Coexistence of interacting opinions in a generalized Sznajd model

The Sznajd model is a sociophysics model that mimics the propagation of opinions in a closed society, where the interactions favor groups of agreeing people. It is based in the Ising and Potts ferromagnetic models and, although the original model used only linear chains, it has since been adapted to general networks. This model has a very rich transient, which has been used to model several aspects of elections, but its stationary states are always consensus states. In order to model more complex behaviors, we have, in a recent work, introduced the idea of biases and prejudices to the Sznajd model by generalizing the bounded confidence rule, which is common to many continuous opinion models, to what we called confidence rules. In that work we have found that the mean field version of this model (corresponding to a complete network) allows for stationary states where noninteracting opinions survive, but never for the coexistence of interacting opinions. In the present work, we provide networks that allow for the coexistence of interacting opinions for certain confidence rules. Moreover, we show that the model does not become inactive; that is, the opinions keep changing, even in the stationary regime. This is an important result in the context of understanding how a rule that breeds local conformity is still able to sustain global diversity while avoiding a frozen stationary state. We also provide results that give some insights on how this behavior approaches the mean field behavior as the networks are changed.

Deformed Gaussian-orthogonal-ensemble description of small-world networks

The study of spectral behavior of networks has gained enthusiasm over the last few years. In particular, random matrix theory (RMT) concepts have proven to be useful. In discussing transition from regular behavior to fully chaotic behavior it has been found that an extrapolation formula of the Brody type can be used. In the present paper we analyze the regular to chaotic behavior of small world (SW) networks using an extension of the Gaussian orthogonal ensemble. This RMT ensemble, coined the deformed Gaussian orthogonal ensemble (DGOE), supplies a natural foundation of the Brody formula. SW networks follow GOE statistics until a certain range of eigenvalue correlations depending upon the strength of random connections. We show that for these regimes of SW networks where spectral correlations do not follow GOE beyond a certain range, DGOE statistics models the correlations very well. The analysis performed in this paper proves the utility of the DGOE in network physics, as much as it has been useful in other physical systems.

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.

Local approximations for polarization potentials

We discuss the derivation of an equivalent polarization potential independent of angular momentum l for use in the optical Schrodinger equation that describes the elastic scattering of heavy ions. Three different methods are used for this purpose. Application of our theory to the low energy scattering of light heavy-ion systems at near-barrier energies is made. It is found that the notion of an l-independent polarization potential has some validity but cannot be a good substitute for the l-dependent local equivalent Feshbach polarization potential.

Depth-dependent local structures in thin films unraveled by grazing-incidence X-ray absorption spectroscopy

A method of using X-ray absorption spectroscopy together with resolved grazing-incidence geometry for depth profiling of atomic, electronic or chemical local structures in thin films is presented. The quantitative deconvolution of thickness-dependent spectral features is performed by fully considering both scattering and absorption formalisms. Surface oxidation and local structural depth profiles in nanometric FePt films are determined, exemplifying the application of the method.

EPR study of local symmetry sites of Ce(3+) in Pb(1-x)Ce(x)A (A=S, Se, and Te)

The local site symmetry of Ce(3+) ions in the diluted magnetic semiconductors Pb(1-x)Ce(x)A (A=S, Se, and Te) has been investigated by electron-paramagnetic resonance (EPR). The experiments were carried out on single crystals with cerium concentration x ranging from 0.001 to 0.035. The isotropic line due to Ce(3+) ions located at the substitutional Pb cation site with octahedral symmetry was observed for all the studied samples. We determined the effective Lande factors to be g=1.333, 1.364, and 1.402 for A=S, Se, and Te, respectively. The small difference with the predicted Lande factor g of 10/7 for the Gamma(7) (J=5/2) ground state was attributed to crystal-field admixture. In addition, EPR lines from Ce(3+) ions located at sites with small distortion from the original octahedral symmetry were also observed. Two distinct sites with axial distortion along the < 001 > crystallographic direction were identified and a third signal in the spectrum was attributed to sites with the cubic symmetry distorted along the < 110 > direction. The distortion at these distinct Ce sites is attributed to Pb lattice vacancies near the cerium ions that compensate for its donor activity.

Observation of charge-dependent azimuthal correlations and possible local strong parity violation in heavy-ion collisions

Parity (P)-odd domains, corresponding to nontrivial topological solutions of the QCD vacuum, might be created during relativistic heavy-ion collisions. These domains are predicted to lead to charge separation of quarks along the orbital momentum of the system created in noncentral collisions. To study this effect, we investigate a three-particle mixed-harmonics azimuthal correlator which is a P-even observable, but directly sensitive to the charge-separation effect. We report measurements of this observable using the STAR detector in Au + Au and Cu + Cu collisions at root s(NN) = 200 and 62 GeV. The results are presented as a function of collision centrality, particle separation in rapidity, and particle transverse momentum. A signal consistent with several of the theoretical expectations is detected in all four data sets. We compare our results to the predictions of existing event generators and discuss in detail possible contributions from other effects that are not related to P violation.

Azimuthal Charged-Particle Correlations and Possible Local Strong Parity Violation

Parity-odd domains, corresponding to nontrivial topological solutions of the QCD vacuum, might be created during relativistic heavy-ion collisions. These domains are predicted to lead to charge separation of quarks along the system's orbital momentum axis. We investigate a three-particle azimuthal correlator which is a P even observable, but directly sensitive to the charge separation effect. We report measurements of charged hadrons near center-of-mass rapidity with this observable in Au+Au and Cu+Cu collisions at s(NN)=200 GeV using the STAR detector. A signal consistent with several expectations from the theory is detected. We discuss possible contributions from other effects that are not related to parity violation.

Engineering interactions for quasiperfect transfer of polariton states through nonideal bosonic networks of distinct topologies

We present a scheme for quasiperfect transfer of polariton states from a sender to a spatially separated receiver, both composed of high-quality cavities filled by atomic samples. The sender and the receiver are connected by a nonideal transmission channel -the data bus- modelled by a network of lossy empty cavities. In particular, we analyze the influence of a large class of data-bus topologies on the fidelity and transfer time of the polariton state. Moreover, we also assume dispersive couplings between the polariton fields and the data-bus normal modes in order to achieve a tunneling-like state transfer. Such a tunneling-transfer mechanism, by which the excitation energy of the polariton effectively does not populate the data-bus cavities, is capable of attenuating appreciably the dissipative effects of the data-bus cavities. After deriving a Hamiltonian for the effective coupling between the sender and the receiver, we show that the decay rate of the fidelity is proportional to a cooperativity parameter that weighs the cost of the dissipation rate against the benefit of the effective coupling strength. The increase of the fidelity of the transfer process can be achieved at the expense of longer transfer times. We also show that the dependence of both the fidelity and the transfer time on the network topology is analyzed in detail for distinct regimes of parameters. It follows that the data-bus topology can be explored to control the time of the state-transfer process.

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.

Knowledge acquisition by networks of interacting agents in the presence of observation errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erdos-Renyi or Barabasi-Albert type. First, we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall performance of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.

Border detection in complex networks

One important issue implied by the finite nature of real-world networks regards the identification of their more external (border) and internal nodes. The present work proposes a formal and objective definition of these properties, founded on the recently introduced concept of node diversity. It is shown that this feature does not exhibit any relevant correlation with several well-established complex networks measurements. A methodology for the identification of the borders of complex networks is described and illustrated with respect to theoretical (geographical and knitted networks) as well as real-world networks (urban and word association networks), yielding interesting results and insights in both cases.

Intermediate motions as studied by solid-state separated local field NMR experiments

In this report, the application of a class of separated local field NMR experiments named dipolar chemical shift correlation (DIPSHIFT) for probing motions in the intermediate regime is discussed. Simple analytical procedures based on the Anderson-Weiss (AW) approximation are presented. In order to establish limits of validity of the AW based formulas, a comparison with spin dynamics simulations based on the solution of the stochastic Liouville-von-Neumann equation is presented. It is shown that at short evolution times (less than 30% of the rotor period), the AW based formulas are suitable for fitting the DIPSHIFT curves and extracting kinetic parameters even in the case of jumplike motions. However, full spin dynamics simulations provide a more reliable treatment and extend the frequency range of the molecular motions accessible by DIPSHIFT experiments. As an experimental test, molecular jumps of imidazol methyl sulfonate and trimethylsulfoxonium iodide, as well as the side-chain motions in the photoluminescent polymer poly[2-methoxy-5-(2(')-ethylhexyloxy)-1,4-phenylenevinylene], were characterized. Possible extensions are also discussed. (c) 2008 American Institute of Physics.

Quantitative determination of optical transmission through subwavelength slit arrays in Ag films: Role of surface wave interference and local coupling between adjacent slits

Measurement of the transmitted intensity from a coherent monomode light source through a series of subwavelength slit arrays in Ag films, with varying array pitch and number of slits, demonstrates enhancement (suppression) by factors of as much as 6 (9) when normalized to the transmission efficiency of an isolated slit. Pronounced minima in the transmitted intensity are observed at array pitches corresponding to lambda(SPP), 2 lambda(SPP), and 3 lambda(SPP), where lambda(SPP) is the wavelength of the surface plasmon polariton (SPP). The position of these minima arises from destructive interference between incident propagating waves and pi-phase-shifted SPP waves. Increasing the number of slits to four or more does not increase appreciably the per-slit transmission intensity. A simple interference model fits well the measured transmitted intensity profile.