PHYSICAL REVIEW E

Frequency-dependent fluid flow in electrolytes on microelectrodes subjected to ac voltages has recently been reported. The fluid flow is predominant at frequencies of the order of the relaxation frequency of the electrode-electrolyte system. The mechanism responsible for this motion has been termed ac electro-osmosis: a continuous flow driven by the interaction of the oscillating electric field and the charge at the diffuse double layer on the electrodes. This paper develops the basis of a theoretical approach to this problem using a linear double layer analysis. The theoretical results are compared with the experiments, and a good correlation is found.

Under the influence of an ac electric field, electrolytes on planar microelectrodes exhibit fluid flow. The nonuniform electric field generated by the electrodes interacts with the suspending fluid through a number of mechanisms, giving rise to body forces and fluid flow. This paper presents the detailed experimental measurements of the velocity of fluid flow on microelectrodes at frequencies below the charge relaxation frequency of the electrolyte. The velocity of latex tracer particles was measured as a function of applied signal frequency and potential, electrolyte conductivity, and position on the electrode surface. The data are discussed in terms of a linear model of ac electroosmosis: the interaction of the nonuniform ac field and the induced electrical double layer.

We introduce a lattice gas model of cluster growth via the diffusive aggregation of particles in a closed system obeying a local, deterministic, microscopically reversible dynamics. This model roughly corresponds to placing the irreversible diffusion limited aggregation model (DLA) in contact with a heat bath. Particles release latent heat when aggregating, while singly connected cluster members can absorb heat and evaporate. The heat bath is initially empty, hence we observe the flow of entropy from the aggregating gas of particles into the heat bath, which is being populated by diffusing heat tokens. Before the population of the heat bath stabilizes, the cluster morphology (quantified by the fractal dimension) is similar to a standard DLA cluster. The cluster then gradually anneals, becoming more tenuous, until reaching configurational equilibrium when the cluster morphology resembles a quenched branched random polymer. As the microscopic dynamics is invertible, we can reverse the evolution, observe the inverse flow of heat and entropy, and recover the initial condition. This simple system provides an explicit example of how macroscopic dissipation and self-organization can result from an underlying microscopically reversible dynamics. We present a detailed description of the dynamics for the model, discuss the macroscopic limit, and give predictions for the equilibrium particle densities obtained in the mean field limit. Empirical results for the growth are then presented, including the observed equilibrium particle densities, the temperature of the system, the fractal dimension of the growth clusters, scaling behavior, finite size effects, and the approach to equilibrium. We pay particular attention to the temporal behavior of the growth process and show that the relaxation to the maximum entropy state is initially a rapid nonequilibrium process, then subsequently it is a quasistatic process with a well defined temperature.

We have investigated the onset of avalanches in fine, cohesive granular materials. In our experiments shear stress is generated by tilting an initialized bed of powder and increasing the angle of tilt until the powder avalanches. We find that the angle alpha of the avalanche decreases with increasing bed width. The avalanche depth increases with the bed width and, in all cases, is of the order of several millimeters, which is much greater than the particle size. We carry out a macroscopic analysis of the avalanche process based on Coulomb's method of wedges. This analysis shows the fundamental role played by powder cohesion and boundary conditions on avalanches in fine cohesive powders. This behavior contrasts with the behavior of noncohesive grains, such as dry sand, where avalanches consist of superficial layers of about ten grains. The reason behind this is that for our experimental powders (particle diameter approximately 10 &mgr;m) the van der Waals interparticle adhesive force exceeds several orders of magnitude particle weight. Adhesive forces oppose gravity, and as a result fine cohesive powders settle in very open structures as compared to noncohesive granular materials. Because of the dominance of adhesive forces over particle weight, our materials behave more like wet sand.

The settling of inertial particles in 2D vertical flows is investigated in the limit where the particle inertia, the free-fall terminal velocity, and the flow unsteadiness can be treated as perturbations. The generic case of recirculation cells bounded by a set of separatrix streamlines forming a heteroclinic cycle of fluid points' dynamics is considered. The (weak) unsteadiness of the flow generally induces a chaotic tangle near the heteroclinic cycle, leading to the apparent diffusion of fluid elements through the boundary. For inertial particles this complex motion can also exist in spite of inertia and sedimentation, provided the Stokes number is below some critical value $St_c$. It is shown that $St_c= Pe^{-1}/|Fr^{-1}\pm u_{0c}^2|$, where $Pe$ is an effective Peclet number related to the diffusion of fluid points through the boundary, $Fr$ is the Froude number based on the horizontal distance between the end points of the separatrix streamline, and $u_0^2$ is the non-dimensional curvature-weighted average of the squared velocity of the steady fluid flow along this separatrix. The $\pm$ sign is positive if gravity and centrifugation act in the same direction, and negative otherwise. When $St < St_c$, particles moving near the separatrix streamline can enter and exit the cell in a complex manner. When $St > St_c$ a regular motion takes place. Trapping can still exist in this case, since particles can be driven towards the interior of the cell in a regular manner, under the effect of either gravity or curvature, or both.

Information flow or information transfer the widely applicable general physics notion can be rigorously derived from first principles, rather than axiomatically proposed as an ansatz. Its logical association with causality is firmly rooted in the dynamical system that lies beneath. The principle of nil causality that reads, an event is not causal to another if the evolution of the latter is independent of the former, which transfer entropy analysis and Granger causality test fail to verify in many situations, turns out to be a proven theorem here. Established in this study are the information flows among the components of time-discrete mappings and time-continuous dynamical systems, both deterministic and stochastic. They have been obtained explicitly in closed form, and put to applications with the benchmark systems such as the Kaplan-Yorkemap, R¨ossler system, baker transformation, H´enon map, and stochastic potential flow. Besides unraveling the causal relations as expected from the respective systems, some of the applications show that the information flow structure underlying a complex trajectory pattern could be tractable. For linear systems, the resulting remarkably concise formula asserts analytically that causation implies correlation, while correlation does not imply causation, providing a mathematical basis for the long-standing philosophical debate over causation versus correlation.

Critical states are usually identified experimentally through power-law statistics or universal scaling functions. We show here that such features naturally emerge from networks in self-sustained irregular regimes away from criticality. Power-law statistics are also seen when the units are replaced by independent stochastic surrogates, and thus are not sufficient to establish criticality. We rather suggest that these are universal features of large-scale networks when considered macroscopically. These results put caution on the interpretation of scaling laws found in nature.

Molecular motors and cytoskeletal filaments mostly work collectively under opposing forces. This opposing force may be due to cargo carried by motors, or resistance coming from cell membrane pressing against the cytoskeletal filaments. Certain recent studies have shown that the collective maximum force (stall force) generated by multiple cytoskeletal filaments or molecular motors may not always be just a simple sum of stall force for individual filaments or motors. To understand this phenomena of excess or deficit collective force generation, we study a broad class of models of both cytoskeletal filaments and molecular motors. We argue that the stall force generated by a group of filaments or motors is additive, i.e., the stall force of N filaments(motors) is N times the stall force of one filament (motor), when the system is in equilibrium at stall. Consequently, we show that this additivity typically does not hold when the system departs from equilibrium at stall. We thus present a novel and unified understanding of existing models exhibiting such non- addivity, and generalize our arguments by developing new models that demonstrate this phenomena. We also propose a quantity similar to thermodynamic efficiency to provide a simple understanding of deviation from stall-force additivity for filament and motor collectives.

Fermi acceleration is the process of energy transfer from massive objects in slow motion to light objects that move fast. The model for such process is a time-dependent Hamiltonian system. As the parameters of the system change with time, the energy is no longer conserved, which makes the acceleration possible. One of the main problems is how to generate a sustained and robust energy growth. We show that the non-ergodicity of any chaotic Hamiltonian system must universally lead to the exponential growth of energy at a slow periodic variation of parameters. We build a model for this process in terms of a Geometric Brownian Motion with a positive drift, and relate it to the entropy increase.

Single component pseudo-potential lattice Boltzmann model has been widely applied in multiphase simulation due to its simplicity and stability. In many research, it has been claimed that this model can be stable for density ratios larger than 1000, however, the application of the model is still limited to small density ratios when the contact angle is considered. The reason is that the original contact angle adjustment method influences the stability of the model. Moreover, simulation results in present work show that, by applying the contact angle adjustment method, the density distribution near the wall is artificially changed, and the contact angle is dependent on the surface tension. Hence, it is very inconvenient to apply this method with a fixed contact angle, and the accuracy of the model cannot be guaranteed. To solve these problems, a contact angle adjustment method based on the geometry analysis is proposed and numerically compared with the original method. Simulation results show that, with the new contact angle adjustment method, the stability of the model is highly improved when the density ratio is relatively large, and it is independent of the surface tension.

Plastic events in amorphous solids can be much more than just "shear transformation zones" when the positional degrees of freedom are coupled non-trivially to other degrees of freedom. Here we consider magnetic amorphous solids where mechanical and magnetic degrees of freedom interact, leading to rather complex plastic events whose nature must be disentangled. In this paper we uncover the anatomy of the various contributions to some typical plastic events. These plastic events are seen as Barkhausen Noise or other "serrated noises". Using theoretical considerations we explain the observed statistics of the various contributions to the considered plastic events. The richness of contributions and their different characteristics imply that in general the statistics of these "serrated noises" cannot be universal, but rather highly dependent on the state of the system and on its microscopic interactions.

A mesoscopic model of amorphous plasticity is discussed in the wider context of depinning models. After embedding in a d + 1 dimensional space, where the accumulated plastic strain lives along the additional dimension, the gradual plastic deformation of amorphous media can be regarded as the motion of an elastic manifold in a disordered landscape. While the associated depinning transition leads to scaling properties, the quadrupolar Eshelby interactions at play induce specific additional features like shear-banding and weak ergodicity breakdown. The latters are shown to be controlled by the existence of soft modes of the quadrupolar interaction, the consequence of which is discussed in the context of depinning.

A method for analytic continuation of imaginary-time correlation functions (here obtained in quantum Monte Carlo simulations) to real-frequency spectral functions is proposed. Stochastically sampling a spectrum parametrized by a large number of delta-functions, treated as a statistical-mechanics problem, it avoids distortions caused by (as demonstrated here) configurational entropy in previous sampling methods. The key development is the suppression of entropy by constraining the spectral weight to within identifiable optimal bounds and imposing a set number of peaks. As a test case, the dynamic structure factor of the S=1/2 Heisenberg chain is computed. Very good agreement is found with Bethe Ansatz results in the ground state (including a sharp edge) and with exact diagonalization of small systems at elevated temperatures.

Nonlinear localized magnetic excitations in one dimensional magnonic crystal is investigated under periodic magntic field. The governing Landau-Lifshitz equation is transformed into variable coefficient nonlinear Schrodinger equation(VCNLS) using sterographic projection. The VCNLS equation is in general nonintegrable, by using painleve analysis necessary conditions for the VCNLS equation to pass Weiss-Tabor-Carnevale (WTC) Painleve test are obtained. A sufficient integrability condition is obtained by further exploring a transformation, which can map the VCNLS equation into the well-known standard nonlinear Schrodinger equation. The transformation built a systematic connection between the solution of the standard nonlinear Schrodinger equation and VC-NLS equation. The results shows the excitation of magnetization in the form of soliton has spatialperiod exists on the background of spin Bloch waves. Such solution exisits only certain constrain conditions on the coefficient of the VCNLS equation are satisfied. The analytical results suggest a way to control the dynamics of magnetization in the form of solitons by an appropriate spatial modulation of the nonlinearity coefficient in the governing VCNLS equation which is determined by the ferromagnetic materials which forms the magnonic crystal.

Time reversal mirrors have been widely used to achieve wave focusing in acoustics and electromagnetics. A typical time reversal experiment requires that a transmitter be initially present at the target focusing point, which limits the application of this technique. In this letter, we propose a method to focus waves at an arbitary location inside a complex enclosure using a numerically calculated wave signal. We use a semi-classical ray algorithm to calculate the signal that would be received at a transceiver port resulting from the injection of a short pulse at the desired target location. The quaility of the reconstruction is quantified in three different ways and the values of these metrics can be predicted by the statistics of the scattering-parameter $|S_{21}|^2$ between the transceiver and target points in the enclosure. We experimentally demonstrate the method using a flat microwave billiard and quantify the reconstruction quality as a function of enclosure loss, port coupling and other considerations.

A novel mechanism for the transport of microscale particles in viscous fluids is demonstrated. The mechanism exploits the trapping of such particles by rotational streaming cells established in the vicinity of an oscillating cylinder, recently analyzed in previous work. The present work explores a strategy of transporting particles between the trapping points established by multiple cylinders undergoing oscillations in sequential intervals. It is demonstrated that, by controlling the sequence of oscillation intervals, an inertial particle is effectively and predictably transported between the stable trapping points. Arrays of cylinders in various arrangements are investigated, revealing a quite general technique for constructing arbitrary particle trajectories. The timescales for transport are also discussed.

Recently, diverse phase transition (PT) types have been obtained in multiplex networks, such as discontinuous, continuous, and mixed-order PTs. However, they emerge from individual systems, and there is no theoretical understanding of such PTs in a single framework. Here, we study a spin model called the Ashkin-Teller (AT) model in a mono-layer scale-free network; this can be regarded as a model of two species of Ising spin placed on each layer of a double-layer network. The four-spin interaction in the AT model represents the inter-layer interaction in the multiplex network. Diverse PTs emerge depending on the inter-layer coupling strength and network structure. Especially, we find that mixed-order PTs occur at the critical end points. The origin of such behavior is explained in the framework of Landau-Ginzburg theory.

We investigate scaling of work output and efficiency of a photonic Carnot engine with the number of quantum coherent resources. Specifically, we consider a generalization of the "phaseonium fuel" for the photonic Carnot engine, which was first introduced as a three-level atom with two lower states in a quantum coherent superposition by [M. O. Scully, M. Suhail Zubairy, G. S. Agarwal, and H. Walther, Science {\bf 299}, 862 (2003)], to the case of $N+1$ level atoms with $N$ coherent lower levels. Deriving a multilevel mesoscopic master equation for the system, we evaluate the harvested work by the engine, and its efficiency. We find that efficiency and extracted work scale quadratically with the number of quantum coherent levels. Quantum coherence boost to the specific energy (work output per unit mass of the resource) is a profound fundamental difference of quantum fuel from classical resources. Besides, we examine the dependence of cavity loss on the number of atomic levels and find that multilevel phaseonium fuel can be utilized to beat the decoherence due to cavity loss. Our results bring the photonic Carnot engines much closer to the capabilities of current resonator technologies.

Using numerical simulations we examine colloids with a long-range Coulomb interaction confined in a two-dimensional trough potential undergoing dynamical compression. As the depth of the confining well is increased, the colloids move via elastic distortions interspersed with intermittent bursts or avalanches of plastic motion. In these avalanches, the colloids rearrange to minimize their colloid-colloid repulsive interaction energy by adopting an average lattice constant that is isotropic despite the anisotropic nature of the compression. The avalanches take the form of shear banding events that decrease or increase the structural order of the system. At larger compressions, the avalanches are associated with a reduction of the number of rows of colloids that fit within the confining potential, and between avalanches the colloids can exhibit partially crystalline or even smectic ordering. The colloid velocity distributions during the avalanches have a non-Gaussian form with power law tails and exponents that are consistent with those found for the velocity distributions of gliding dislocations. We observe similar behavior when we subsequently decompress the system, and find a partially hysteretic response reflecting the irreversibility of the plastic events.

Small-scale heat exchanges have recently been modeled with resource theories intended to extend thermodynamics to the nanoscale and quantum regimes. We generalize these theories to exchanges of quantities other than heat, to baths other than heat baths, and to free energies other than the Helmholtz free energy. These generalizations are illustrated with "grand-potential" theories that model movements of heat and particles. Free operations include unitaries that conserve energy and particle number. From this conservation law and from resource-theory principles, the grand-canonical form of the free states is derived. States are shown to form a quasiorder characterized by free operations, d-majorization, the hypothesis-testing entropy, and rescaled Lorenz curves. We calculate the work distillable from, and we bound the work cost of creating, a state. These work quantities can differ but converge to the grand potential in the thermodynamic limit. Extending thermodynamic resource theories beyond heat baths, we open diverse realistic systems to modeling with one-shot statistical mechanics. Prospective applications such as electrochemical batteries are hoped to bridge one-shot theory to experiments.

We study the mean field dynamics of self-trapping in Bose-Einstein condensates loaded in deep optical lattices with Gaussian initial conditions. We calculate a detailed dynamical phase diagram accurately describing the different dynamical regimes (such as diffusion and self-trapping) that markedly differs from earlier predictions based on variational dynamics. The phase diagram exhibits a very complex structure which could readily be tested in current experiments. We derive an explicit theoretical estimate for the transition to self-trapping in excellent agreement with our numerical findings.

We report analytical and numerical modelling of active elastic networks, motivated by experiments on crosslinked actin networks contracted by myosin motors. Within a broad range of parameters, the motor-driven collapse of active elastic networks leads to a critical state. We show that this state is qualitatively different from that of the random percolation model. Intriguingly, it possesses both euclidean and scale-free structure with Fisher exponent smaller than $2$. Remarkably, an indistinguishable Fisher exponent and the same euclidean structure is obtained at the critical point of the random percolation model after absorbing all enclaves into their surrounding clusters. We propose that in the experiment the enclaves are absorbed due to steric interactions of network elements. We model the network collapse, taking into account the steric interactions. The model shows how the system robustly drives itself towards the critical point of the random percolation model with absorbed enclaves, in agreement with the experiment.

A general lattice Boltzmann (LB) model is proposed for solving nonlinear partial differential equations with the form $\partial_t \phi+\sum_{k=1}^{m} \alpha_k \partial_x^k \Pi_k (\phi)=0$, where $\alpha_k$ are constant coefficients, and $\Pi_k (\phi)$ are the known differential functions of $\phi$, $1\leq k\leq m \leq 6$. The model can be applied to the common nonlinear evolutionary equations, such as (m)KdV equation, KdV-Burgers equation, K($m,n$) equation, Kuramoto-Sivashinsky equation, and Kawahara equation, etc. Unlike the existing LB models, the correct constraints on moments of equilibrium distribution function in the proposed model are given by choosing suitable \emph{auxiliary-moments}, and how to exactly recover the macroscopic equations through Chapman-Enskog expansion is discussed in this paper. Detailed simulations of these equations are performed, and it is found that the numerical results agree well with the analytical solutions and the numerical solutions reported in previous studies. Comment: 18 pages, 4 figures

We present a characterization of short-term stability of random Boolean networks under \emph{arbitrary} distributions of transfer functions. Given any distribution of transfer functions for a random Boolean network, we present a formula that decides whether short-term chaos (damage spreading) will happen. We provide a formal proof for this formula, and empirically show that its predictions are accurate. Previous work only works for special cases of balanced families. It has been observed that these characterizations fail for unbalanced families, yet such families are widespread in real biological networks.

Parameterization of reaction rates for thermal desorption are often analyzed using the Arrhenius equation. Data analysis procedures typically impose the empirical constraint of compensation, such that the different parameters in the equation balance each other out thereby leading to an implicitly assumed constant reaction rate for a wide range of thermally activated processes. However, the compensation effect has not been generally demonstrated and its origins are not completely understood. Using kinetic Monte Carlo simulations on a model interface, we explore how site and adsorbate interactions influence surface coverage during a typical desorption process. We find that the traditional criterion for the existence of a compensation effect for interacting species breaks down and the time characterizing desorption increases with increasing interaction strength due to an increase in the effective activation energy. At the molecular-site level these changes are the result of enhanced site correlations with increasing adsorbate interaction strength suppressing the onset of desorption. Our results show that the parameters vary as a result of interactions, however they do not offset or compensate each other completely as predicted with traditional methods of analysis.