In social systems, people communicate with each other and form groups based on their interests. The pattern of interactions, the network, and the ideas that flow on the network naturally evolve together. Researchers use simple models to capture the feedback between changing network patterns and ideas on the network, but little is understood about the role of past events in the feedback process. Here, we introduce a simple agent-based model to study the coupling between peoples’ ideas and social networks, and better understand the role of history in dynamic social networks. We measure how information about ideas can be recovered from information about network structure and, the other way around, how information about network structure can be recovered from information about ideas. We find that it is, in general, easier to recover ideas from the network structure than vice versa.

We apply analytical and numerical methods to study the linear stability of stripe patterns in two generalizations of the two-dimensional Swift-Hohenberg equation that include coupling to a mean flow. A projection operator is included in our models to allow exact stripe solutions. In the generalized models, stripes become unstable to the skew-varicose, oscillatory skew-varicose, and cross-roll instabilities, in addition to the usual Eckhaus and zigzag instabilities. We analytically derive stability boundaries for the skew-varicose instability in various cases, including several asymptotic limits. We also use numerical techniques to determine eigenvalues and hence stability boundaries of other instabilities. We extend our analysis to both stress-free and no-slip boundary conditions and we note a crossover from the behavior characteristic of no-slip to that of stress-free boundaries as the coupling to the mean flow increases or as the Prandtl number decreases. Close to the critical value of the bifurcation parameter, the skew-varicose instability has the same curvature as the Eckhaus instability provided the coupling to the mean flow is greater than a critical value. The region of stable stripes is completely eliminated by the cross-roll instability for large coupling to the mean flow.

We explore the driven and damped dynamics of two coupled particles evolving in a symmetric and periodic substrate potential that is subjected to a static bias force. In addition, each particle is time-periodically driven with the same magnitude as, but out of phase to, its counterpart. It is shown that, for a certain parameter regime, the coupled particles can become self-organized and go against the direction of the bias force. This self-organization involves the particles becoming frequency locked with the driving force, and thus periodic motion ensues. We employ numerical arguments to show that running periodic states provide solutions of the system. Further, heuristic evidence is provided explaining how the two particles can travel against the bias force. In an effort to unearth coupling phenomena within the system, a detailed analysis of how the coupling strength affects the nonlinear dynamics is carried out. We show that within a range of coupling strengths the existence of periodic running solutions associated with negative mobility. To examine the robustness of our results we compare the deterministic system with the corresponding Langevin system. It is shown that, below a critical temperature, the qualitative behavior of the system remains the same.

The small-angle scattering curves of deterministic mass fractals are studied and analyzed in momentum space. In the fractal region, the curve $I\left(q\right)q^D$ is found to be log-periodic with good accuracy, and the period is equal to the scaling factor of the fractal. Here, $D$ and $I\left(q\right)$ are the fractal dimension and the scattering intensity, respectively. The number of periods of this curve coincides with the number of fractal iterations. We show that the log-periodicity of $I\left(q\right)q^D$ in the momentum space is related to the log-periodicity of the quantity $g\left(r\right)r^{3-D}$ in the real space, where $g\left(r\right)$ is the pair distribution function. The minima and maxima positions of the scattering intensity are estimated explicitly by relating them to the pair distance distribution in real space. It is shown that the minima and maxima are damped with increasing polydispersity of the fractal sets; however, they remain quite pronounced even at sufficiently large values of polydispersity. A generalized self-similar Vicsek fractal with controllable fractal dimension is introduced, and its scattering properties are studied to illustrate the above findings. In contrast with the usual methods, the present analysis allows us to obtain not only the fractal dimension and the edges of the fractal region, but also the fractal iteration number, the scaling factor, and the number of structural units from which the fractal is composed.

Particles, bubbles, and drops carried by a fluid in a confined environment such as a pipe can be subjected to hydrodynamic lift forces, i.e., forces that are perpendicular to the direction of the flow. We investigated the positioning effect of lift forces acting on buoyant drops and bubbles suspended in a carrier fluid and flowing in a horizontal microchannel. We report experiments on drops of water in fluorocarbon liquid, and on bubbles of nitrogen in hydrocarbon liquid and silicone oil, inside microchannels with widths on the order of 0.1–1 mm. Despite their buoyancy, drops and bubbles could travel without contacting with the walls of channels; the most important parameters for reaching this flow regime in our experiments were the viscosity and the velocity of the carrier fluid, and the sizes of drops and bubbles. The dependencies of the transverse position of drops and bubbles on these parameters were investigated. At steady state, the trajectories of drops and bubbles approached the center of the channel for drops and bubbles almost as large as the channel, carried by rapidly flowing viscous liquids; among our experiments, these flow conditions were characterized by larger capillary numbers and smaller Reynolds numbers. Analytical models of lift forces developed for the flow of drops much smaller than the width of the channel failed to predict their transverse position, while computational fluid dynamic simulations of the experiments agreed better with the experimental measurements. The degrees of success of these predictions indicate the importance of confinement on generating strong hydrodynamic lift forces. We conclude that, inside microfluidic channels, it is possible to support and position buoyant drops and bubbles simply by flowing a single-stream (i.e., “sheathless”) carrier liquid that has appropriate velocity and hydrodynamic properties.

The Vlasov equation is simulated by following the characteristics of phase points in phase space. It is shown that by increasing the number of phase points, without enhancing the resolution of phase-space grid, the accuracy of the simulation will be improved. In addition, the phase-point spacing introduces a smaller scale than grid spacing on which fine structures might be more conveniently handled. In order to perform simulation with a large population of phase points, an alternative to the bilinear interpolation scheme is introduced that reduces the number of operations. It is shown that by randomizing initial phase-point velocities, the recurrence effect does not happen. Finally, the standard problem of linear and nonlinear Landau damping will be examined.

Brownian dynamics of a self-propelled particle in linear shear flow is studied analytically by solving the Langevin equation and in simulation. The particle has a constant propagation speed along a fluctuating orientation and is additionally subjected to a constant torque. In two spatial dimensions, the mean trajectory and the mean square displacement (MSD) are calculated as functions of time $t$ analytically. In general, the mean trajectories are cycloids that are modified by finite temperature effects. With regard to the MSD, different regimes are identified where the MSD scales with $t^{\nu }$ with $\nu =0,1,2,3,4$. In particular, an accelerated ($\nu =4$) motion emerges if the particle is self-propelled along the gradient direction of the shear flow.

In the literature, two quite different phase-field formulations for the problem of alloy solidification can be found. In the first, the material in the diffuse interfaces is assumed to be in an intermediate state between solid and liquid, with a unique local composition. In the second, the interface is seen as a mixture of two phases that each retain their macroscopic properties, and a separate concentration field for each phase is introduced. It is shown here that both types of models can be obtained by the standard variational procedure if a grand-potential functional is used as a starting point instead of a free energy functional. The dynamical variable is then the chemical potential instead of the composition. In this framework, a complete analogy with phase-field models for the solidification of a pure substance can be established. This analogy is then exploited to formulate quantitative phase-field models for alloys with arbitrary phase diagrams. The precision of the method is illustrated by numerical simulations with varying interface thickness.

We study the deformation of a network of entangled non-cross-linked semiflexible fibers subjected to compression. We show that the deformation is intermittent, heterogeneous, and dominated by the occurrence of avalanches. Avalanches imply relative fiber sliding and rearrangement and lead to a serrated stress-strain curve. A large fraction of the fibers in the system contribute to an avalanche, and the amplitudes of the sliding events are correlated spatially. This phenomenon is qualitatively similar in systems with and without friction between fibers and is not due to frictional stick slip.

Despite their importance for solar thermal power applications, phase-diagrams of molten salt mixture heat transfer fluids (HTFs) are not readily accessible from first principles. We present a molecular dynamics scheme general enough to identify eutectics of any HTF candidate mixture. The eutectic mixture and temperature are located using the liquid mixture free energy and the pure component solid-liquid free energy differences. The liquid mixture free energy is obtained using thermodynamic integration over particle identity transmutations sampled with molecular dynamics at a single temperature. Drawbacks of conventional phase diagram mapping methodologies are avoided by not considering solid mixtures, thereby evading expensive computations of solid phase free energies. Numerical results for binary and ternary mixtures of alkali nitrates agree well with experimental measurements.

We study the growth of perturbations in a uniformly collapsing cloud of self-gravitating Brownian particles. This problem shares analogies with the formation of large-scale structures in a universe experiencing a “big-crunch” or with the formation of stars in a molecular cloud experiencing gravitational collapse. Starting from the barotropic Smoluchowski-Poisson system, we derive a new equation describing the evolution of the density contrast in the comoving (collapsing) frame. This equation can serve as a prototype to study the process of self-organization in complex media with structureless initial conditions. We solve this equation analytically in the linear regime and compare the results with those obtained by using the “Jeans swindle” in a static medium. The stability criteria, as well as the laws for the time evolution of the perturbations, differ. The Jeans criterion is expressed in terms of a critical wavelength ${\lambda }_J$ while our criterion is expressed in terms of a critical polytropic index ${\gamma }_{4/3}$. In a static background, the system is stable for $\lambda <{\lambda }_J$ and unstable for $\lambda >{\lambda }_J$. In a collapsing cloud, the system is stable for $\gamma >{\gamma }_{4/3}$ and unstable for $\gamma <{\gamma }_{4/3}$. If $\gamma ={\gamma }_{4/3}$, it is stable for $\lambda <{\lambda }_J$ and unstable for $\lambda >{\lambda }_J$. We also study the fragmentation process in the nonlinear regime. We determine the growth of the skewness, the long-wavelength tail of the power spectrum and find a self-similar solution to the nonlinear equations valid for large times. Finally, we consider dissipative self-gravitating Bose-Einstein condensates with short-range interactions and show that, in a strong friction limit, the dissipative Gross-Pitaevskii-Poisson system is equivalent to the quantum barotropic Smoluchowski-Poisson system. This yields new types of nonlinear mean-field Fokker-Planck equations, including quantum effects.

We study the structural correlations and the nonlinear response to a driving force of a two-dimensional phase-field-crystal model with random pinning. The model provides an effective continuous description of lattice systems in the presence of disordered external pinning centers, allowing for both elastic and plastic deformations. We find that the phase-field crystal with disorder assumes an amorphous glassy ground state, with only short-ranged positional and orientational correlations, even in the limit of weak disorder. Under increasing driving force, the pinned amorphous-glass phase evolves into a moving plastic-flow phase and then, finally, a moving smectic phase. The transverse response of the moving smectic phase shows a vanishing transverse critical force for increasing system sizes.

We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the computation of the eigenvalues and the corresponding eigenvectors of local diffusion matrices. We demonstrate our algorithm by applying it to two examples of systems showing Hopf bifurcation. We argue that computing the eigenvectors associated to the eigenvalues of the diffusion matrix at local mesh points in the phase space enables one to define vector fields of stochastic eigendirections. In particular, the eigenvector associated to the lowest eigenvalue defines the path of minimum stochastic forcing in phase space, and a transform to a new coordinate system aligned with the eigenvectors can increase the predictability of the system.

A one-dimensional hopping model is useful for describing the motion of microscopic particles in a thermal noise environment. Recent experiments on the new generation of light-driven rotary molecular motors found that a motor in state $i$ can jump forward to state $i+1$ or $i+2$ or backward to state $i-1$ or $i-2$ directly. In this paper, inspired by these experiments, such a modified periodic one-dimensional hopping model with arbitrary period $N$ is studied theoretically. The mean velocity, effective diffusion constant, and mean dwell time in one single mechanochemical cycle are obtained. The corresponding results are illustrated and verified by being applied to the synthetic rotary molecular motors.

The effective capillary interaction potentials for small colloidal particles trapped at the surface of liquid droplets are calculated analytically. Pair potentials between capillary monopoles and dipoles, corresponding to particles floating on a droplet with a fixed center of mass and subjected to external forces and torques, respectively, exhibit a repulsion at large angular separations and an attraction at smaller separations, with the latter resembling the typical behavior for flat interfaces. This change of character is not observed for quadrupoles, corresponding to free particles on a mechanically isolated droplet. The analytical results are compared with the numerical minimization of the surface free energy of the droplet in the presence of spherical or ellipsoidal particles.

We present an ellipsometry study of the interface between thermotropic liquid crystals and liquid phases consisting of various binary mixtures of water and glycerol. The liquid-crystal samples contain a small constant amount of a surfactant which induces a homeotropic anchoring at the interface. We determine the smectic or nematic order at the interface in the temperature range above the liquid-crystal–isotropic transition while the water to glycerol ratio is varied, corresponding to a systematic modification of the polarity of the liquid phase. The surface-induced order becomes less pronounced with increasing glycerol concentration in the liquid phase. The observed behavior is compared with previous studies in which the surfactant concentration in the liquid-crystal bulk phase was varied. The results indicate that in both cases the magnitude of the surfactant coverage at the interface is the key quantity which determines the liquid-crystal surface order at the interface.

In population genetics, the Moran model describes the neutral evolution of a biallelic gene in a population of haploid individuals subjected to mutations. We show in this paper that this model can be mapped into an influence dynamical process on networks subjected to external influences. The panmictic case considered by Moran corresponds to fully connected networks and can be completely solved in terms of hypergeometric functions. Other types of networks correspond to structured populations, for which approximate solutions are also available. This approach to the classic Moran model leads to a relation between regular networks based on spatial grids and the mechanism of isolation by distance. We discuss the consequences of this connection for topopatric speciation and the theory of neutral speciation and biodiversity. We show that the effect of mutations in structured populations, where individuals can mate only with neighbors, is greatly enhanced with respect to the panmictic case. If mating is further constrained by genetic proximity between individuals, a balance of opposing tendencies takes place: increasing diversity promoted by enhanced effective mutations versus decreasing diversity promoted by similarity between mates. Resolution of large enough opposing tendencies occurs through speciation via pattern formation. We derive an explicit expression that indicates when speciation is possible involving the parameters characterizing the population. We also show that the time to speciation is greatly reduced in comparison with the panmictic case.

We demonstrate the dynamical characteristics of adaptive delayed-feedback control systems, exploiting a discrete-time adaptive control method derived for carrying out detailed analysis. In particular, the systems exhibit singularities such as power-law decay of the distribution of transient times and almost zero finite-time Lyapunov exponents. We can explain these results by characterizing such systems as having (1) a Jacobian matrix with unity eigenvalue in the whole phase space, and (2) parameters approaching a stability boundary proven to be identical with that of (nonadaptive) delayed-feedback control.

We study the dynamics of a model stochastic two-gene switch at the nucleotide and codon levels. First, we show that its stability, the mean lifetime of the noisy attractors, differs from that of a model where transcription and translation elongation are modeled as single-step delayed events, indicating the need of detailed models to study the dynamics of switches. Next, we vary the coupling between the two genes by varying the affinity of repressor proteins to the promoters and measure the mutual information between the two proteins times series. We find that there is a degree of coupling that maximizes information propagation between the two genes. This is explained by the effects of the coupling on mean and entropy of RNA and protein numbers of each gene, as well as correlation, 2-tuple entropy between the two proteins numbers, and, finally, the stability of the noisy attractors. We also find that increasing the rate of translation initiation increases the correlation between RNA and protein numbers and between the two proteins, due to increased stability of the noisy attractors. Increasing the rate of transcription or decreasing RNA degradation causes opposite effects to the correlation between RNA and proteins of each gene and the stability of the noisy attractors. Finally, we add a sequence-dependent transcription pause site and show that both its probability of occurrence, as well as its mean time length, affects the dynamics of the switch, further demonstrating the dependence of the dynamics of this circuit on sequence level events.

Recent studies revealed that reaction-diffusion (RD) dynamics can be significantly influenced by the structure of the underlying network. In this paper, a framework is established to study a closely related problem, i.e., to control the proportion of active particles in an RD process by adjusting the structure of the underlying diffusion network. Both distributed and centralized rewiring and reweighting control schemes are proposed for unweighted and weighted networks, respectively. Simulations show that the proportion of active particles can indeed be controlled to a certain extent even when the distributed control mechanism is totally random, while quite high precision can be achieved by centralized control schemes. More interestingly, it is found that the reactants in heterogeneous networks have wider controllable ranges than those in homogeneous networks with similar numbers of nodes and links, if only the weights of links are changed with a fixed bound. Therefore, it is believed that heterogeneous networks fit the changeable environment better, which provides another explanation for some common observations on many heterogeneous real-world networks.