Randomly distributed offset charges affect the nonlinear current-voltage property via the fluctuation of the threshold voltage above which the current flows in an array of a Coulomb blockade (CB). We analytically derive the distribution of the threshold voltage for a model of one-dimensional locally coupled CB arrays and propose a general relationship between conductance and distribution. In addition, we show that the distribution for a long array is equivalent to the distribution of the number of upward steps for aligned objects of different heights. The distribution satisfies a novel Fokker-Planck equation corresponding to active Brownian motion. The feature of the distribution is clarified by comparing it with the Wigner and Ornstein-Uhlenbeck processes. It is not restricted to the CB model but is instructive in statistical physics generally.

Recent advances in single-molecule experiments show that various complex systems display nonergodic behavior. In this paper, we show how to test ergodicity and ergodicity breaking in experimental data. Exploiting the so-called dynamical functional, we introduce a simple test which allows us to verify ergodic properties of a real-life process. The test can be applied to a large family of stationary infinitely divisible processes. We check the performance of the test for various simulated processes and apply it to experimental data describing the motion of mRNA molecules inside live Escherichia coli cells. We show that the data satisfy necessary conditions for mixing and ergodicity. The detailed analysis is presented in the supplementary material.

The continuous-time random walk (CTRW) formalism can be adapted to encompass stochastic processes with memory. In this paper we will show how the random combination of two different unbiased CTRWs can give rise to a process with clear drift, if one of them is a CTRW with memory. If one identifies the other one as noise, the effect can be thought of as a kind of stochastic resonance. The ultimate origin of this phenomenon is the same as that of the Parrondo paradox in game theory.

Disruption of the cellular membrane by the amyloidogenic peptide, islet amyloid polypeptide (IAPP), has been considered as one of the mechanisms of $\beta$-cell death during type 2 diabetes. The N-terminal region (residues 1–19) of the human version of IAPP is suggested to be primarily responsible for the membrane-disrupting effect of the full-length hIAPP peptide. However, the detailed assembly mode of hIAPP1–19 with membrane remains unclear. To gain insight into the interactions of hIAPP1–19 oligomer with the model membrane, we have employed coarse-grained molecular dynamics self-assembly simulations to study the aggregation of hIAPP1–19 fragments in the binary lipid made of zwitterionic dipalmitoylphosphatidylcholine (DPPC) and anionic dipalmitoylphosphatidylserine (DPPS) in the presence and absence of different levels of cholesterol content. The membrane-destabilizing effect of hIAPP1–19 is found to be modulated by the presence of cholesterol. In the absence of cholesterol, hIAPP1–19 aggregates prefer to locate inside the bilayer, forming pore-like assemblies. While in the presence of cholesterol molecules, the lipid bilayer becomes more ordered and stiff, and the hIAPP1–19 aggregates are dominantly positioned at the bilayer-water interface. The action of cholesterol may suggest a possible way to maintain the membrane integrity by small molecule interference.

We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.

The magnetohydrodynamic (MHD) equations in the presence of a guiding magnetic field are investigated by means of direct numerical simulations. The basis of the investigation consists of nine runs forced at the small scales. The results demonstrate that for a large enough uniform magnetic field the large scale flow behaves as a two-dimensional (2D) (non-MHD) fluid exhibiting an inverse cascade of energy in the direction perpendicular to the magnetic field, while the small scales behave like a three-dimensional (3D) MHD fluid cascading the energy forwards. The amplitude of the inverse cascade is sensitive to the magnetic field amplitude, the domain size, the forcing mechanism, and the forcing scale. All these dependences are demonstrated by the varying parameters of the simulations. Furthermore, in the case that the system is forced anisotropically in the small parallel scales an inverse cascade in the parallel direction is observed that is feeding the 2D modes $k_{\parallel }=0$.

In this paper, we report on persistence results of reactive-wetting advancing interfaces performed with mercury on silver at room temperature. Earlier kinetic roughening studies of reactive-wetting systems at room temperature as well as at high temperatures revealed some limited information on the spatiotemporal behavior of these systems. However, by calculating the persistence exponent, we were able to identify two distinct kinetic time regimes in this process. In the first one, while the interface is moving but its width is not yet growing, the persistence exponent is $\theta =0.55\pm 0.05$, which is typical for a random, noisy behavior. In the second regime, there is an effective growth of the interface width with a growth exponent $\beta =0.67\pm 0.06$ followed by saturation, according to the Family-Vicsek description of interface growth. The persistence exponent in this regime is $\theta =0.37\pm 0.05$, which indicates that the relation $\theta =1-\beta$ seems to hold even for this nonlinear experimental system.

The exclusive queueing process (EQP) has recently been introduced as a model for the dynamics of queues that takes into account the spatial structure of the queue. It can be interpreted as a totally asymmetric exclusion process of varying length. Here we investigate the case of deterministic bulk hopping $p=1$ that turns out to be one of the rare cases where exact nontrivial results for the dynamical properties can be obtained. Using a time-dependent matrix product form we calculate several dynamical properties, e.g., the density profile of the system.

Generalized superstatistics, i.e., a “statistics of superstatistics,” is proposed. A generalized superstatistical system comprises a set of superstatistical subsystems and represents a generalized hyperensemble. There exists a random control parameter that determines both the density of energy states and the distribution of the intensive parameter for each superstatistical subsystem, thereby forming the third, upper level of dynamics. Generalized superstatistics can be used for nonstationary nonequilibrium systems. The system in which a supercritical multitype age-dependent branching process takes place is an example of a nonstationary generalized superstatistical system. The theory is applied to pair production in a neutron star magnetosphere.

The roughening phase diagram of the $d=3$ Ising model with uniaxially anisotropic interactions is calculated for the entire range of anisotropy, from decoupled planes to the isotropic model to the solid-on-solid model, using hard-spin mean-field theory. The phase diagram contains the line of ordering phase transitions and, at lower temperatures, the line of roughening phase transitions, where the interface between ordered domains roughens. Upon increasing the anisotropy, roughening transition temperatures settle after the isotropic case, whereas the ordering transition temperature increases to infinity. The calculation is repeated for the $d=2$ Ising model for the full range of anisotropy, yielding no roughening transition.

We formulate an approximate thermodynamic theory of the phase transition in driven lattice gases with attractive nearest-neighbor interactions. We construct the van der Waals equation of state for a driven system where a nonequilibrium chemical potential can be expressed as a function of density and driving field. A Maxwell's construction leads to the phase transition from a homogeneous fluid phase to the coexisting phases of gas and liquid.

Transport properties of a single-mode waveguide with rough boundary are studied by discrimination between two mechanisms of surface scattering, the amplitude and square-gradient ones. Although these mechanisms are generically mixed, we show that for some profiles they can separately operate within nonoverlapping intervals of wave numbers of scattering waves. This effect may be important in realistic situations due to inevitable long-range correlations in scattering profiles.

We study the critical behavior of the Ising model in the case of quenched disorder constrained by fractality on random Sierpinski fractals with a Hausdorff dimension $d_f\simeq 1.8928$. This is a first attempt to study a situation between the borderline cases of deterministic self-similarity and quenched randomness. Intensive Monte Carlo simulations were carried out. Scaling corrections are much weaker than in the deterministic cases, so that our results enable us to ensure that finite-size scaling holds, and that the critical behavior is described by a new universality class. The hyperscaling relation is compatible with an effective dimension equal to the Hausdorff one; moreover the two eigenvalues exponents of the renormalization flows are shown to be different from the ones calculated from $\epsilon$ expansions, and from the ones obtained for fourfold symmetric deterministic fractals. Although the space dimensionality is not integer, lack of self-averaging properties exhibits some features very close to the ones of a random fixed point associated with a relevant disorder.

We introduce and study the block voter model with noise on two-dimensional square lattices using Monte Carlo simulations and finite-size scaling techniques. The model is defined by an outflow dynamics where a central set of $N_{\mathrm{PCS}}$ spins, here denoted by persuasive cluster spins (PCS), tries to influence the opinion of their neighboring counterparts. We consider the collective behavior of the entire system with varying PCS size. When $N_{\mathrm{PCS}}>2$, the system exhibits an order-disorder phase transition at a critical noise parameter $q_c$ which is a monotonically increasing function of the size of the persuasive cluster. We conclude that a larger PCS has more power of persuasion, when compared to a smaller one. It also seems that the resulting critical behavior is Ising-like independent of the range of interaction.

We study the nonequilibrium thermodynamics of a single particle with two available energy levels, in contact with a classical (Maxwell-Boltzmann) or quantum (Bose-Einstein) heat bath. The particle can undergo transitions between the levels via thermal activation or deactivation. The energy levels are alternately raised at a given rate regardless of occupation by the particle, maintaining a fixed energy gap equal to $\varepsilon$ between them. We explicitly calculate the work, heat, and entropy production rates. The efficiency in both the classical and the quantum case goes to a limit between 100 and $50\%$ that depends on the relative rates of particle transitions and level elevation. In the classical problem we explicitly find the large deviation functions for heat, work, and internal energy.

We use a simple fragmentation model to describe the statistical behavior of the Voronoi cell patterns generated by a homogeneous and isotropic set of points in 1D and in 2D. In particular, we are interested in the distribution of sizes of these Voronoi cells. Our model is completely defined by two probability distributions in 1D and again in 2D, the probability to add a new point inside an existing cell and the probability that this new point is at a particular position relative to the preexisting point inside this cell. In 1D the first distribution depends on a single parameter while the second distribution is defined through a fragmentation kernel; in 2D both distributions depend on a single parameter. The fragmentation kernel and the control parameters are closely related to the physical properties of the specific system under study. We use our model to describe the Voronoi cell patterns of several systems. Specifically, we study the island nucleation with irreversible attachment, the 1D car-parking problem, the formation of second-level administrative divisions, and the pattern formed by the Paris Métro stations.

We numerically investigated various dynamical behaviors of a vibrated granular gas in microgravity. Using the parameters of an earlier Mini-Texus 5 experiment, three-dimensional simulations, based on molecular dynamics, efficiently reproduce experimental results. Using Kolmogorov-Smirnov tests, four dynamical regimes have been distinguished: gaseous state, partial clustering, complete clustering, and bouncing aggregates. Different grain radii and densities have been considered in order to describe a complete $(r,\eta )$-phase diagram. The latter exhibits rich features such as phase transitions and triple points. Our work emphasizes the complexity of diluted granular systems and opens fundamental perspectives.

Gas-liquid phase coexistence curves of the polarizable Stockmayer fluid in external electric fields are computed using molecular dynamics computer simulation. We study in particular the critical-point shift dependence on polarizability and external electric field distinguishing the cases of fixed charge density and fixed potential. The results are compared to a previously developed mean-field theory for the polarizable Stockmayer fluid in an external field. We also investigate the behavior of the isochoric heat capacity near gas-liquid criticality via finite-size scaling depending on polarizability and external field.

Simulation of the Rouse model in flow underlies a great variety of numerical investigations of polymer dynamics, in both entangled melts and solutions and in dilute solution. Typically a simple explicit stochastic Euler method is used to evolve the Rouse model. Here we compare this approach to an operator splitting method, which splits the evolution operator into stochastic linear and deterministic nonlinear parts and takes advantage of an analytical solution for the linear Rouse model in terms of the noise history. We show that this splitting method has second-order weak convergence, whereas the Euler method has only first-order weak convergence. Furthermore, the splitting method is unconditionally stable, in contrast to the limited stability range of the Euler method. Similar splitting methods are applicable to a broad class of problems in stochastic dynamics in which noise competes with ordering and flow to determine steady-state order parameter structures.

We perform equilibrium computer simulations of a two-dimensional pinned flexible polymer exposed to a quenched disorder potential consisting of hard disks. We are especially interested in the high-density regime of the disorder, where subtle structures such as cavities and channels play a central role. We apply an off-lattice growth algorithm proposed by Garel and Orland [J. Phys. A 23, L621 (1990)], where a distribution of polymers is constructed in parallel by growing each of them monomer by monomer. In addition we use a multicanonical Monte Carlo method in order to cross-check the results of the growth algorithm. We measure the end-to-end distribution and the tangent-tangent correlations. We also investigate the scaling behavior of the mean square end-to-end distance in dependence on the monomer number. While the influence of the potential in the low-density case is merely marginal, it dominates the configurational properties of the polymer for high densities.