This paper introduces an error reduction ratio–causality (ERR-causality) test that can be used to detect and track causal relationships between two signals. In comparison to the traditional Granger method, one significant advantage of the new ERR-causality test is that it can effectively detect the time-varying direction of linear or nonlinear causality between two signals without fitting a complete model. Another important advantage is that the ERR-causality test can detect both the direction of interactions and estimate the relative time shift between the two signals. Numerical examples are provided to illustrate the effectiveness of the new method together with the determination of the causality between electroencephalograph signals from different cortical sites for patients during an epileptic seizure.

Time-delayed systems are known to exhibit symmetric square waves oscillating with a period close to twice the delay. Here, we show that strongly asymmetric square waves of a period close to one delay are possible. The plateau lengths can be tuned by changing a control parameter. The problem is investigated experimentally and numerically using a simple bandpass optoelectronic delay oscillator modeled by nonlinear delay integrodifferential equations. An asymptotic approximation of the square-wave periodic solution valid in the large delay limit allows an analytical description of its main properties (extrema and square pulse durations). A detailed numerical study of the bifurcation diagram indicates that the asymmetric square waves emerge from a Hopf bifurcation.

The formation of the spiral patterns in dielectric-barrier discharge is investigated through instantaneous pictures at successive driving half cycles taken by an intensified-charge coupled device (ICCD). The filaments discretely distributed in each instantaneous picture corresponding to one discharge pulse indicate that they are the basic unit of the spiral patterns. An individual filament can undergo two movement states within continuous discharges: pinning at the same locations and shifting along the arm with a small displacement (less than the filament radius), which results in the formation of smooth arms. The averaged correlation time between the instantaneous patterns is found to be about two driving half-cycles by the cross-correlation calculations.

We analyze the dynamics of a model of a nanobeam under compression. The model is a two-mode truncation of the Euler-Bernoulli beam equation subject to compressive stress applied at both ends. We consider parameter regimes where the first mode is unstable and the second mode can be either stable or unstable, and the remaining modes (neglected) are always stable. Material parameters used correspond to a silicon nanobeam. The two-mode model Hamiltonian is the sum of a (diagonal) kinetic energy term and a potential energy term. The form of the potential energy function suggests an analogy with isomerization reactions in chemistry, where “isomerization” here corresponds to a transition between two stable beam configurations. We therefore study the dynamics of the buckled beam using the conceptual framework established for the theory of isomerization reactions. When the second mode is stable the potential energy surface has an index one saddle, and when the second mode is unstable the potential energy surface has an index two saddle and two index one saddles. Symmetry of the system allows us to readily construct a phase space dividing surface between the two “isomers” (buckled states); we rigorously prove that, in a specific energy range, it is a normally hyperbolic invariant manifold. The energy range is sufficiently wide that we can treat the effects of the index one and index two saddles on the isomerization dynamics in a unified fashion. We have computed reactive fluxes, mean gap times, and reactant phase space volumes for three stress values at several different energies. In all cases the phase space volume swept out by isomerizing trajectories is considerably less than the reactant density of states, proving that the dynamics is highly nonergodic. The associated gap time distributions consist of one or more “pulses” of trajectories. Computation of the reactive flux correlation function shows no sign of a plateau region; rather, the flux exhibits oscillatory decay, indicating that, for the two-mode model in the physical regime considered, a rate constant for isomerization does not exist.

In our recent Letter [Phys. Rev. Lett. 107, 274101 (2011)], we demonstrated that slow random perturbations of a system parameter were responsible for the emergence of rogue waves in a fiber laser with coexisting attractors. In this paper we investigate how the probability of a particular state to appear in multistate intermittency can be controlled by low-pass noise filtering. We show that the probability of some states depends nonmonotonously on the noise amplitude and cutoff frequency. The conditions for the emergence of extreme pulses in a erbium-doped fiber laser are analyzed numerically and experimentally.

Recently, we systematically derived a system of two coupled conservation equations governing a thin liquid layer with a deformable surface composed of two completely miscible components [Phys. Fluids 22, 104102 (2010)]. One equation describes the location of the free surface and the second one the evolution of the mean concentration. This lubrication model was investigated previously in linearized form. The study is now extended to the fully nonlinear case of thin liquid films of a binary mixture (in one and two horizontal spatial dimensions) with and without heat transport. For an initially flat and motionless film heated from below, we analyze the component separation induced by the Soret effect. Nonlinear simulations show that the Soret effect can cause a multitude of interesting behaviors, such as oscillatory patterns and solitonlike structures (localized traveling drops or holes). A stronger component separation induced by stronger Soret effects favors faster-moving localized structures. For isothermal systems, we study the fusion and the mixing of two thin liquid films of different but perfectly miscible liquids. Marangoni-driven forces can cause delayed coalescence, ripple formation, and fingering patterns at the borderline between the two liquid layers. A systematic analysis for ripple pattern formation and finger instabilities at different diffusion constants shows that these phenomena appear more pronounced for lower diffusion in the system.

A polymer solution partially filling a rotating horizontal drum undergoes an elastically driven instability at low Reynolds numbers. This instability manifests itself through localized plumelike bursts, perturbing the free liquid surface. Here we present an expanded experimental account regarding the dynamics of individual plumes and the statistics pertaining to the complex collective interaction between plumes, which leads to plume coagulation. We also present a detailed description of an optical technique that enables the visualization and measurement of surface perturbations in coating flows within a rotating horizontal drum.

When a red blood cell (RBC) is subjected to an external flow, it is deformed by the hydrodynamic forces acting on its membrane. The resulting elastic tensions in the membrane play a key role in mechanotransduction and govern its rupture in the case of hemolysis. In this study, we analyze the motion and deformation of an RBC in a simple shear flow and the resulting elastic tensions on the membrane. The large deformation of the red blood cell is modelled by coupling a finite element method to solve the membrane mechanics and a boundary element method to solve the flows of the internal and external liquids. Depending on the capillary number Ca, ratio of the viscous to elastic forces, we observe three kinds of RBC motion: tumbling at low Ca, swinging at larger Ca, and breathing at the transitions. In the swinging regime, the region of the high principal tensions periodically oscillates, whereas that of the high isotropic tensions is almost unchanged. Due to the strain-hardening property of the membrane, the deformation is limited but the membrane tension increases monotonically with the capillary number. We have quantitatively compared our numerical results with former experimental results. It indicates that a membrane isotropic tension $\mathcal{O}({10}^{-6}$ N/m) is high enough for molecular release from RBCs and that the typical maximum membrane principal tension for haemolysis would be $\mathcal{O}({10}^{-4}$ N/m). These findings are useful to clarify not only the membrane rupture but also the mechanotransduction of RBCs.

For a continuous maximum-entropy distribution (obtained from an arbitrary number of simultaneous constraints), we derive a general relation connecting the Lagrange multipliers and the expectation values of certain particularly constructed functions of the states of the system. From this relation, an estimator for a given Lagrange multiplier can be constructed from derivatives of the corresponding constraining function. These estimators sometimes lead to the determination of the Lagrange multipliers by way of solving a linear system, and, in general, they provide another tool to widen the applicability of Jaynes's formalism. This general relation, especially well suited for computer simulation techniques, also provides some insight into the interpretation of the hypervirial relations known in statistical mechanics and the recently derived microcanonical dynamical temperature. We illustrate the usefulness of these new relations with several applications in statistics.

We investigate the chemical dissolution of porous media using a 2D network model in which the system is represented as a series of interconnected pipes with the diameter of each segment increasing in proportion to the local reactant consumption. Moreover, the topology of the network is allowed to change dynamically during the simulation: As the diameters of the eroding pores become comparable with the interpore distances, the pores are joined together, thus changing the interconnections within the network. With this model, we investigate different growth regimes in an evolving porous medium, identifying the mechanisms responsible for the emergence of specific patterns. We consider both the random and regular network and study the effect of the network geometry on the patterns. Finally, we consider practically important problem of finding an optimum flow rate that gives a maximum increase in permeability for a given amount of reactant.

The size of the population of random walkers required to obtain converged estimates in diffusion Monte Carlo (DMC) increases dramatically with system size. We illustrate this by comparing ground state energies of small clusters of parahydrogen (up to 48 molecules) computed by DMC and path integral ground state (PIGS) techniques. We contend that the bias associated with a finite population of walkers is the most likely cause of quantitative numerical discrepancies between PIGS and DMC energy estimates reported in the literature, for this few-body Bose system. We discuss the viability of DMC as a general-purpose ground state technique, and argue that PIGS, and even finite temperature methods, enjoy more favorable scaling, and are therefore a superior option for systems of large size.

We study a quantum thermal engine model for which the heat transfer law is determined by Einstein's theory of radiation. The working substance of the quantum engine is assumed to be a two-level quantum system of which the constituent particles obey Maxwell-Boltzmann (MB), Fermi-Dirac (FD), or Bose-Einstein (BE) distributions, respectively, at equilibrium. The thermal efficiency and its bounds at maximum power of these models are derived and discussed in the long and short thermal contact time limits. The similarity and difference between these models are discussed. We also compare the efficiency bounds of this quantum thermal engine to those of its classical counterpart.

The mechanism for electric-field-induced segregation of additives, containing a polar group, in a host liquid crystal is proposed. It is shown that the polarity of an applied dc electric field, or the frequency of an ac electric field, strongly influences the segregation of reactive monomers containing an ester group. An explanation of this result is offered based on the association of dissolved ions with polar groups of the reactive monomers. This association is considered to cause these types of additives to drift to the cell surface in the presence of an external electric field. The described mechanism can be applied to the segregation of a broad range of additives in a liquid-crystal host.

Optical second-harmonic generation (SHG) has been studied in a trimer smectic $C^{*}$ liquid crystal especially designed for nonlinear optical applications. The molecule has a long conjugated donor-acceptor unit that transversally links three parallel rod-shaped moieties. A strong SHG signal has been observed at a fundamental wavelength of 1369 nm even in the presence of the spontaneous helicoidal structure of the smectic $C^{*}$ phase. This unusual behavior has been interpreted as due to the existence of phase matching, in which the wave vector mismatch is compensated by the wave vector of the helix. This point has been confirmed by the study of the SHG intensity versus sample thickness and light polarization characteristics. The main coefficient of the second-order susceptibility tensor of the material has been estimated to be $d_{22}=28$ pm/V.

We discuss the conditions under which a population of anomalously diffusing individuals can be characterized by demographic fluctuations that are anomalously scaling themselves. Two examples are provided in the case of individuals migrating by Gaussian diffusion, and by a sequence of Lévy flights.

The Galton board is a classic example of the appearance of randomness and stochasticity. In the dynamical model of the Galton board, the macroscopic motion is governed by deterministic equations of motion, and predictability depends on uncertainty in the initial conditions and its evolution by the dynamics. In this sense the Galton board is similar to coin tossing. In this paper, we analyze a simple dynamical model which is inspired by the Galton board. Especially, we focus on the predictability, considering the relation between the uncertainty of initial states and the structure of basins of initial states that result in the same exit state. The model has basins with fractal basin structure, unlike the basins in coin tossing models which have only finite structure. Arbitrarily small uncertainty of initial conditions can cause unpredictability of final states if the initial conditions are chosen in fractal regions. In this sense, our model is in a different category from the coin tossing model. We examine the predictability of a small Galton board model from the viewpoint of the sensitivity and the statistical bias of final states. We show that it is possible to determine the radii of scatterers corresponding to a given predictability criterion, specified as a statistical bias, and a given uncertainty of initial conditions.

Time-resolved measurements of electron and ion temperatures using Thomson scattering have been combined with proton radiography data for comprehensive characterization of individual laser-produced plasma bubbles or the interaction of bubble pairs, where reconnection of azimuthal magnetic fields occurs. Measurements of ion and electron temperatures agree with lasnex simulations of single plasma bubbles, which include the physics of magnetic fields. There is negligible difference in temperatures between a single plasma bubble and the interaction region of bubble pairs, although the ion temperature may be slightly higher due to the collision of expanding plasmas. These results are consistent with reconnection in a $\beta \sim 8$ plasma, where the release of magnetic energy ($<$5$\%$ of the electron thermal energy) does not appreciably affect the hydrodynamics.

The emergent fluctuating hydrodynamics of the multiparticle collision dynamics (MPC) approach, a particle-based mesoscale simulation technique for fluid dynamics, is analyzed theoretically and numerically. We focus on the stochastic rotation dynamics implementation of the MPC method. The fluid is characterized by its longitudinal and transverse velocity correlation functions in Fourier space and velocity autocorrelation functions in real space. Particular attention is paid to the role of sound, which leads to piecewise negative correlation functions. Moreover, finite system-size effects are addressed with an emphasis on the role of sound. Analytical expressions are provided for the transverse and longitudinal velocity correlations, which are derived from the linearized Landau-Lifshitz Navier-Stokes equation adopted for an isothermal MPC fluid. The comparison of the analytical results with simulations shows excellent agreement above a minimal length scale. The simulations indicate a breakdown in hydrodynamics on length scales smaller than this minimal length. This demonstrates that we have an excellent analytical description and understanding of the MPC method and its limitations in terms of time and length scales.