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.

Signature of the interaction between dark energy and dark matter in observations

We investigate the effect of an interaction between dark energy and dark matter upon the dynamics of galaxy clusters. This effect is computed through the Layser-Irvine equation, which describes how an astrophysical system reaches virial equilibrium and was modified to include the dark interactions. Using observational data from almost 100 purportedly relaxed galaxy clusters we put constraints on the strength of the couplings in the dark sector. We compare our results with those from other observations and find that a positive (in the sense of energy flow from dark energy to dark matter) nonvanishing interaction is consistent with the data within several standard deviations.

Field theory model for dark matter and dark energy in interaction

We propose a field theory model for dark energy and dark matter in interaction. Comparing the classical solutions of the field equations with the observations of the CMB shift parameter, baryonic acoustic oscillations, lookback time, and the Gold supernovae sample, we observe a possible interaction between dark sectors with energy decay from dark energy into dark matter. The observed interaction provides an alleviation to the coincidence problem.

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.

Testing the interaction between dark energy and dark matter via the latest observations

Cosmological analyses based on currently available observations are unable to rule out a sizeable coupling between dark energy and dark matter. However, the signature of the coupling is not easy to grasp, since the coupling is degenerate with other cosmological parameters, such as the dark energy equation of state and the dark matter abundance. We discuss possible ways to break such degeneracy. Based on the perturbation formalism, we carry out the global fitting by using the latest observational data and get a tight constraint on the interaction between dark sectors. We find that the appropriate interaction can alleviate the coincidence problem.

Effect of weak dipolar interaction on the magnetic properties of Ni nanoparticles assembly analyzed with different protocols

The effect of weak dipolar interactions (DIs) between Ni nanoparticles (NPs) in samples with different Ni concentrations was investigated by performing a detailed characterization of their structural and magnetic properties. From the determination of several physical parameters of Ni NP assemblies, it was found that the ac and dc magnetic susceptibility measurements are valuable for identifying the DIs between NPs while hysteresis loops measurements showed to be very insensitive, provided that the strength of the DI field is much smaller than the maximum coercive field. Therefore, the sensitivity of the observed static and dynamical magnetic properties to the effect of weak DI depends on the measurement protocols used. (C) 2011 American Institute of Physics. [doi:10.1063/1.3556767]

Casimir interaction between a perfect conductor and graphene described by the Dirac model

We adopt the Dirac model for graphene and calculate the Casimir interaction energy between a plane suspended graphene sample and a parallel plane perfect conductor. This is done in two ways. First, we use the quantum-field-theory approach and evaluate the leading-order diagram in a theory with 2+1-dimensional fermions interacting with 3+1-dimensional photons. Next, we consider an effective theory for the electromagnetic field with matching conditions induced by quantum quasiparticles in graphene. The first approach turns out to be the leading order in the coupling constant of the second one. The Casimir interaction for this system appears to be rather weak. It exhibits a strong dependence on the mass of the quasiparticles in graphene.

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.

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.

Spin Hall effect due to intersubband-induced spin-orbit interaction in symmetric quantum wells

We investigate the intrinsic spin Hall effect in two-dimensional electron gases in quantum wells with two subbands, where a new intersubband-induced spin-orbit coupling is operative. The bulk spin Hall conductivity sigma(z)(xy) is calculated in the ballistic limit within the standard Kubo formalism in the presence of a magnetic field B and is found to remain finite in the B=0 limit, as long as only the lowest subband is occupied. Our calculated sigma(z)(xy) exhibits a nonmonotonic behavior and can change its sign as the Fermi energy (the carrier areal density n(2D)) is varied between the subband edges. We determine the magnitude of sigma(z)(xy) for realistic InSb quantum wells by performing a self-consistent calculation of the intersubband-induced spin-orbit coupling.

Control of the persistent currents in two interacting quantum rings through the Coulomb interaction and interring tunneling

The persistent current in two vertically coupled quantum rings containing few electrons is studied. We find that the Coulomb interaction between the rings in the absence of tunneling affects the persistent current in each ring and the ground-state configurations. Quantum tunneling between the rings alters significantly the ground state and the persistent current in the system.

Intersubband-induced spin-orbit interaction in quantum wells

Recently, we have found an additional spin-orbit (SO) interaction in quantum wells with two subbands [Bernardes , Phys. Rev. Lett. 99, 076603 (2007)]. This new SO term is nonzero even in symmetric geometries, as it arises from the intersubband coupling between confined states of distinct parities, and its strength is comparable to that of the ordinary Rashba. Starting from the 8x8 Kane model, here we present a detailed derivation of this new SO Hamiltonian and the corresponding SO coupling. In addition, within the self-consistent Hartree approximation, we calculate the strength of this new SO coupling for realistic symmetric modulation-doped wells with two subbands. We consider gated structures with either a constant areal electron density or a constant chemical potential. In the parameter range studied, both models give similar results. By considering the effects of an external applied bias, which breaks the structural inversion symmetry of the wells, we also calculate the strength of the resulting induced Rashba couplings within each subband. Interestingly, we find that for double wells the Rashba couplings for the first and second subbands interchange signs abruptly across the zero bias, while the intersubband SO coupling exhibits a resonant behavior near this symmetric configuration. For completeness we also determine the strength of the Dresselhaus couplings and find them essentially constant as function of the applied bias.

Anomalous Rashba spin-orbit interaction in InAs/GaSb quantum wells

We theoretically investigate the Rashba spin-orbit interaction in InAs/GaSb quantum wells (QWs). We find that the Rashba spin-splitting (RSS) sensitively depends on the thickness of the InAs layer. The RSS exhibits nonlinear behavior for narrow InAs/GaSb QWs and the oscillating feature for wide InAs/GaSb QWs. The nonlinear and oscillating behaviors arise from the weakened and enhanced interband coupling. The RSS also show asymmetric features respect to the direction of the external electric field. (C) 2008 American Institute of Physics.

Ultra-high-energy cosmic rays from centaurus A: jet interaction with gaseous shells

Ultra-high-energy cosmic rays (UHECRs), with energies above similar to 6 x 10(19) eV, seem to show a weak correlation with the distribution of matter relatively near to us in the universe. It has earlier been proposed that UHECRs could be accelerated in either the nucleus or the outer lobes of the nearby radio galaxy Cen A. We show that UHECR production at a spatially intermediate location about 15 kpc northeast from the nucleus, where the jet emerging from the nucleus is observed to strike a large star-forming shell of gas, is a plausible alternative. A relativistic jet is capable of accelerating lower energy heavy seed cosmic rays (CRs) to UHECRs on timescales comparable to the time it takes the jet to pierce the large gaseous cloud. In this model, many CRs arising from a starburst, with a composition enhanced in heavy elements near the knee region around PeV, are boosted to ultra-high energies by the relativistic shock of a newly oriented jet. This model matches the overall spectrum shown by the Auger data and also makes a prediction for the chemical composition as a function of particle energy. We thus predict an observable anisotropy in the composition at high energy in the sense that lighter nuclei should preferentially be seen toward the general direction of Cen A. Taking into consideration the magnetic field models for the Galactic disk and a Galactic magnetic wind, this scenario may resolve the discrepancy between HiRes and Auger results concerning the chemical composition of UHECRs.