A dynamical model of a soft, thermally fluctuating two-dimensional tube is used to study the effect of thermal fluctuations of a confining environment on diffusive transport. The tube fluctuations in both space and time are driven by Brownian motion and suppressed by surface tension and the rigidity of the surrounding environment. The dynamical fluctuations modify the concentration profile boundary condition at the tube surface. They decrease the diffusive transport rate through the tube for two important cases: uniform tube fluctuations (wave vector, $q=0$ mode) for finite tube lengths and fluctuations of any wave vector for infinitely long tubes.

Complex fluids in shear flow and biased dynamics in crowded environments exhibit counterintuitive features which are difficult to address both at a theoretical level and by molecular dynamic simulations. To understand some of these features we study a schematic model of a highly viscous liquid, the two-dimensional Kob-Andersen kinetically constrained model, driven into nonequilibrium steady states by a uniform non-Hamiltonian force. We present a detailed numerical analysis of the microscopic behavior of the model, including transversal and longitudinal spatial correlations and dynamic heterogeneities. In particular, we show that at high particle density the transition from positive to negative resistance regimes in the current vs field relation can be explained via the emergence of nontrivial structures that intermittently trap the particles and slow down the dynamics. We relate such spatial structures to the current vs field relation in the different transport regimes.

We investigate percolation transitions in a nonlocal network model numerically. In this model, each node has an exclusive partner and a link is forbidden between two nodes whose $r$-neighbors share any exclusive pair. The $r$-neighbor of a node $x$ is defined as a set of at most $N^r$ neighbors of $x$, where $N$ is the total number of nodes. The parameter $r$ controls the strength of a nonlocal effect. The system is found to undergo a percolation transition belonging to the mean-field universality class for $r<1/2$. On the other hand, for $r>1/2$, the system undergoes a peculiar phase transition from a nonpercolating phase to a quasicritical phase where the largest cluster size $G$ scales as $G\sim N^{\alpha }$ with $\alpha =0.74\left(1\right)$. In the marginal case with $r=1/2$, the model displays a percolation transition that does not belong to the mean-field universality class.

It is shown by means of a $1/m$ expansion about the large-$m$ limit of the $m$-vector spin glass that the value of the intercept of the de Almeida-Thouless line on the zero temperature axis $h_{AT}$ is proportional to $T_c\left(d\right)$, the zero-field transition temperature of the large-$m$ model in $d$ dimensions. Since numerical studies indicate that $T_c\left(d\right)=0$ for $d\le 6$, it follows that there should be no Almeida-Thouless line for $d\le 6$.

Dense packings of hard particles have important applications in many fields, including condensed matter physics, discrete geometry, and cell biology. In this paper, we employ a stochastic search implementation of the Torquato-Jiao adaptive-shrinking-cell (ASC) optimization scheme [Nature (London) 460, 876 (2009)] to find maximally dense particle packings in $d$-dimensional Euclidean space ${\mathbb{R}}^d$. While the original implementation was designed to study spheres and convex polyhedra in $d\ge 3$, our implementation focuses on $d=2$ and extends the algorithm to include both concave polygons and certain complex convex or concave nonpolygonal particle shapes. We verify the robustness of this packing protocol by successfully reproducing the known putative optimal packings of congruent copies of regular pentagons and octagons, then employ it to suggest dense packing arrangements of congruent copies of certain families of concave crosses, convex and concave curved triangles (incorporating shapes resembling the Mercedes-Benz logo), and “moonlike” shapes. Analytical constructions are determined subsequently to obtain the densest known packings of these particle shapes. For the examples considered, we find that the densest packings of both convex and concave particles with central symmetry are achieved by their corresponding optimal Bravais lattice packings; for particles lacking central symmetry, the densest packings obtained are nonlattice periodic packings, which are consistent with recently-proposed general organizing principles for hard particles. Moreover, we find that the densest known packings of certain curved triangles are periodic with a four-particle basis, and we find that the densest known periodic packings of certain moonlike shapes possess no inherent symmetries. Our work adds to the growing evidence that particle shape can be used as a tuning parameter to achieve a diversity of packing structures.

We present a comprehensive theoretical study of finite-size effects in the relaxation dynamics of glass-forming liquids. Our analysis is motivated by recent theoretical progress regarding the understanding of relevant correlation length scales in liquids approaching the glass transition. We obtain predictions both from general theoretical arguments and from a variety of specific perspectives: mode-coupling theory, kinetically constrained and defect models, and random first-order transition theory. In the last approach, we predict in particular a nonmonotonic evolution of finite-size effects across the mode-coupling crossover due to the competition between mode-coupling and activated relaxation. We study the role of competing relaxation mechanisms in giving rise to nonmonotonic finite-size effects by devising a kinetically constrained model where the proximity to the mode-coupling singularity can be continuously tuned by changing the lattice topology. We use our theoretical findings to interpret the results of extensive molecular dynamics studies of four model liquids with distinct structures and kinetic fragilities. While the less fragile model only displays modest finite-size effects, we find a more significant size dependence evolving with temperature for more fragile models, such as Lennard-Jones particles and soft spheres. Finally, for a binary mixture of harmonic spheres we observe the predicted nonmonotonic temperature evolution of finite-size effects near the fitted mode-coupling singularity, suggesting that the crossover from mode-coupling to activated dynamics is more pronounced for this model. Finally, we discuss the close connection between our results and the recent report of a nonmonotonic temperature evolution of a dynamic length scale near the mode-coupling crossover in harmonic spheres.

Crawling cells exhibit a variety of cell shape dynamics, ranging from complex ruffling and bubbling to oscillatory protrusion and retraction. Periodic shape changes during cell migration are recorded in fast-moving fish epithelial keratocytes where sticking and slipping at opposite sides of the cell's broad trailing edge generate bipedal locomotion. Barnhart et al. [Biophys. J. 98, 933 (2010)] recently proposed a mechanical spring model specifically designed to capture bipedal locomotion in these cells. We extend their model by benchmarking the dynamics of four mechanical configurations against those of crawling keratocytes. Our analysis shows that elastic coupling to the cell nucleus is necessary to generate its lateral motion. We select one configuration to study the effects of cell elasticity, size, and aspect ratio on crawling dynamics. This configuration predicts that shape dynamics are highly dependent on the lamellipodial elasticity but less sensitive to elasticity at the trailing edge. The model predicts a wide range of dynamics seen in actual crawling keratocytes, including coherent bipedal, coherent nonbipedal, and decoherent motions. This work highlights how the dynamical behavior of crawling cells can be derived from mechanical properties through which biochemical factors may operate to regulate cellular locomotion.

We numerically investigate the heterogeneity in cluster sizes in the two-dimensional Ising model and verify its scaling form recently proposed in the context of percolation problems [Phys. Rev. E 84, 010101(R) (2011)]. The scaling exponents obtained via the finite-size scaling analysis are shown to be consistent with theoretical values of the fractal dimension $d_f$ and the Fisher exponent $\tau$ for the cluster distribution. We also point out that strong finite-size effects exist due to the geometric nature of the cluster-size heterogeneity.

A bimolecular homogeneous irreversible reaction of the kind $A+B\to C$ is simulated in a plane channel as a base example of reactive transport processes taking place at the microscale within porous and/or fractured media. The numerical study explores the way microscale processes embedded in dimensionless quantities such as Péclet (Pe) and Damköhler (Da) numbers propagate to upscaled coefficients describing effective system dynamics. The microscale evolution of the reactant concentrations is obtained through a particle-based numerical method which has been specifically tailored to the considered problem. Key results include a complete documentation of the process evolution for a wide range of Pe and Da, in terms of the global reaction rate, space-time distribution of reactants, and local mixing features leading to characterization of effective reaction and dispersion coefficients governing a section-averaged upscaled model of the system. The robustness of previously presented theoretical analyses concerning closures of volume-averaged (upscaled) formulations is assessed. The work elucidates the dependence of the effective dispersion and reactive parameters on the microscale mixing and reactive species evolution. Our results identify the role played by Da and Pe on the occurrence of incomplete mixing of reactants, which affects the features of the reactive transport scenario.

We study the diffusion of influence in random multiplex networks where links can be of $r$ different types, and, for a given content (e.g., rumor, product, or political view), each link type is associated with a content-dependent parameter $c_i$ in $[0,\infty ]$ that measures the relative bias type $i$ links have in spreading this content. In this setting, we propose a linear threshold model of contagion where nodes switch state if their “perceived” proportion of active neighbors exceeds a threshold $\tau$. Namely a node connected to $m_i$ active neighbors and $k_i-m_i$ inactive neighbors via type $i$ links will turn active if $\sum c_i{m}_i/\sum c_i{k}_i$ exceeds its threshold $\tau$. Under this model, we obtain the condition, probability and expected size of global spreading events. Our results extend the existing work on complex contagions in several directions by (i) providing solutions for coupled random networks whose vertices are neither identical nor disjoint, (ii) highlighting the effect of content on the dynamics of complex contagions, and (iii) showing that content-dependent propagation over a multiplex network leads to a subtle relation between the giant vulnerable component of the graph and the global cascade condition that is not seen in the existing models in the literature.

The study of networks has become a substantial interdisciplinary endeavor that encompasses myriad disciplines in the natural, social, and information sciences. Here we introduce a framework for constructing taxonomies of networks based on their structural similarities. These networks can arise from any of numerous sources: They can be empirical or synthetic, they can arise from multiple realizations of a single process (either empirical or synthetic), they can represent entirely different systems in different disciplines, etc. Because mesoscopic properties of networks are hypothesized to be important for network function, we base our comparisons on summaries of network community structures. Although we use a specific method for uncovering network communities, much of the introduced framework is independent of that choice. After introducing the framework, we apply it to construct a taxonomy for 746 networks and demonstrate that our approach usefully identifies similar networks. We also construct taxonomies within individual categories of networks, and we thereby expose nontrivial structure. For example, we create taxonomies for similarity networks constructed from both political voting data and financial data. We also construct network taxonomies to compare the social structures of 100 Facebook networks and the growth structures produced by different types of fungi.

Using high-resolution particle tracking velocimetry, we study the effects of the forcing geometry on the statistics of an electromagnetically stirred thin-layer flow. We consider two forcing arrangements: one that produces a lattice of vortices as a base flow, and one that produces an array of shear bands. We find that the vortex flow drives stronger fluctuating kinetic energy while the shear-band flow leads to more intense fluctuating velocity gradients. We explain our results by considering the spectral flow of energy in the system. Our results have implications for the design of two-dimensional flow experiments.

Using direct numerical simulations with grids of up to ${512}^3$ points, we investigate long-time properties of three-dimensional magnetohydrodynamic turbulence in the absence of forcing and examine in particular the roles played by the quadratic invariants of the system and the symmetries of the initial configurations. We observe that when sufficient accuracy is used, initial conditions with a high degree of symmetries, as in the absence of helicity, do not travel through parameter space over time, whereas by perturbing these solutions either explicitly or implicitly using, for example, single precision for long times, the flows depart from their original behavior and can either become strongly helical or have a strong alignment between the velocity and the magnetic field. When the symmetries are broken, the flows evolve towards different end states, as already predicted by statistical arguments for nondissipative systems with the addition of an energy minimization principle. Increasing the Reynolds number by an order of magnitude when using grids of ${64}^3$–${512}^3$ points does not alter these conclusions. Furthermore, the alignment properties of these flows, between velocity, vorticity, magnetic potential, induction, and current, correspond to the dominance of two main regimes, one helically dominated and one in quasiequipartition of kinetic and magnetic energies. We also contrast the scaling of the ratio of magnetic energy to kinetic energy as a function of wave number to the ratio of eddy turnover time to Alfvén time as a function of wave number. We find that the former ratio is constant with an approximate equipartition for scales smaller than the largest scale of the flow, whereas the ratio of time scales increases with increasing wave number.

Inspired by the chaotic waterwheel invented by Malkus and Howard about 40 years ago, we have developed a gas turbine that randomly switches the sense of rotation between clockwise and counterclockwise. The nondimensionalized expressions for the equations of motion of our turbine are represented as a starlike network of many Lorenz subsystems sharing the angular velocity of the turbine rotor as the central node, referred to as augmented Lorenz equations. We show qualitative similarities between the statistical properties of the angular velocity of the turbine rotor and the velocity field of large-scale wind in turbulent Rayleigh-Bénard convection reported by Sreenivasan et al. [Phys. Rev. E 65, 056306 (2002)]. Our equations of motion achieve the random reversal of the turbine rotor through the stochastic resonance of the angular velocity in a double-well potential and the force applied by rapidly oscillating fields. These results suggest that the augmented Lorenz model is applicable as a dynamical model for the random reversal of turbulent large-scale wind through cessation.

This work focuses on an improved multicomponent interparticle-potential lattice Boltzmann model. The model results in viscosity-independent equilibrium densities and is capable of simulating kinematic viscosity ratios greater than 1000. External forces are incorporated into the discrete Boltzmann equation, rather than through an equilibrium velocity shift as in the original Shan and Chen (hereafter, SC) model. The model also requires the derivation of a momentum conserving effective velocity, which is substituted into the equilibrium distribution function and applies to both the single- and multiple-relaxation-time formulations. Additionally, higher-order isotropy is used in the calculation of the fluid-fluid interaction forces to reduce the magnitude of spurious currents (i.e., numerical errors) in the vicinity of interfaces. First, we compare the model to the SC model for static bubble simulations. We demonstrate that the model results in viscosity-independent equilibrium bubble densities for a wide range of kinematic viscosities, which is not the case for the SC model. Furthermore, we show that the model is capable of simulating stable bubbles for kinematic viscosity ratios greater than 1000 (when higher-order isotropy is used), whereas the SC model is known to be limited to kinematic viscosity ratios on the order of 10. Next we verify the model for surface tension via Laplace's law and show that the model results in the same surface tension values for a range of kinematic viscosities and kinematic viscosity ratios of 10, 100, and 1000. The model is also verified for layered cocurrent flow though parallel plates. We show that the simulated velocity profiles preserve continuity at the interface for kinematic viscosity ratios ranging from 0.001 to 1000 and that the model accurately predicts nonwetting and wetting phase relative permeability for kinematic viscosity ratios of 0.01 to 100.

We perform classical nonequilibrium molecular dynamics simulations to calculate heat flow through a microscopic junction connecting two larger reservoirs. In contrast to earlier papers, we also include the reservoirs in the simulated region to study the effect of the bulk-nanostructure interfaces and the bulk conductance. The scalar Fermi-Pasta-Ulam (FPU) model is used to describe the effects of anharmonic interactions in a simple manner. The temperature profile close to the junction in the low-temperature limit is shown to exhibit strong directional features that fade out when temperature increases. Simulating both the FPU chain and the two bulk regions is also shown to eliminate the nonmonotonous temperature variations found for simpler geometries and models. We show that, with sufficiently large reservoirs, the temperature profile in the chain does not depend on the details of thermalization used at the boundaries.

A nonlinear dynamics approach can be used in order to quantify complexity in written texts. As a first step, a one-dimensional system is examined: two written texts by one author (Lewis Carroll) are considered, together with one translation into an artificial language (i.e., Esperanto) are mapped into time series. Their corresponding shuffled versions are used for obtaining a baseline. Two different one-dimensional time series are used here: one based on word lengths (LTS), the other on word frequencies (FTS). It is shown that the generalized Hurst exponent $h\left(q\right)$ and the derived $f\left(\alpha \right)$ curves of the original and translated texts show marked differences. The original texts are far from giving a parabolic $f\left(\alpha \right)$ function, in contrast to the shuffled texts. Moreover, the Esperanto text has more extreme values. This suggests cascade model-like, with multiscale time-asymmetric features as finally written texts. A discussion of the difference and complementarity of mapping into a LTS or FTS is presented. The FTS $f\left(\alpha \right)$ curves are more opened than the LTS ones.

We study the statistical mechanics of a model glassy system based on sudoku, a familiar and popular mathematical puzzle. Sudoku puzzles provide a very rare example of a class of frustrated systems with a unique ground state without symmetry. Here, the puzzle is recast as a thermodynamic system where the number of violated rules defines the energy. We use Monte Carlo simulation to show that the “sudoku Hamiltonian” exhibits two transitions as a function of temperature, a paramagnetic, and a glass transition. Of these, the intermediate condensed phase is the only one that visits the ground state (i.e., it solves the puzzle, though this is not the purpose of the study). Both transitions are associated with an entropy change, paramagnetism measured from the dynamics of the Monte Carlo run, showing a peak in specific heat, while the residual glass entropy is determined by finding multiple instances of the glass by repeated annealing. There are relatively few such simple models for frustrated or glassy systems that exhibit both ordering and glass transitions; sudoku puzzles are unique for the ease with which they can be obtained, with the proof of the existence of a unique ground state via the satisfiability of all constraints. Simulations suggest that in the glass phase there is an increase in information entropy with lowering temperature. In fact, we have shown that sudoku puzzles have the type of rugged energy landscape with multiple minima that typifies glasses in many physical systems. This puzzling result is a manifestation of the paradox of the residual glass entropy. These readily available puzzles can now be used as solvable model Hamiltonian systems for studying the glass transition.

The statistics of the first passage time in connection with the quasideterministic (QD) approach is used to characterize the non-Markovian decay process of the unstable state of an electrically charged Brownian particle under the influence of an electromagnetic field. We consider a constant magnetic field and a fluctuating electric field, which satisfies the properties of a Gaussian exponentially correlated noise. It is shown that at the beginning of the decay process, the magnetic field is strongly coupled to the noise correlation time and thus the requirements of the QD approach are not satisfied. Only in the approximation of a weak coupling between both parameters can the time characterization of the decay process be successfully achieved. Our theoretical approach relies on a Langevin equation for the charged particle in an arbitrary two-dimensional unstable potential and applies to a bistable potential as a particular case.

We have carried out a theoretical study of the effect of the electric field $\mathbf{\text{E}}$ on the thermodynamical properties and surface tension $\gamma$ of free-standing smectic films. Calculations, based upon the extended McMillan approach with anisotropic forces, show a stepwise reduction and increase of the values of the Helmholtz free energy $f$ and $\gamma$, respectively, per partially fluorinated 5-$n$-alkyl-2-[4-$n$-(perfluoroalkyl-metheleneoxy)phenyl] (H10F5MOPP) molecule, as the temperature is raised above that for the bulk smectic-$A$–isotropic transition. Calculations show that $\mathbf{\text{E}}$ may not only affect the layer-thinning transition sequence, but also change the first multilayer jump in the thickness and increase the value of $\gamma$ per H10F5MOPP molecule. Reasonable agreement between the theoretically predicted and the experimentally obtained data on $\gamma$ of the partially fluorinated H10F5MOPP film has been obtained.