Avalanches and Extreme Value Statistics of a Mesoscale Moving Contact Line.

We report direct atomic force microscopy measurements of pinning-depinning dynamics of a circular moving contact line (CL) over the rough surface of a micron-sized vertical hanging glass fiber, which intersects a liquid-air interface. The measured capillary force acting on the CL exhibits sawtoothlike fluctuations, with a linear accumulation of force of slope k (stick) followed by a sharp release of force δf, which is proportional to the CL slip length. From a thorough analysis of a large volume of the stick-slip events, we find that the local maximal force F_{c} needed for CL depinning follows the extreme value statistics and the measured δf follows the avalanche dynamics with a power law distribution in good agreement with the Alessandro-Beatrice-Bertotti-Montorsi (ABBM) model. The experiment provides an accurate statistical description of the CL dynamics at mesoscale, which has important implications to a common class of problems involving stick-slip motion in a random defect or roughness landscape.

Symmetry-breaking-induced rare fluctuations in a time-delay dynamic system.

Inspired by the experimental and numerical findings, we study the dynamic instabilities of two coupled nonlinear delay differential equations that are used to describe the coherent oscillations between the top and bottom boundary layers in turbulent Rayleigh-Bénard convection. By introducing two sensitivity parameters for the instabilities of the top and bottom boundary layers, we find three different types of solutions, namely in-phase single-period oscillations, multi-period oscillations and chaos. The chaos solution contains rare but large amplitude fluctuations. The statistical properties of these fluctuations are consistent with those observed in the experiment for the massive eruption of thermal plumes, which causes random reversals of the large-scale circulation in turbulent Rayleigh-Bénard convection. Our study thus provides new insights into the origin of rare massive eruptions and sudden changes of large-scale flow pattern that are often observed in convection systems of geophysical and astrophysical scales.

Colloidal diffusion over a quenched two-dimensional random potential.

A two-layer colloidal system is developed for the study of diffusion over a quenched two-dimensional random potential. A mixture of bidisperse silica spheres is used to form a randomly packed colloidal monolayer on the bottom substrate. The corrugated surface of the bottom colloidal monolayer provides a gravitational potential field for the dilute diffusing particles in the top layer. The population probability histogram P(x,y) of the diffusing particles is obtained to fully characterize the random potential landscape U(x,y) via the Boltzmann distribution. The dynamical properties of the top diffusing particles, such as their mean square displacement (MSD), histogram of the escape time, and long-time self-diffusion coefficient, are simultaneously measured from the particle trajectories. A quantitative relationship between the long-time diffusion coefficient and the random potential is obtained, which is in good agreement with the theoretical prediction. The measured MSD reveals a wide region of subdiffusion resulting from the structural disorders. The crossover from subdiffusion to normal diffusion is explained by the Lorentz model for tracer diffusion through a heterogeneous space filled with a set of randomly distributed obstacles.

Colloidal diffusion over a quasicrystalline-patterned surface.

We report a systematic study of colloidal diffusion over a substrate with quasicrystalline-patterned holes. Silica spheres of diameter comparable to the hole diameter diffuse over the patterned substrate and experience a gravitational potential U(x, y). Using optical microscopy, we track the particle trajectories and find two distinct states: a trapped state when the particles are inside the holes and a free-diffusion state when they are on the flat surface outside the holes. The potential U(x, y) and dynamic properties of the diffusing particle, such as its mean dwell time, mean square displacement, and long-time diffusion coefficient DL, are measured simultaneously. The measured DL is in good agreement with the prediction of two theoretical models proposed for diffusion over a quasicrystal lattice. The experiment demonstrates the applications of this newly constructed potential landscape.

Regulatory effects on the population dynamics and wave propagation in a cell lineage model.

We consider the interplay of cell proliferation, cell differentiation (and de-differentiation), cell movement, and the effect of feedback regulations on the population and propagation dynamics of different cell types in a cell lineage model. Cells are assumed to secrete and respond to negative feedback molecules which act as a control on the cell lineage. The cell densities are described by coupled reaction-diffusion partial differential equations, and the propagating wave front solutions in one dimension are investigated analytically and by numerical solutions. In particular, wavefront propagation speeds are obtained analytically and verified by numerical solutions of the equations. The emphasis is on the effects of the feedback regulations on different stages in the cell lineage. It is found that when the progenitor cell is negatively regulated, the populations of the cell lineage are strongly down-regulated with the steady growth rate of the progenitor cell being driven to zero beyond a critical regulatory strength. An analytic expression for the critical regulation strength in terms of the model parameters is derived and verified by numerical solutions. On the other hand, if the inhibition is acting on the differentiated cells, the change in the population dynamics and wave propagation speed is small. In addition, it is found that only the propagating speed of the progenitor cells is affected by the regulation when the diffusion of the differentiated cells is large. In the presence of de-differentiation, the effect on down-regulating the progenitor population is weakened and there is no effect on the propagation speed due to regulation, suggesting that the effect of regulatory control is diminished by de-differentiation pathways.

Colloidal transport and diffusion over a tilted periodic potential: dynamics of individual particles.

A tilted two-layer colloidal system is constructed for the study of force-assisted barrier-crossing dynamics over a periodic potential. The periodic potential is provided by the bottom layer colloidal spheres forming a fixed crystalline pattern on a glass substrate. The corrugated surface of the bottom colloidal crystal provides a gravitational potential field for the top layer diffusing particles. By tilting the sample at an angle θ with respect to the vertical (gravity) direction, a tangential component of the gravitational force F is applied to the diffusing particles. The measured mean drift velocity v(F, Eb) and diffusion coefficient D(F, Eb) of the particles as a function of F and energy barrier height Eb agree well with the exact results of the one-dimensional drift velocity (R. L. Stratonovich, Radiotekh. Elektron, 1958, 3, 497) and diffusion coefficient (P. Reimann, et al., Phys. Rev. Lett., 2001, 87, 010602 and P. Reimann, et al., Phys. Rev. E, 2002, 65, 031104). Based on these exact results, we show analytically and verify experimentally that there exists a scaling region, in which v(F, Eb) and D(F, Eb) both scale as ν'(F)exp[-E(F)/kBT], where the Arrhenius pre-factor ν'(F) and effective barrier height E(F) are both modified by F. The experiment demonstrates the applications of this model system in evaluating different scaling forms of ν'(F) and E(F) and their accuracy, in order to extract useful information about the external potential, such as the intrinsic barrier height Eb.

Intrinsic fluctuations of cell migration under different cellular densities.

The motility of the Dictyostelium discoideum (DD) cell is studied by video microscopy when the cells are plated on top of an agar plate at different densities, n. It is found that the fluctuating kinetics of the cells can be divided into two normal directions: the cell's forward-moving direction and its normal direction. Along the forward-moving direction, the slope of the amplitude of fluctuation vs. velocity (R||(v)) increases with n, while along the normal direction the slope of R⊥ is independent of n. Both R|| and R⊥ are functions of the cell speed v. The observed linearity in R⊥(v) indicated that the amplitude of orientational fluctuation (κ) of DD cells is a constant independent of v. The independence of the slope of R⊥(v) on n indicated that κ is also not affected by cellular interactions. The independence of κ on both v and n suggests that orientational fluctuation originates from the intrinsic property of motion fluctuations in DD.

Coexistence of distinct nonuniform nonequilibrium steady states in Ehrenfest multiurn model on a ring.

The recently proposed Ehrenfest M-urn model with interactions on a ring is considered as a paradigm model which can exhibit a variety of distinct nonequilibrium steady states. Unlike the previous three-urn model on a ring which consists of a uniform steady state and a nonuniform nonequilibrium steady state, it is found that for even M≥4, an additional nonequilibrium steady state can coexist with the original ones. Detailed analysis reveals that this additional nonequilibrium steady state emerged via a pitchfork bifurcation which cannot occur if M is odd. Properties of this nonequilibrium steady state, such as stability, and steady-state flux are derived analytically for the four-urn case. The full phase diagram with the phase boundaries is also derived explicitly. The associated thermodynamic stability is also analyzed, confirming its stability. These theoretical results are also explicitly verified by direct Monte Carlo simulations for the three-urn and four-urn ring models.

Gambling demon and stopping-time fluctuation relation of a Brownian particle under a time-dependent trapping potential.

A gambling demon is an external agent that can terminate a time-dependent driving protocol when a certain observable of the system exceeds a prescribed threshold. The gambling demon is examined in detail both theoretically and experimentally in a Brownian particle system under a compressing potential trap. Insight for choosing an appropriate work threshold for stopping is discussed. The energetics and the distributions of the stopping positions and stopping times are measured in simulations to gain further understanding of the process. Furthermore, the nonstationary and far-from-equilibrium stochastic process in the action of the gambling demon allows us to examine in detail some fundamental issues in stochastic thermodynamics, such as irreversibility and stopping-time fluctuation relation. Paradoxical violation of the stopping-time fluctuation relation can be reconciled in terms of the entropy production associated with fast hidden internal degrees of freedom. All the simulation or theoretical results are confirmed experimentally.

Model on cell movement, growth, differentiation and de-differentiation: reaction-diffusion equation and wave propagation.

We construct a model for cell proliferation with differentiation into different cell types, allowing backward de-differentiation and cell movement. With different cell types labeled by state variables, the model can be formulated in terms of the associated transition probabilities between various states. The cell population densities can be described by coupled reaction-diffusion partial differential equations, allowing steady wavefront propagation solutions. The wavefront profile is calculated analytically for the simple pure growth case (2-states), and analytic expressions for the steady wavefront propagating speeds and population growth rates are obtained for the simpler cases of 2-, 3- and 4-states systems. These analytic results are verified by direct numerical solutions of the reaction-diffusion PDEs. Furthermore, in the absence of de-differentiation, it is found that, as the mobility and/or self-proliferation rate of the down-lineage descendant cells become sufficiently large, the propagation dynamics can switch from a steady propagating wavefront to the interesting situation of propagation of a faster wavefront with a slower waveback. For the case of a non-vanishing de-differentiation probability, the cell growth rate and wavefront propagation speed are both enhanced, and the wavefront speeds can be obtained analytically and confirmed by numerical solution of the reaction-diffusion equations.

Theory of nonequilibrium asymptotic state thermodynamics: Interacting Ehrenfest urn ring as an example.

A generalized class of the nonequilibrium state, called the nonequilibrium asymptotic state (NEAS), is proposed. The NEAS is constructed within the framework of Fokker-Planck equations in thermodynamic limit. Besides the usual equilibrium state and nonequilibrium steady state (NESS), the class of NEAS could also cover the nonequilibrium periodic state (NEPS) in which its dynamics shows periodicity, the nonequilibrium quasiperiodic state (NEQPS), and nonequilibrium chaotic state (NECS) in which its dynamics becomes chaotic. Based on the theory of NEAS thermodynamics, the corresponding thermodynamics of different NEASs could also be determined. Finally the interacting Ehrenfest urn ring model is used as an example to illustrate how different kinds of NEAS (equilibrium state, uniform NESS, nonuniform NESS, NEPS) in the three-urn case are identified in our framework. In particular, the thermodynamics of NEPS and its phase transitions to other types of NEAS are studied.

Diverse phase transitions in optimized directed network models with distinct inward and outward node weights.

We consider growing directed network models that aim at minimizing the weighted connection expenses while at the same time favoring other important network properties such as weighted local node degrees. We employed statistical mechanics methods to study the growth of directed networks under the principle of optimizing some objective function. By mapping the system to an Ising spin model, analytic results are derived for two such models, exhibiting diverse and interesting phase transition behaviors for general edge weight, inward and outward node weight distributions. In addition, the unexplored cases of negative node weights are also investigated. Analytic results for the phase diagrams are derived showing even richer phase transition behavior, such as first-order transition due to symmetry, second-order transitions with possible reentrance, and hybrid phase transitions. We further extend previously developed zero-temperature simulation algorithm for undirected networks to the present directed case and for negative node weights, and we can obtain the minimal cost connection configuration efficiently. All the theoretical results are explicitly verified by simulations. Possible applications and implications are also discussed.

Statistical laws of stick-slip friction at mesoscale.

Friction between two rough solid surfaces often involves local stick-slip events occurring at different locations of the contact interface. If the apparent contact area is large, multiple local slips may take place simultaneously and the total frictional force is a sum of the pinning forces imposed by many asperities on the interface. Here, we report a systematic study of stick-slip friction over a mesoscale contact area using a hanging-beam lateral atomic-force-microscope, which is capable of resolving frictional force fluctuations generated by individual slip events and measuring their statistical properties at the single-slip resolution. The measured probability density functions (PDFs) of the slip length δxs, the maximal force Fc needed to trigger the local slips, and the local force gradient [Formula: see text] of the asperity-induced pinning force field provide a comprehensive statistical description of stick-slip friction that is often associated with the avalanche dynamics at a critical state. In particular, the measured PDF of δxs obeys a power law distribution and the power-law exponent is explained by a new theoretical model for the under-damped spring-block motion under a Brownian-correlated pinning force field. This model provides a long-sought physical mechanism for the avalanche dynamics in stick-slip friction at mesoscale.

Activity-assisted barrier crossing of self-propelled colloids over parallel microgrooves.

We report a systematic study of the dynamics of self-propelled particles (SPPs) over a one-dimensional periodic potential landscape U_{0}(x), which is fabricated on a microgroove-patterned polydimethylsiloxane (PDMS) substrate. From the measured nonequilibrium probability density function P(x;F_{0}) of the SPPs, we find that the escape dynamics of the slow rotating SPPs across the potential landscape can be described by an effective potential U_{eff}(x;F_{0}), once the self-propulsion force F_{0} is included into the potential under the fixed angle approximation. This work demonstrates that the parallel microgrooves provide a versatile platform for a quantitative understanding of the interplay among the self-propulsion force F_{0}, spatial confinement by U_{0}(x), and thermal noise, as well as its effects on activity-assisted escape dynamics and transport of the SPPs.

Efficient reconstruction of directed networks from noisy dynamics using stochastic force inference.

We consider coupled network dynamics under uncorrelated noises that fluctuate about the noise-free long-time asymptotic state. Our goal is to reconstruct the directed network only from the time-series data of the dynamics of the nodes. By using the stochastic force inference method with a simple natural choice of linear polynomial basis, we derive a reconstruction scheme of the connection weights and the noise strength of each node. Explicit simulations for directed and undirected random networks with various node dynamics are carried out to demonstrate the good accuracy and high efficiency of the reconstruction scheme. We further consider the case when only a subset of the network and its node dynamics can be observed, and it is demonstrated that the directed weighted connections among the observed nodes can be easily and faithfully reconstructed. In addition, we propose a scheme to infer the number of hidden nodes and their effects on each observed node. The accuracy of these results is illustrated by simulations.

Stochastic currents and efficiency in an autonomous heat engine.

We experimentally demonstrate that a Brownian gyrator of a colloidal particle confined in a two-dimensional harmonic potential with different effective temperatures on orthogonal axes can work as an autonomous heat engine capable of extracting work from the heat bath, generated by an optical feedback trap. The results confirm the theoretically predicted thermodynamic currents and validate the attainability of Carnot efficiency as well as the trade-off relation between power and efficiency. We further show that current fluctuations and the entropy production rate are time independent in the steady state and their product near the Carnot efficiency is close to the lower bound of the thermodynamic uncertainty relation.

Revealing directed effective connectivity of cortical neuronal networks from measurements.

In the study of biological networks, one of the major challenges is to understand the relationships between network structure and dynamics. In this paper, we model in vitro cortical neuronal cultures as stochastic dynamical systems and apply a method that reconstructs directed networks from dynamics [Ching and Tam, Phys. Rev. E 95, 010301(R) (2017)2470-004510.1103/PhysRevE.95.010301] to reveal directed effective connectivity, namely, the directed links and synaptic weights, of the neuronal cultures from voltage measurements recorded by a multielectrode array. The effective connectivity so obtained reproduces several features of cortical regions in rats and monkeys and has similar network properties as the synaptic network of the nematode Caenorhabditis elegans, whose entire nervous system has been mapped out. The distribution of the incoming degree is bimodal and the distributions of the average incoming and outgoing synaptic strength are non-Gaussian with long tails. The effective connectivity captures different information from the commonly studied functional connectivity, estimated using statistical correlation between spiking activities. The average synaptic strengths of excitatory incoming and outgoing links are found to increase with the spiking activity in the estimated effective connectivity but not in the functional connectivity estimated using the same sets of voltage measurements. These results thus demonstrate that the reconstructed effective connectivity can capture the general properties of synaptic connections and better reveal relationships between network structure and dynamics.

Frequency enhancement in coupled noisy excitable elements.

Oscillatory dynamics of coupled excitable FitzHugh-Nagumo elements in the presence of noise is investigated as a function of the coupling strength g. For two such coupled elements, their frequencies are enhanced and will synchronize at a frequency higher than the uncoupled frequencies of each element. As g increases, there is an unexpected peak in the frequency enhancement before reaching synchronization. The results can be understood with an analytic model based on the excitation across a potential barrier whose height is controlled by g. Simulation results of a coupled square lattice can quantitatively reproduce the unexpected peak in the variation of the beating rates observed in cultured cardiac cells experiments.

Effects of hidden nodes on noisy network dynamics.

We consider coupled network dynamics under uncorrelated noises, but only a subset of the network and their node dynamics can be observed. The effects of hidden nodes on the dynamics of the observed nodes can be viewed as having an extra effective noise acting on the observed nodes. These effective noises possess spatial and temporal correlations whose properties are related to the hidden connections. The spatial and temporal correlations of these effective noises are analyzed analytically and the results are verified by simulations on undirected and directed weighted random networks and small-world networks. Furthermore, by exploiting the network reconstruction relation for the observed network noisy dynamics, we propose a scheme to infer information of the effects of the hidden nodes such as the total number of hidden nodes and the weighted total hidden connections on each observed node. The accuracy of these results are demonstrated by explicit simulations.

Optimized two-dimensional networks with edge-crossing cost: Frustrated antiferromagnetic spin system.

We consider a quasi-two-dimensional network connection growth model that minimizes the wiring cost while maximizing the network connections, but at the same time edge crossings are penalized or forbidden. This model is mapped to a dilute antiferromagnetic Ising spin system with frustrations. We obtain analytic results for the order-parameter or mean degree of the optimized network using mean-field theories. The cost landscape is analyzed in detail showing complex structures due to frustration as the crossing penalty increases. For the case of strictly no edge crossing is allowed, the mean-field equations lead to a new algorithm that can effectively find the (near) optimal solution even for this strongly frustrated system. All these results are also verified by Monte Carlo simulations and numerical solution of the mean-field equations. Possible applications and relation to the planar triangulation problem is also discussed.