Reconstructing network connection topology and interaction strengths solely from measurement of the dynamics of the nodes is a challenging inverse problem of broad applicability in various areas of science and engineering. For a discrete-time step network under noises whose noise-free dynamics is stationary, we derive general analytic results relating the weighted connection matrix of the network to the correlation functions obtained from time-series measurements of the nodes for networks with one-dimensional intrinsic node dynamics. Information about the intrinsic node dynamics and the noise strengths acting on the nodes can also be obtained. Based on these results, we develop a scheme that can reconstruct the above information of the network using only the time-series measurements of node dynamics as input. Reconstruction formulas for higher-dimensional node dynamics are also derived and illustrated with a two-dimensional node dynamics network system. Furthermore, we extend our results and obtain a reconstruction scheme even for the cases when the noise-free dynamics is periodic. We demonstrate that our method can give accurate reconstruction results for weighted directed networks with linear or nonlinear node dynamics of various connection topologies, and with linear or nonlinear couplings.

While it is widely accepted that information is encoded in neurons via action potentials or spikes, it is far less understood what specific features of spiking contain encoded information. Experimental evidence has suggested that the timing of the first spike may be an energy-efficient coding mechanism that contains more neural information than subsequent spikes. Therefore, the biophysical features of neurons that underlie response latency are of considerable interest. Here we examine the effects of channel noise on the first spike latency of a Hodgkin-Huxley neuron receiving random input from many other neurons. Because the principal feature of a Hodgkin-Huxley neuron is the stochastic opening and closing of channels, the fluctuations in the number of open channels lead to fluctuations in the membrane voltage and modify the timing of the first spike. Our results show that when a neuron has a larger number of channels, (i) the occurrence of the first spike is delayed and (ii) the variation in the first spike timing is greater. We also show that the mean, median, and interquartile range of first spike latency can be accurately predicted from a simple linear regression by knowing only the number of channels in the neuron and the rate at which presynaptic neurons fire, but the standard deviation (i.e., neuronal jitter) cannot be predicted using only this information. We then compare our results to another commonly used stochastic Hodgkin-Huxley model and show that the more commonly used model overstates the first spike latency but can predict the standard deviation of first spike latencies accurately. We end by suggesting a more suitable definition for the neuronal jitter based upon our simulations and comparison of the two models.

We propose a surface model of spin dephasing in lung tissue that includes both susceptibility and diffusion effects to provide a closed-form solution of the Bloch-Torrey equation on the alveolar surface. The nonlocal susceptibility effects of the model are validated against numerical simulations of spin dephasing in a realistic lung tissue geometry acquired from synchotron-based $\mu \mathrm{CT}$ data sets of mouse lung tissue, and against simulations in the well-known Wigner-Seitz model geometry. The free induction decay is obtained in dependence on microscopic tissue parameters and agrees very well with in vivo lung measurements at 1.5 Tesla to allow a quantification of the local mean alveolar radius. Our results are therefore potentially relevant for the clinical diagnosis and therapy of pulmonary diseases.

Direct numerical simulations of homogeneous decaying turbulence with background rotation show the existence of a systematic and significant imbalance between the non-linear energy cascade to small scales and its dissipation. By starting the decay from a statistically stationary and weakly rotating turbulent state, where the dissipation and the energy flux are approximately equal, the data show a growing imbalance between the two until a maximum is reached when the dissipation is about twice the energy flux. This dichotomy of behaviors during decay is reminiscent of the nonequilibrium and the equilibrium regions previously reported for nonrotating turbulence [Valente and Vassilicos, Phys. Rev. Lett. 108, 214503 (2012)]. Note, however, that for decaying rotating turbulence the classical scaling of the dissipation rate $\epsilon \propto u^{\prime 3}/L$ (where $u^{\prime }$ and $L$ are the root mean square fluctuating velocity and the integral length scale, respectively) does not appear to hold during decay, which may be attributed to the effect of the background rotation on the energy cascade. On the other hand, the maximum energy flux holds the scaling ${\mathrm{\Pi }}_{\max }\propto u^{\prime 3}/L$ in the initial stage of the decay until the maximum imbalance is reached.

Time evolution of the fully resolved incompressible homogeneous turbulent shear flow in noninteger Fourier dimensions is numerically investigated. The Fourier dimension of the flow field is extended from the integer value 3 to the noninteger values by projecting the Navier-Stokes equation on the fractal set of the active Fourier modes with dimensions $2.7\le d\le 3.0$. The results of this study revealed that the dynamics of both large and small scale structures are nontrivially influenced by changing the Fourier dimension $d$. While both turbulent production and dissipation are significantly hampered as $d$ decreases, the evolution of their ratio is almost independent of the Fourier dimension. The mechanism of the energy distribution among different spatial directions is also impeded by decreasing $d$. Due to this deficient energy distribution, turbulent field shows a higher level of the large-scale anisotropy in lower Fourier dimensions. In addition, the persistence of the vortex stretching mechanism and the forward spectral energy transfer, which are three-dimensional turbulence characteristics, are examined at changing $d$, from the standard case $d=3.0$ to the strongly decimated flow field for $d=2.7$. As the Fourier dimension decreases, these forward energy transfer mechanisms are strongly suppressed, which in turn reduces both the small-scale intermittency and the deviation from Gaussianity. Besides the energy exchange intensity, the variations of $d$ considerably modify the relative weights of local to nonlocal triadic interactions. It is found that the contribution of the nonlocal triads to the total turbulent kinetic energy exchange increases as the Fourier dimension increases.

Scaling properties of a two-dimensional (2d) plasma physical current-sheet simulation model involving a full set of magnetohydrodynamic (MHD) equations with current-dependent resistivity are investigated. The current sheet supports a spatial magnetic field reversal that is forced through loading of magnetic flux containing plasma at boundaries of the simulation domain. A balance is reached between loading and annihilation of the magnetic flux through reconnection at the current sheet; the transport of magnetic flux from boundaries to current sheet is realized in the form of spatiotemporal avalanches exhibiting power-law statistics of lifetimes and sizes. We identify this dynamics as self-organized criticality (SOC) by verifying an extended set of scaling laws related to both global and local properties of the current sheet (critical susceptibility, finite-size scaling of probability distributions, geometric exponents). The critical exponents obtained from this analysis suggest that the model operates in a slowly driven SOC state similar to the mean-field state of the directed stochastic sandpile model. We also investigate multiscale correlations in the velocity field and find them numerically indistinguishable from certain intermittent turbulence (IT) theories. The results provide clues on physical conditions for SOC behavior in a broad class of plasma systems with propagating instabilities, and suggest that SOC and IT may coexist in driven current sheets which occur ubiquitously in astrophysical and space plasmas.

In this work, a high-order weighted essentially nonoscillatory (WENO) finite-difference lattice Boltzmann method (WENOLBM) is developed and assessed for an accurate simulation of incompressible flows. To handle curved geometries with nonuniform grids, the incompressible form of the discrete Boltzmann equation with the Bhatnagar-Gross-Krook (BGK) approximation is transformed into the generalized curvilinear coordinates and the spatial derivatives of the resulting lattice Boltzmann equation in the computational plane are solved using the fifth-order WENO scheme. The first-order implicit-explicit Runge-Kutta scheme and also the fourth-order Runge-Kutta explicit time integrating scheme are adopted for the discretization of the temporal term. To examine the accuracy and performance of the present solution procedure based on the WENOLBM developed, different benchmark test cases are simulated as follows: unsteady Taylor-Green vortex, unsteady doubly periodic shear layer flow, steady flow in a two-dimensional (2D) cavity, steady cylindrical Couette flow, steady flow over a 2D circular cylinder, and steady and unsteady flows over a NACA0012 hydrofoil at different flow conditions. Results of the present solution are compared with the existing numerical and experimental results which show good agreement. To show the efficiency and accuracy of the solution methodology, the results are also compared with the developed second-order central-difference finite-volume lattice Boltzmann method and the compact finite-difference lattice Boltzmann method. It is shown that the present numerical scheme is robust, efficient, and accurate for solving steady and unsteady incompressible flows even at high Reynolds number flows.

Spatially extended systems can support local transient excitations in which just a part of the system is excited. The mechanisms reported so far are local excitability and excitation of a localized structure. Here we introduce an alternative mechanism based on the coexistence of two homogeneous stable states and spatial coupling. We show the existence of a threshold for perturbations of the homogeneous state. Subthreshold perturbations decay exponentially. Superthreshold perturbations induce the emergence of a long-lived structure formed by two back to back fronts that join the two homogeneous states. While in typical excitability the trajectory follows the remnants of a limit cycle, here reinjection is provided by front interaction, such that fronts slowly approach each other until eventually annihilating. This front-mediated mechanism shows that extended systems with no oscillatory regimes can display excitability.

For a low-dissipation heat engine model we present the role of the partial contact times and the total operational time as control parameters to switch from maximum power state to maximum $\mathrm{\Omega }$ trade-off state. The symmetry of the dissipation coefficients may be used in the design of the heat engine to offer, in such switching, a suitable compromise between efficiency gain, power losses, and entropy change. Bounds for entropy production, efficiency, and power output are presented for transitions between both regimes. In the maximum power and maximum $\mathrm{\Omega }$ trade-off cases the relevant space of parameters are analyzed together with the configuration of minimum entropy production. A detailed analysis of the parameter's space shows physically prohibited regions in which there is no longer a heat engine and another region that is physically well behaved but is not suitable for possible optimization criteria.

For quite some time nonmonotonic flow curve was thought to be a requirement for shear banded flows in complex fluids. Thus, in simple yield stress fluids shear banding was considered to be absent. Recent spatially resolved rheological experiments have found simple yield stress fluids to exhibit shear banded flow profiles. One proposed mechanism for the initiation of such transient shear banding process has been a small stress heterogeneity rising from the experimental device geometry. Here, using computational fluid dynamics methods, we show that transient shear banding can be initialized even under homogeneous stress conditions by the fluid start-up inertia, and that such mechanism indeed is present in realistic experimental conditions.

The application of an electric field to microspheres suspended in a liquid crystal causes particle translation in a plane perpendicular to the applied field direction. Depending on applied electric field amplitude and frequency, a wealth of different motion modes may be observed above a threshold, which can lead to linear, circular, or random particle trajectories. We present the stability diagram for these different translational modes of particles suspended in the isotropic and the chiral nematic phase of a liquid crystal and investigate the angular velocity, circular diameter, and linear velocity as a function of electric field amplitude and frequency. In the isotropic phase a narrow field amplitude-frequency regime is observed to exhibit circular particle motion whose angular velocity increases with applied electric field amplitude but is independent of applied frequency. The diameter of the circular trajectory decreases with field amplitude as well as frequency. In the cholesteric phase linear as well as circular particle motion is observed. The former exhibits an increasing velocity with field amplitude, while decreasing with frequency. For the latter, the angular velocity exhibits an increase with field amplitude and frequency. The rotational sense of the particles on a circular trajectory in the chiral nematic phase is independent of the helicity of the liquid crystalline structure, as is demonstrated by employing a cholesteric twist inversion compound.

The impact of water drops onto a solid surface at subfreezing temperatures has been experimentally studied. Drop nucleation has been observed using a high-speed video system. The statistics of nucleation allows the estimation of the average number of nucleation sites per unit area of the wetted part of the substrate. We have discovered that the nucleation rate in the impacting drop is not constant. The observed significant increase of the nucleation rate at small times after impact $t<50$ ms can be explained by the generation of nanobubbles at early times of drop impact. These bubbles serve as additional nucleation sites and enhance the nucleation rate.

We investigate numerically and theoretically the internal structures of a driven granular gas in cuboidal cell geometries. Clustering is reported and particles are classified as gaseous or clustered via a local packing fraction criterion based on a Voronoi tessellation. We observe that small clusters arise in the corners of the box, elucidating early reports of partial clustering. These aggregates have a condensation-like surface growth. When a critical size is reached, a structural transition occurs and all clusters merge together, leaving a hole in the center of the cell. This hole then becomes the new center of particle capture. Taking into account all structural modifications and defining a saturation packing fraction, we propose an empirical model for the cluster growth.

The nonequilibrium gas flow in a two-dimensional microchannel with a ratchet surface and a moving wall is investigated numerically with a kinetic method [Guo et al., Phys. Rev. E 91, 033313 (2015)]. The presence of periodic asymmetrical ratchet structures on the bottom wall of the channel and the temperature difference between the walls of the channel result in a thermally induced flow, and hence a tangential propelling force on the wall. Such thermally induced propelling mechanism can be utilized as a model heat engine. In this article, the relations between the propelling force and the top wall moving velocity are obtained by solving the Boltzmann equation with the Shakhov model deterministically in a wide range of Knudsen numbers. The flow fields at both the static wall state and the critical state at which the thermally induced force cancels the drag force due to the active motion of the top wall are analyzed. A counterintuitive relation between the flow direction and the shear force is observed in the highly rarefied condition. The output power and thermal efficiency of the system working as a model heat engine are analyzed based on the momentum and energy transfer between the walls. The effects of Knudsen number, temperature difference, and geometric configurations are investigated. Guidance for improving the mechanical performance is discussed.

The generalized Crank-Nicolson method is employed to obtain numerical solutions of the two-dimensional time-dependent Schrödinger equation. An adapted alternating-direction implicit method is used, along with a high-order finite-difference scheme in space. Extra care has to be taken for the needed precision of the time development. The method permits a systematic study of the accuracy and efficiency in terms of powers of the spatial and temporal step sizes. To illustrate its utility the method is applied to several two-dimensional systems.

Within the framework of the central-moment-based lattice Boltzmann method, we propose a strategy to account for external forces in two and three dimensions. Its numerical properties are evaluated against consolidated benchmark problems, highlighting very high accuracy and optimal convergence. Moreover, our derivations are light and intelligible.

The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

In this paper, a higher order Chapmann-Enskog expansion technique is applied to pseudopotential lattice Boltzmann equation (LBE), and the contribution of third order error terms to pressure tensor is analyzed in detail. To be consistent with the thermodynamic theory, a force term is introduced to modify the coefficients in the pressure tensor. Some numerical simulations are conducted to validate the LBE, and the results show that the predictions of the present LBE agree well with the analytical solution and other predictions.

Aging can be observed for numerous physical systems. In such systems statistical properties [like probability distribution, mean square displacement (MSD), first-passage time] depend on a time span $t_a$ between the initialization and the beginning of observations. In this paper we study aging properties of ballistic Lévy walks and two closely related jump models: wait-first and jump-first. We calculate explicitly their probability distributions and MSDs. It turns out that despite similarities these models react very differently to the delay $t_a$. Aging weakly affects the shape of probability density function and MSD of standard Lévy walks. For the jump models the shape of the probability density function is changed drastically. Moreover for the wait-first jump model we observe a different behavior of MSD when $t_a\ll t$ and $t_a\gg t$.