We show that one may view the self-part and the distinct-part of the van Hove dynamic correlation function of a simple fluid as the one-body density distributions of a binary mixture that evolve in time according to dynamical density functional theory. For a test case of soft-core Brownian particles the theory yields results for the van Hove function that agree quantitatively with those of our Brownian dynamics computer simulations. At sufficiently high densities the free energy landscape underlying the dynamics exhibits a barrier as a function of the mean particle displacement, shedding new light on the nature of glass formation. For hard spheres confined between parallel planar walls the barrier height oscillates in phase with the local density, implying that the mobility is maximal between layers, which should be experimentally observable in confined colloidal dispersions.

We study an evolutionary prisoner’s dilemma game with two layered graphs, where the lower layer is the physical infrastructure on which the interactions are taking place and the upper layer represents the connections for the strategy adoption (learning) mechanism. This system is investigated by means of Monte Carlo simulations and an extended pair-approximation method. We consider the average density of cooperators in the stationary state for a fixed interaction graph, while varying the number of edges in the learning graph. According to the Monte Carlo simulations, the cooperation is modified substantially in a way resembling a coherence-resonance-like behavior when the number of learning edges is increased. This behavior is reproduced by the analytical results.

Analytic treatment and Monte Carlo simulations are used to study the effective potential between two spheres in a suspension of rods whose ends can adhere to the surface of the spheres. When only one end of each rod is adhesive the effective potential changes from being attractive to repulsive with enhancing the adherence, but when both ends of each rod are adhesive the effective potential is not a monotonic function of the distance between the two spheres for strong adherence. As the adhesive strength is fixed, the range of the effective potential will increase with increasing the length of the rods. When the adhesive range is much smaller than the diameter of the spheres, its influence on single end adhesion is approximately linear and on two end adhesion is about quadratic. Our results are qualitatively consistent with a recent experimental work.

Many materials weaken through fracturing when subjected to extreme stresses. By contrast, we show that breaking down repulsive bits of matter dispersed in a viscous liquid can cause a dramatic and irreversible increase in the dispersion’s elasticity. Anionically stabilized microscale emulsions subjected to a history of high-pressure microfluidic flow can develop an unusually large elastic modulus as droplets are ruptured to the nanoscale, yielding “nanonaise.” As the droplet size approaches the Debye screening length, the nanoemulsion vitrifies. Consequently, the onset of elasticity for disordered uniform nanoemulsions can occur at droplet volume fractions far below maximal random jamming of spheres.

We study the dynamics of a one-dimensional discrete flow with open boundaries—a series of moving point particles connected by ideal springs. These particles flow towards an inlet at constant velocity, pass into a region where they are free to move according to their nearest neighbor interactions, and then pass an outlet where they travel with a sinusoidally varying velocity. As the amplitude of the outlet oscillations is increased, we find that the resident time of particles in the chamber follows a bifurcating (Feigenbaum) route to chaos. This irregular dynamics may be related to the complex behavior of many particle discrete flows or is possibly a low-dimensional analogue of nonstationary flow in continuous systems.

The response of degree-correlated scale-free attractor networks to stimuli is studied. We show that degree-correlated scale-free networks are robust to random stimuli as well as the uncorrelated scale-free networks, while assortative (disassortative) scale-free networks are more (less) sensitive to directed stimuli than uncorrelated networks. We find that the degree correlation of scale-free networks makes the dynamics of attractor systems different from uncorrelated ones. The dynamics of correlated scale-free attractor networks results in the effects of degree correlation on the response to stimuli.

This paper presents a cellular automaton model without step back to simulate the pedestrian counter flow in a channel. The consideration of the surrounding environment when people make judgments on moving directions is added to a random walker model also without step back. Two types of walkers: the right walkers going to the right and the left walkers going to the left are taken into account. The characteristics of counterflow are clarified. Influences of the different interaction radius values and system sizes on movement are studied. Phase transition from free moving to jamming is observed with the increase of entrance density. It is found that the critical entrance density $p_c$ at the transition point does not depend on the system size when the interaction radius value is large. Simulation results are represented as a comparison with the random walker model.

The electromigration-induced shape evolution of two-dimensional vacancy islands on a crystal surface is studied using a continuum approach. We consider the regime where mass transport is restricted to terrace diffusion in the interior of the island. In the limit of fast attachment (detachment) kinetics a circle translating at constant velocity is a stationary solution of the problem. In contrast to earlier work [O. Pierre-Louis and T. L. Einstein, Phys. Rev. B 62, 13697 (2000)], we show that the circular solution remains linearly stable for arbitrarily large driving forces. The numerical solution of the full nonlinear problem nevertheless reveals a fingering instability at the trailing end of the island, which develops from finite amplitude perturbations and eventually leads to pinch off. Relaxing the condition of instantaneous attachment (detachment) kinetics, we obtain noncircular elongated stationary shapes in an analytic approximation that compares favorably to the full numerical solution.

We report analytical results for the development of instability of an interface between two immiscible, Newtonian fluid layers confined in a rotating annular Hele-Shaw cell. We perform a linear stability analysis and focus our study on the influence of both Coriolis force and curvature parameters on the interface instability growth rate. The results show that the Coriolis force does not alter the stability of a disturbance with a particular wave number but reduces the maximum growth rate. The results related to the role played by the confinement of the liquid layers are also shown to provide a modification of the fastest-growing mode and its corresponding linear growth rate.

This paper provides a way of focusing wide-angle charged-particle beams in multiple lens systems. In previous papers [H. Matsuda et al., Phys. Rev. E 71, 066503 (2005); 74, 036501 (2006)], it was shown that an ellipsoidal mesh, combined with electrostatic lenses, enables correction of spherical aberration over wide acceptance angles up to $\pm 60°$. In this paper, practical situations where ordinary electron lenses are arranged behind the wide-angle electrostatic lenses are taken into account using ray tracing calculation. For practical realization of the wide-angle lens systems, the acceptance angle is set to $\pm 50°$. We note that the output beams of the wide-angle electrostatic lenses have somewhat large divergence angles which cause unacceptable or non-negligible spherical aberration in additional lenses. A solution to this problem is presented showing that lens combinations to cancel spherical aberration are available, whereby wide-angle charged-particle beams can be finely focused with considerably reduced divergence angles less than $\pm 5°$.

Propagation, transmission and reflection properties of linearly polarized plane waves and arbitrarily short electromagnetic pulses in one-dimensional dispersionless dielectric media possessing an arbitrary space-time dependence of the refractive index are studied by using a two-component, highly symmetric version of Maxwell’s equations. The use of any slow varying amplitude approximation is avoided. Transfer matrices of sharp nonstationary interfaces are calculated explicitly, together with the amplitudes of all secondary waves produced in the scattering. Time-varying multilayer structures and spatiotemporal lenses in various configurations are investigated analytically and numerically in a unified approach. Several effects are reported, such as pulse compression, broadening and spectral manipulation of pulses by a spatiotemporal lens, and the closure of the forbidden frequency gaps with the subsequent opening of wave number band gaps in a generalized Bragg reflector.

It is well known that exact enumerations of close-packed dimers can be carried out for two-dimensional lattices. While details of results are now known for most lattices, due to the unique nature of the lattice structure, there has been no complete analysis for the kagomé lattice. Here we derive the close-form expression $(1∕3)$ $\ln \left(4xyz\right)$ for the free energy of close-packed dimers on the kagomé lattice, where $x$, $y$, and $z$ are dimer weights. We use two different approaches: the Kasteleyn method of evaluating a Pfaffian and an alternative vertex model formulation. Both methods lead to the same final expression. The correlation function between two dimers at a distance equal or greater than two lattice spacings is found to vanish identically.

The hierarchical reference theory (HRT) and the self-consistent Ornstein-Zernike approximation (SCOZA) are two liquid state theories that both furnish a largely satisfactory description of the critical region as well as the phase coexistence and equation of state in general. Furthermore, there are a number of similarities that suggest the possibility of a unification of both theories. Earlier in this respect we have studied consistency between the internal energy and free energy routes. As a next step toward this goal we here consider consistency with the compressibility route too, but we restrict explicit evaluations to a model whose exact solution is known showing that a unification works in that case. The model in question is the mean spherical model (MSM) which we here extend to a generalized MSM. For this case, we show that the correct solutions can be recovered from suitable boundary conditions through either SCOZA or HRT alone as well as by the combined theory. Furthermore, the relation between the HRT-SCOZA equations and those of SCOZA and HRT becomes transparent.

Sedimentation-diffusion equilibrium density profiles of suspensions of charge-stabilized colloids are calculated theoretically and by Monte Carlo (MC) simulations, both for a one-component model of colloidal particles interacting through pairwise screened-Coulomb repulsions and for a three-component model of colloids, cations, and anions with unscreened-Coulomb interactions. We focus on a state point for which experimental measurements are available [C. P. Royall et al., J. Phys.: Condens Matter 17, 2315 (2005)]. Despite the apparently different picture that emerges from the one- and three-component models (repelling colloids pushing each other to high altitude in the former, versus a self-generated electric field that pushes the colloids up in the latter), we find similar colloidal density profiles for both models from theory as well as simulation, thereby suggesting that these pictures represent different viewpoints of the same phenomenon. The sedimentation profiles obtained from an effective one-component model by MC simulations and theory, together with MC simulations of the multicomponent primitive model are consistent among themselves, but differ quantitatively from the results of a theoretical multicomponent description at the Poisson-Boltzmann level. We find that for small and moderate colloid charge the Poisson-Boltzmann theory gives profiles in excellent agreement with the effective one-component theory if a smaller effective charge is used. We attribute this discrepancy to the poor treatment of correlations in the Poisson-Boltzmann theory.

We study the dynamics of networks of inhibitory map-based bursting neurons. Linear analysis allows us to understand how the patterns of bursting are determined by network topology and how they depend on the strength of synaptic connections, when inhibition is balanced. Two kinds of patterns are found depending on the symmetry of the network: slow cyclic patterns riding on subthreshold oscillations where almost all neurons contribute bursts in a sparse manner and fast patterns of bursts in which only one of two mutually exclusive groups of neurons take part. We also discuss the properties of the neuron model that underlie the described phenomena, comment on the limitations of the technique of analysis, and point to some possible ways to overcome them.

We introduce an immunization method where the percentage of required vaccinations for immunity are close to the optimal value of a targeted immunization scheme of highest degree nodes. Our strategy retains the advantage of being purely local, without the need for knowledge on the global network structure or identification of the highest degree nodes. The method consists of selecting a random node and asking for a neighbor that has more links than himself or more than a given threshold and immunizing him. We compare this method to other efficient strategies on three real social networks and on a scale-free network model and find it to be significantly more effective.

We study a locally nonconservative self-organized branching process (SOBP) in an open system of excitable agents exhibiting spontaneous excitation and deexcitation. The SOBP achieves criticality even in the absence of energy conservation as the population relaxes to a stable state with no overexcited agent. Criticality is widely thought to happen only in a locally conservative SOBP. Our model explains the observed characteristic size in the size distribution of tuna fish schools and the neuronal avalanches in cortical networks.

Extreme times techniques, generally applied to nonequilibrium statistical mechanical processes, are also useful for a better understanding of financial markets. We present a detailed study on the mean first-passage time for the volatility of return time series. The empirical results extracted from daily data of major indices seem to follow the same law regardless of the kind of index thus suggesting an universal pattern. The empirical mean first-passage time to a certain level $L$ is fairly different from that of the Wiener process showing a dissimilar behavior depending on whether $L$ is higher or lower than the average volatility. All of this indicates a more complex dynamics in which a reverting force drives volatility toward its mean value. We thus present the mean first-passage time expressions of the most common stochastic volatility models whose approach is comparable to the random diffusion description. We discuss asymptotic approximations of these models and confront them to empirical results with a good agreement with the exponential Ornstein-Uhlenbeck model.

Nowadays there is a multitude of measures designed to capture different aspects of network structure. To be able to say if a measured value is expected or not, one needs to compare it with a reference model (null model). One frequently used null model is the ensemble of graphs with the same set of degrees as the original network. Here, we argue that this ensemble can give more information about the original network than effective values of network structural quantities. By mapping out this ensemble in the space of some low-level network structure—in our case, those measured by the assortativity and clustering coefficients—one can, for example, study where in the valid region of the parameter space the observed networks are. Such analysis suggests which quantities (or combination of quantities) are actively optimized during the evolution of the network. We use four very different biological networks to exemplify our method. Among other things, we find that high clustering might be a force in the evolution of protein interaction networks. We also find that all four networks are conspicuously robust to both random errors and targeted attacks.