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.

Role of noise in population dynamics cycles

Noise is an intrinsic feature of population dynamics and plays a crucial role in oscillations called phase-forgetting quasicycles by converting damped into sustained oscillations. This function of noise becomes evident when considering Langevin equations whose deterministic part yields only damped oscillations. We formulate here a consistent and systematic approach to population dynamics, leading to a Fokker-Planck equation and the associate Langevin equations in accordance with this conceptual framework, founded on stochastic lattice-gas models that describe spatially structured predator-prey systems. Langevin equations in the population densities and predator-prey pair density are derived in two stages. First, a birth-and-death stochastic process in the space of prey and predator numbers and predator-prey pair number is obtained by a contraction method that reduces the degrees of freedom. Second, a van Kampen expansion in the inverse of system size is then performed to get the Fokker-Planck equation. We also study the time correlation function, the asymptotic behavior of which is used to characterize the transition from the cyclic coexistence of species to the ordinary coexistence.

Dynamic polarizability, Cauchy moments, and the optical absorption spectrum of liquid water: A sequential molecular dynamics/quantum mechanical approach

The dynamic polarizability and optical absorption spectrum of liquid water in the 6-15 eV energy range are investigated by a sequential molecular dynamics (MD)/quantum mechanical approach. The MD simulations are based on a polarizable model for liquid water. Calculation of electronic properties relies on time-dependent density functional and equation-of-motion coupled-cluster theories. Results for the dynamic polarizability, Cauchy moments, S(-2), S(-4), S(-6), and dielectric properties of liquid water are reported. The theoretical predictions for the optical absorption spectrum of liquid water are in good agreement with experimental information.

Electronic properties of liquid ammonia: A sequential molecular dynamics/quantum mechanics approach

The electronic properties of liquid ammonia are investigated by a sequential molecular dynamics/quantum mechanics approach. Quantum mechanics calculations for the liquid phase are based on a reparametrized hybrid exchange-correlation functional that reproduces the electronic properties of ammonia clusters [(NH(3))(n); n=1-5]. For these small clusters, electron binding energies based on Green's function or electron propagator theory, coupled cluster with single, double, and perturbative triple excitations, and density functional theory (DFT) are compared. Reparametrized DFT results for the dipole moment, electron binding energies, and electronic density of states of liquid ammonia are reported. The calculated average dipole moment of liquid ammonia (2.05 +/- 0.09 D) corresponds to an increase of 27% compared to the gas phase value and it is 0.23 D above a prediction based on a polarizable model of liquid ammonia [Deng , J. Chem. Phys. 100, 7590 (1994)]. Our estimate for the ionization potential of liquid ammonia is 9.74 +/- 0.73 eV, which is approximately 1.0 eV below the gas phase value for the isolated molecule. The theoretical vertical electron affinity of liquid ammonia is predicted as 0.16 +/- 0.22 eV, in good agreement with the experimental result for the location of the bottom of the conduction band (-V(0)=0.2 eV). Vertical ionization potentials and electron affinities correlate with the total dipole moment of ammonia aggregates. (c) 2008 American Institute of Physics.

Jensen inequalities for tunneling probabilities in complex systems

The Jensen theorem is used to derive inequalities for semiclassical tunneling probabilities for systems involving several degrees of freedom. These Jensen inequalities are used to discuss several aspects of sub-barrier heavy-ion fusion reactions. The inequality hinges on general convexity properties of the tunneling coefficient calculated with the classical action in the classically forbidden region.

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.

Atomistic molecular dynamics study of interface formation: Al on poly(p-phenylene vinylene)

We model interface formation by metal deposition on the conjugated polymer poly-para-phenylene vinylene, studying direct aluminum and layered aluminum-calcium structures Al/PPV and Al/Ca/PPV. To do that we use classical molecular dynamics simulations, checked by ab initio density-functional theory calculations, for selected relevant configurations. We find that Al not only migrates easily into the film, with a strong charge transfer to the neighboring chains, but also promotes rearrangement of the polymer in the interfacial region to the hexagonal structure. On the other hand, our results indicate that a thin Ca layer is sufficient to protect the film and maintain a well-defined metal/polymer interface, and that also a thin Al capping layer may protect the whole from environmental degradation.

Amorphous HfO(2) and Hf(1-x)Si(x)O via a melt-and-quench scheme using ab initio molecular dynamics

We have performed ab initio molecular dynamics simulations to generate an atomic structure model of amorphous hafnium oxide (a-HfO(2)) via a melt-and-quench scheme. This structure is analyzed via bond-angle and partial pair distribution functions. These results give a Hf-O average nearest-neighbor distance of 2.2 angstrom, which should be compared to the bulk value, which ranges from 1.96 to 2.54 angstrom. We have also investigated the neutral O vacancy and a substitutional Si impurity for various sites, as well as the amorphous phase of Hf(1-x)Si(x)O(2) for x=0.25, 0375, and 0.5.

Spin dynamics of NiCl(2)-4SC(NH(2))(2) in the field-induced ordered phase

NiCl(2)-4SC(NH(2))(2) (known as DTN) is a spin-1 material with a strong single-ion anisotropy that is regarded as a new candidate for Bose-Einstein condensation (BEC) of spin degrees of freedom. We present a systematic study of the low-energy excitation spectrum of DTN in the field-induced magnetically ordered phase by means of high-field electron spin resonance measurements at temperatures down to 0.45 K. We argue that two gapped modes observed in the experiment can be consistently interpreted within a four-sublattice antiferromagnet model with a finite interaction between two tetragonal subsystems and unbroken axial symmetry. The latter is crucial for the interpretation of the field-induced ordering in DTN in terms of BEC.

Gauge invariance and classical dynamics of noncommutative particle theory

We consider a model of classical noncommutative particle in an external electromagnetic field. For this model, we prove the existence of generalized gauge transformations. Classical dynamics in Hamiltonian and Lagrangian form is discussed; in particular, the motion in the constant magnetic field is studied in detail. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3299296]

The clusters Abell 222 and Abell 223: a multi-wavelength view

Context. The Abell 222 and 223 clusters are located at an average redshift z similar to 0.21 and are separated by 0.26 deg. Signatures of mergers have been previously found in these clusters, both in X-rays and at optical wavelengths, thus motivating our study. In X-rays, they are relatively bright, and Abell 223 shows a double structure. A filament has also been detected between the clusters both at optical and X-ray wavelengths. Aims. We analyse the optical properties of these two clusters based on deep imaging in two bands, derive their galaxy luminosity functions (GLFs) and correlate these properties with X-ray characteristics derived from XMM-Newton data. Methods. The optical part of our study is based on archive images obtained with the CFHT Megaprime/Megacam camera, covering a total region of about 1 deg(2), or 12.3 x 12.3 Mpc(2) at a redshift of 0.21. The X-ray analysis is based on archive XMM-Newton images. Results. The GLFs of Abell 222 in the g' and r' bands are well fit by a Schechter function; the GLF is steeper in r' than in g'. For Abell 223, the GLFs in both bands require a second component at bright magnitudes, added to a Schechter function; they are similar in both bands. The Serna & Gerbal method allows to separate well the two clusters. No obvious filamentary structures are detected at very large scales around the clusters, but a third cluster at the same redshift, Abell 209, is located at a projected distance of 19.2 Mpc. X-ray temperature and metallicity maps reveal that the temperature and metallicity of the X-ray gas are quite homogeneous in Abell 222, while they are very perturbed in Abell 223. Conclusions. The Abell 222/Abell 223 system is complex. The two clusters that form this structure present very different dynamical states. Abell 222 is a smaller, less massive and almost isothermal cluster. On the other hand, Abell 223 is more massive and has most probably been crossed by a subcluster on its way to the northeast. As a consequence, the temperature distribution is very inhomogeneous. Signs of recent interactions are also detected in the optical data where this cluster shows a ""perturbed"" GLF. In summary, the multiwavelength analyses of Abell 222 and Abell 223 are used to investigate the connection between the ICM and the cluster galaxy properties in an interacting system.

Soliton dynamics at an interface between a uniform medium and a nonlinear optical lattice

We study trapping and propagation of a matter-wave soliton through the interface between uniform medium and a nonlinear optical lattice. Different regimes for transmission of a broad and a narrow solitons are investigated. Reflections and transmissions of solitons are predicted as a function of the lattice phase. The existence of a threshold in the amplitude of the nonlinear optical lattice, separating the transmission and reflection regimes, is verified. The localized nonlinear surface state, corresponding to the soliton trapped by the interface, is found. Variational approach predictions are confirmed by numerical simulations for the original Gross-Pitaevskii equation with nonlinear periodic potentials.

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.