Experimental observation of a permanent reflectional symmetry breaking (RSB) is reported for a laminar three-dimensional wake. Based on flow visualizations, a first bifurcation from the trivial steady symmetric state to a steady RSB state is characterized at $\mathrm{Re}=340$. The RSB state becomes unsteady after a second bifurcation at $\mathrm{Re}=410$. It is found that this RSB regime is persistent at large Reynolds numbers and is responsible for a bistable turbulent wake.

Epidemic spreading has been well studied in the past decade, where the main concentration is focused on the influence of network topology but little attention is paid to the individual's crisis awareness. We here study how the crisis awareness, i.e., personal self-protection, influences the epidemic spreading by presenting a susceptible-infected-recovered model with information-driven vaccination. We introduce two parameters to quantitatively characterize the crisis awareness. One is the information creation rate $\lambda$ and the other is the information sensitivity $\eta$. We find that the epidemic spreading can be significantly suppressed in both the homogeneous and heterogeneous networks when both $\lambda$ and $\eta$ are relatively large. More interesting is that the needed vaccine will be significantly reduced when the information is well spread, which is a good news for the poor countries and regions with limited resources.

Motivated by the observation that anomalous diffusion is a realistic feature in the dynamics of biological populations, we investigate its implications in a paradigmatic model for the evolution of a single species density $u(x,t)$. The standard model includes growth and competition in a logistic expression, and spreading is modeled through normal diffusion. Moreover, the competition term is nonlocal, which has been shown to give rise to spatial patterns. We generalize the diffusion term through the nonlinear form ${\partial }_{t}u(x,t)=D{\partial }_{xx}u{(x,t)}^{\nu }$ (with $D,\nu >0$), encompassing the cases where the state-dependent diffusion coefficient either increases ($\nu >1$) or decreases ($\nu <1$) with the density, yielding subdiffusion or superdiffusion, respectively. By means of numerical simulations and analytical considerations, we display how that nonlinearity alters the phase diagram. The type of diffusion imposes critical values of the model parameters for the onset of patterns and strongly influences their shape, inducing fragmentation in the subdiffusive case. The detection of the main persistent mode allows analytical prediction of the critical thresholds.

We introduce a concept of generalized synchronization, able to encompass the setting of collective synchronized behavior for mutually coupled systems and networking systems featuring complex topologies in their connections. The onset of the synchronous regime is confirmed by the dependence of the system's Lyapunov exponents on the coupling parameter. The presence of a generalized synchronization regime is verified by means of the nearest neighbor method.

In this paper we numerically investigate the influence of dissipation during particle collisions in an homogeneous turbulent velocity field by coupling a discrete element method to a lattice-Boltzmann simulation with spectral forcing. We show that even at moderate particle volume fractions the influence of dissipative collisions is important. We also investigate the transition from a regime where the turbulent velocity field significantly influences the spatial distribution of particles to a regime where the distribution is mainly influenced by particle collisions.

Coherent diffraction imaging (CDI) of single molecules at atomic resolution is a major goal for the x-ray free-electron lasers (XFELs). However, during an imaging pulse, the fast laser-induced ionization may strongly affect the recorded diffraction pattern of the irradiated sample. The radiation tolerance of the imaged molecule should then be investigated a priori with a dedicated simulation tool. The continuum approach is a powerful tool for modeling the evolution of irradiated large systems consisting of more than a few hundred thousand atoms. However, this method follows the evolution of average single-particle densities, and the experimentally recorded intensities reflect the spatial two-particle correlations. The information on these correlations is then inherently not accessible within the continuum approach. In this paper we analyze this limitation of continuum models and discuss the applicability of continuum models for imaging studies. We derive a formula to calculate scattered intensities (including both elastic and inelastic scattering) from the estimates obtained with a single-particle continuum model under conditions typical for CDI studies with XFELs. We demonstrate through numerical simulations that it describes the scattered signal with good accuracy. Two-particle correlation effects manifest themselves only in the region of low momentum transfers, together with the effects of the finite size of the sample. We also show that inelastic scattering on bound electrons can have a significant impact on the measured intensities: it contributes to the background that reduces the contrast of the recorded image. This effect is even more pronounced at larger momentum transfers. Therefore, whereas inelastic scattering can be neglected for nanocrystals, where Bragg scattering dominates, and in experiments imaging single objects at low resolution, it should be taken into account when planning atomic resolution imaging of nonperiodic samples. Finally, we show the effect of the electronic damage on the recorded total signal. Progressing damage does not change the positions of intensity peaks that correspond to the (fixed) positions of imaged ions. It only changes the contrast between intensity minima and maxima, which reduces the image contrast. Our results have implications for imaging-oriented studies of radiation damage performed with continuum models, as they define the limits of applicability of these models for CDI simulations.

We have developed a flexible framework for constructing Jastrow factors which allows for the introduction of terms involving arbitrary numbers of particles. The use of various three- and four-body Jastrow terms in quantum Monte Carlo calculations is investigated, including a four-body van der Waals-like term, and anisotropic terms. We have tested these Jastrow factors on one- and two-dimensional homogeneous electron gases, the Be, B, and O atoms, and the BeH, H${}_2$O, N${}_2$, and H${}_2$ molecules. Our optimized Jastrow factors retrieve more than 90$\%$ of the fixed-node diffusion Monte Carlo correlation energy in variational Monte Carlo for each system studied.

A method based on “small-deformation mechanical response” has been developed to locally resolve the Poisson's ratio via molecular dynamics simulations. The approach can be used for simple and composite materials to characterize systems with two or more continuous phases in the framework of periodic boundary conditions. The proposed technique represents a simple method to obtain a local mechanical description of complex systems. A polystyrene bulk, a silica bulk, and a polystyrene-silica heterogeneous composite material have been characterized under imposed strain. The results show the effects of local material inhomogeneities which are present in the glassy material and in the composite system. The Poisson's ratio spatial profiles for silica, the polystyrene bulk, and in the interphase region between the soft polymer bulk and the hard surface have also been calculated. The obtained local mechanical description can be employed in micromechanical models developed to predict the overall mechanical properties of multicomponent materials.

Pulsed laser irradiation of damaged solids promotes ultrafast nonequilibrium kinetics, on the submicrosecond scale, leading to microscopic modifications of the material state. Reliable theoretical predictions of this evolution can be achieved only by simulating particle interactions in the presence of large and transient gradients of the thermal field. We propose a kinetic Monte Carlo (KMC) method for the simulation of damaged systems in the extremely far-from-equilibrium conditions caused by the laser irradiation. The reference systems are nonideal crystals containing point defect excesses, an order of magnitude larger than the equilibrium density, due to a preirradiation ion implantation process. The thermal and, eventual, melting problem is solved within the phase-field methodology, and the numerical solutions for the space- and time-dependent thermal field were then dynamically coupled to the KMC code. The formalism, implementation, and related tests of our computational code are discussed in detail. As an application example we analyze the evolution of the defect system caused by P ion implantation in Si under nanosecond pulsed irradiation. The simulation results suggest a significant annihilation of the implantation damage which can be well controlled by the laser fluence.

Unidirectional pulse propagation equations [UPPE, Phys. Rev. E 70, 036604 (2004)] have provided a theoretical underpinning for computer-aided investigations into dynamics of high-power ultrashort laser pulses and have been successfully utilized for almost a decade. Unfortunately, they are restricted to applications in bulk media or, with additional approximations, to simple waveguide geometries in which only a few guided modes can approximate the propagating waveform. The purpose of this work is to generalize the directional pulse propagation equations to structures characterized by strong refractive index differences and material interfaces. We also outline a numerical solution framework that draws on the combination of the bulk-media UPPE method with single-frequency beam-propagation techniques.

The forward-reverse or FR method is an efficient bidirectional work method for determining the potential of mean force $w\left(z\right)$ and also supposedly gives in principle the position-dependent diffusion coefficient $D\left(z\right)$. Results from a variation called the OFR (oscillating FR) method suggest inconsistencies in the $D\left(z\right)$ values when calculated as prescribed by the FR method. A new steering protocol has thus been developed and applied to the OFR method for the accurate determination of $D\left(z\right)$ and also provides greater convergence for $w\left(z\right)$ in molecular dynamics simulations. The bulk diffusion coefficient for water was found to be $(6.03\pm 0.16)\times {10}^{-5}$ cm${}^2$/s at 350 K with system size dependence within the statistical error bars. Using this steering protocol, $D\left(z\right)$ and $w\left(z\right)$ for water permeating a dipalmitoylphosphatidylcholine (DPPC) bilayer were determined. The potential of mean force is shown to have a barrier of peak height, $w_{\text{max}}/\left(k_{B}T\right)=8.4$, with a width of about 10 Å on either side from the membrane center. The diffusion constant is shown to be highest in the core region of the membrane [peak value $\sim (8.0\pm 0.8)\times {10}^{-5}$ cm${}^2$/s], lowest in the head-group region [minimum value $\sim (2.0\pm 0.3)\times {10}^{-5}$ cm${}^2$/s], and to tend toward the bulk value as the water molecule leaves the membrane. The permeability coefficient $P$ for H${}_2$O in DPPC was determined using the simulated $D\left(z\right)$ and $w\left(z\right)$ to give values of $(0.129\pm 0.075)$ cm/s at 323 K and $(0.141\pm 0.043)$ cm/s at 350 K. The results show more spatial detail than results presented in previous work while reducing the computational and user effort.

While the existence of polar ordered states in active systems is well established, the dynamics of the self-assembly processes are still elusive. We study a lattice gas model of self-propelled elongated particles interacting through excluded volume and alignment interactions, which shows a phase transition from an isotropic to a polar ordered state. By analyzing the ordering process we find that the transition is driven by the formation of a critical nucleation cluster and a subsequent coarsening process. Moreover, the time to establish a polar ordered state shows a power-law divergence.

The formation and fragmentation of networks are typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size, examining the emergence of a giant component. This approach does not study the effects of evolving network structure on dynamics that occur at the nodes, such as the synchronization of oscillators and the spread of information, epidemics, and neuronal excitations. We introduce and analyze an alternative link-formation rule, called social climber (SC) attachment, that may be combined with arbitrary percolation models to produce a phase transition using the largest eigenvalue of the network adjacency matrix as the order parameter. This eigenvalue is significant in the analyses of many network-coupled dynamical systems in which it measures the quality of global coupling and is hence a natural measure of connectivity. We highlight the important self-organized properties of SC attachment and discuss implications for controlling dynamics on networks.

We propose a new pairwise Fermi updating rule by considering a social average payoff when an agent copies a neighbor's strategy. In the update rule, a focal agent compares her payoff with the social average payoff of the same strategy that her pairwise opponent has. This concept might be justified by the fact that people reference global and, somehow, statistical information, not local information when imitating social behaviors. We presume several possible ways for the social average. Simulation results prove that the social average of some limited agents realizes more significant cooperation than that of the entire population.

We investigate the dynamics of a broad class of stochastic copying processes on a network that includes examples from population genetics (spatially structured Wright-Fisher models), ecology (Hubbell-type models), linguistics (the utterance selection model), and opinion dynamics (the voter model) as special cases. These models all have absorbing states of fixation where all the nodes are in the same state. Earlier studies of these models showed that the mean time when this occurs can be made to grow as different powers of the network size by varying the degree distribution of the network. Here we demonstrate that this effect can also arise if one varies the asymmetry of the copying dynamics while holding the degree distribution constant. In particular, we show that the mean time to fixation can be accelerated even on homogeneous networks when certain nodes are very much more likely to be copied from than copied to. We further show that there is a complex interplay between degree distribution and asymmetry when they may covary, and that the results are robust to correlations in the network or the initial condition.

In a recent paper [Zuriguel et al., Phys. Rev. Lett. 107, 278001 (2011)] it has been shown that the presence of an obstacle above the outlet can significatively reduce the clogging probability of granular matter pouring from a silo. The amount of this reduction strongly depends on the obstacle position. In this work, we present new measurements to analyze different outlet sizes, extending foregoing results and revealing that the effect of the obstacle is enhanced as the outlet size is increased. In addition, the effect of the obstacle position on the flow rate properties and in the geometrical features of arches is studied. These results reinforce previous evidence of the pressure reduction induced by the obstacle. In addition, it is shown how the mean avalanche size and the average flow rate are not necessarily linked. On the other hand, a close relationship is suggested between the mean avalanche size and the flow rate fluctuations.

Regular tetrahedra have been demonstrated recently giving high packing density in random configurations. However, it is unknown whether the random-packing density of tetrahedral particles with other shapes can reach an even higher value. A numerical investigation on the random packing of regular and irregular tetrahedral particles is carried out. Shape effects of rounded corner, eccentricity, and height on the packing density of tetrahedral particles are studied. Results show that altering the shape of tetrahedral particles by rounding corners and edges, by altering the height of one vertex, or by lateral displacement of one vertex above its opposite face, all individually have the effect of reducing the random-packing density. In general, the random-packing densities of irregular tetrahedral particles are lower than that of regular tetrahedra. The ideal regular tetrahedron should be the shape which has the highest random-packing density in the family of tetrahedra, or even among convex bodies. An empirical formula is proposed to describe the rounded corner effect on the packing density, and well explains the density deviation of tetrahedral particles with different roundness ratios. The particles in the simulations are verified to be randomly packed by studying the pair correlation functions, which are consistent with previous results. The spherotetrahedral particle model with the relaxation algorithm is effectively applied in the simulations.

Space-filling assemblies of athermal hydrophobic particles floating at an air-water interface, called particle rafts, are shown to undergo an unusual phase transition between two amorphous states, i.e., a low density “less-rigid” state and a high density “more-rigid” state, as a function of particulate number density ($\Phi$). The former is shown to be a capillary bridged solid and the latter is shown to be a frictionally coupled one. Simultaneous studies involving direct imaging as well as measuring its mechanical response to longitudinal and shear stresses show that the transition is marked by a subtle structural anomaly and a weakening of the shear response. The structural anomaly is identified from the variation of the mean coordination number, mean area of the Voronoi cells, and spatial profile of the displacement field with $\Phi$. The weakened shear response is related to local plastic instabilities caused by the depinning of the contact line of the underlying fluid on the rough surfaces of the particles.

Control of the morphologies of polymer films and layers by addition of nanosize particles is a novel technique for design of nanomaterials and is also at the core of some important biological processes. In order to facilitate the analysis of experimental data and enable predictive engineering of such systems, solid theoretical understanding is necessary. We study theoretically and computationally the behavior of plane-grafted polymer layers (brushes) in athermal solvent, decorated with small nanoparticle inclusions, using mean field theory and coarse-grained simulations. We show that the morphology of such layers is very sensitive to the interaction between the polymers and the nanoparticles and to the nanoparticle density. In particular, the mean field model shows that for a certain range of parameters, the nanoparticles induce a sharp transition in the layer height, accompanied by a sharp increase in the number of adsorbed nanoparticles. At other parameter values, the layer height depends smoothly on the nanoparticle concentration. Predictions of the theoretical model are verified by Langevin dynamics simulations. The results of the paper are in qualitative agreement with experiments on in vitro models of biological transport and suggest strategies for morphological control of nanocomposite materials.

Plant petioles and stems are hierarchical cellular structures, displaying structural features defined at multiple length scales. One or more of the intermediate hierarchical levels consists of tissues, in which the cellular distribution is quasirandom. The current work focuses on the realistic modeling of plant tissue microstructures. The finite-edge centroidal Voronoi tessellation (FECVT) is here introduced to overcome the drawbacks of the semi-infinite edges of a typical Voronoi model. FECVT can generate a realistic model of a tissue microstructure, which might have finite edges at its border, be defined by a boundary contour of any shape, and include complex heterogeneity and cellular gradients. The centroid-based Voronoi tessellation is applied to model the microstructure of the Philodendron melinonii petiole and the Arabidopsis thaliana stem, which both display intense cellular gradients. FECVT coupled with a digital image processing algorithm is implemented to capture the nonperiodic microstructures of plant tissues. The results obtained via this method satisfactorily obey the geometric, statistical, and topological laws of naturally evolved cellular solids. The predicted models are also validated by experimental data.