flow as a function of transverse momentum, v(2)(p(T)), is reported for different collision centralities for charged hadrons h(+/-) and strangeness-ontaining hadrons K(S)(0), Lambda, Xi, and phi in the midrapidity region vertical bar eta vertical bar < 1.0. Significant reduction in systematic uncertainty of the measurement due to nonflow effects has been achieved by correlating particles at midrapidity, vertical bar eta vertical bar < 1.0, with those at forward rapidity, 2.5 < vertical bar eta vertical bar < 4.0. We also present azimuthal correlations in p + p collisions at root s = 200 GeV to help in estimating nonflow effects. To study the system-size dependence of elliptic flow, we present a detailed comparison with previously published results from Au + Au collisions at root s(NN) = 200 GeV. We observe that v(2)(p(T)) of strange hadrons has similar scaling properties as were first observed in Au + Au collisions, that is, (i) at low transverse momenta, p(T) < 2 GeV/c, v(2) scales with transverse kinetic energy, m(T) - m, and (ii) at intermediate p(T), 2 < p(T) < 4 GeV/c, it scales with the number of constituent quarks, n(q.) We have found that ideal hydrodynamic calculations fail to reproduce the centrality dependence of v(2)(p(T)) for K(S)(0) and Lambda. Eccentricity scaled v(2) values, v(2)/epsilon, are larger in more central collisions, suggesting stronger collective flow develops in more central collisions. The comparison with Au + Au collisions, which go further in density, shows that v(2)/epsilon depends on the system size, that is, the number of participants N(part). This indicates that the ideal hydrodynamic limit is not reached in Cu + Cu collisions, presumably because the assumption of thermalization is not attained.

Interpretation of MINOS data in terms of nonstandard neutrino interactions

The MINOS experiment at Fermilab has recently reported a tension between the oscillation results for neutrinos and antineutrinos. We show that this tension, if it persists, can be understood in the framework of nonstandard neutrino interactions (NSI). While neutral current NSI (nonstandard matter effects) are disfavored by atmospheric neutrinos, a new charged current coupling between tau neutrinos and nucleons can fit the MINOS data without violating other constraints. In particular, we show that loop-level contributions to flavor-violating tau decays are sufficiently suppressed. However, conflicts with existing bounds could arise once the effective theory considered here is embedded into a complete renormalizable model. We predict the future sensitivity of the T2K and NOvA experiments to the NSI parameter region favored by the MINOS fit, and show that both experiments are excellent tools to test the NSI interpretation of the MINOS data.

Chaotic advection in blood flow

In this paper we argue that the effects of irregular chaotic motion of particles transported by blood can play a major role in the development of serious circulatory diseases. Vessel wall irregularities modify the flow field, changing in a nontrivial way the transport and activation of biochemically active particles. We argue that blood particle transport is often chaotic in realistic physiological conditions. We also argue that this chaotic behavior of the flow has crucial consequences for the dynamics of important processes in the blood, such as the activation of platelets which are involved in the thrombus formation.

Network of recurrent events for the Olami-Feder-Christensen model

We numerically study the dynamics of a discrete spring-block model introduced by Olami, Feder, and Christensen (OFC) to mimic earthquakes and investigate to what extent this simple model is able to reproduce the observed spatiotemporal clustering of seismicity. Following a recently proposed method to characterize such clustering by networks of recurrent events [J. Davidsen, P. Grassberger, and M. Paczuski, Geophys. Res. Lett. 33, L11304 (2006)], we find that for synthetic catalogs generated by the OFC model these networks have many nontrivial statistical properties. This includes characteristic degree distributions, very similar to what has been observed for real seismicity. There are, however, also significant differences between the OFC model and earthquake catalogs, indicating that this simple model is insufficient to account for certain aspects of the spatiotemporal clustering of seismicity.

Communication structure of cortical networks

Large-scale cortical networks exhibit characteristic topological properties that shape communication between brain regions and global cortical dynamics. Analysis of complex networks allows the description of connectedness, distance, clustering, and centrality that reveal different aspects of how the network's nodes communicate. Here, we focus on a novel analysis of complex walks in a series of mammalian cortical networks that model potential dynamics of information flow between individual brain regions. We introduce two new measures called absorption and driftness. Absorption is the average length of random walks between any two nodes, and takes into account all paths that may diffuse activity throughout the network. Driftness is the ratio between absorption and the corresponding shortest path length. For a given node of the network, we also define four related measurements, namely in-and out-absorption as well as in-and out-driftness, as the averages of the corresponding measures from all nodes to that node, and from that node to all nodes, respectively. We find that the cat thalamo-cortical system incorporates features of two classic network topologies, Erdos-Renyi graphs with respect to in-absorption and in-driftness, and configuration models with respect to out-absorption and out-driftness. Moreover, taken together these four measures separate the network nodes based on broad functional roles (visual, auditory, somatomotor, and frontolimbic).

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs-a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.