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This article presents the results of an analytical and computer study of the collective dynamic properties of a chain of self-oscillating systems (conditionally — oscillators). It is assumed that the couplings of individual elements of the chain are non-reciprocal, unidirectional. More precisely, it is assumed that each element of the chain is under the influence of the previous one, while the reverse reaction is absent (physically insignificant). This is the main feature of the chain. This system can be interpreted as an active discrete medium with unidirectional transfer, in particular, the transfer of a matter. Such chains can represent mathematical models of real systems having a lattice structure that occur in various fields of natural science and technology: physics, chemistry, biology, radio engineering, economics, etc. They can also represent models of technological and computational processes. Nonlinear self-oscillating systems (conditionally, oscillators) with a wide “spectrum” of potentially possible individual self-oscillations, from periodic to chaotic, were chosen as the “elements” of the lattice. This allows one to explore various dynamic modes of the chain from regular to chaotic, changing the parameters of the elements and not changing the nature of the elements themselves. The joint application of qualitative methods of the theory of dynamical systems and qualitative-numerical methods allows one to obtain a clear picture of all possible dynamic regimes of the chain. The conditions for the existence and stability of spatially-homogeneous dynamic regimes (deterministic and chaotic) of the chain are studied. The analytical results are illustrated by a numerical experiment. The dynamical regimes of the chain are studied under perturbations of parameters at its boundary. The possibility of controlling the dynamic regimes of the chain by turning on the necessary perturbation at the boundary is shown. Various cases of the dynamics of chains comprised of inhomogeneous (different in their parameters) elements are considered. The global chaotic synchronization (of all oscillators in the chain) is studied analytically and numerically.

We developed an algorithm for fast simulation of VLSI CMOS (Very Large Scale Integration with Complementary Metal-Oxide-Semiconductors) with an accuracy control. The algorithm provides an ability of parallel numerical experiments in multiprocessor computational environment. There is computation speed up by means of block-matrix and structural (DCCC) decompositions application. A feature of the approach is both in a choice of moments and ways of parameters synchronization and application of multi-rate integration methods. Due to this fact we have ability to estimate and control error of given characteristics.

This article is investigated phenomenon of asteroid braking in neighborhood Chelyabinsk. Simulation of trajectory and asteroid basic parameters is accomplished on the basis of not numerous fixed video film and measurements. Calculation of hypersonic flow around asteroid is carried out before and after asteroid collapse. Possible version of asteroids synchronous braking is discussed. Trajectory data and gas dynamic functions are presented as data for definition of asteroid collapse.

In this paper, we propose a new software for simulation of fluid-structure interaction. The software is designed for solving coupled problems and provides an interface for synchronization synchronisation and data exchange between existing fluid and structural solvers. Algorithms of coupling solvers and mesh deformation are discussed. The software can be used on hybrid CPU/GPU platforms.

The propagation of stable coherent entities of an electromagnetic field in nonlinear media with parameters varying in space can be described in the framework of iterations of nonlinear integral transformations. It is shown that for a set of geometries relevant to typical problems of nonlinear optics, numerical modeling by reducing to dynamical systems with discrete time and continuous spatial variables to iterates of local nonlinear Feigenbaum and Ikeda mappings and nonlocal diffusion-dispersion linear integral transforms is equivalent to partial differential equations of the Ginzburg–Landau type in a fairly wide range of parameters. Such nonlocal mappings, which are the products of matrix operators in the numerical implementation, turn out to be stable numerical- difference schemes, provide fast convergence and an adequate approximation of solutions. The realism of this approach allows one to take into account the effect of noise on nonlinear dynamics by superimposing a spatial noise specified in the form of a multimode random process at each iteration and selecting the stable wave configurations. The nonlinear wave formations described by this method include optical phase singularities, spatial solitons, and turbulent states with fast decay of correlations. The particular interest is in the periodic configurations of the electromagnetic field obtained by this numerical method that arise as a result of phase synchronization, such as optical lattices and self-organized vortex clusters.

We present a simulation methodology for the prediction of ЃgunexpectedЃh bottlenecks, i.e., the bottlenecks that occur suddenly and unexpectedly for drivers on a highway. Such unexpected bottlenecks can be either a moving bottleneck (MB) caused by a slow moving vehicle or a motionless bottleneck caused by a stopped vehicle (SV). Based on simulations of a stochastic microscopic traffic flow model in the framework of KernerЃfs three-phase traffic theory, we show that through the use of a small share of probe vehicles (FCD) randomly distributed in traffic flow the reliable prediction of ЃgunexpectedЃh bottlenecks is possible. We have found that the time dependence of the probability of MB and SV prediction as well as the accuracy of the estimation of MB and SV location depend considerably on sequences of phase transitions from free flow (F) to synchronized flow (S) (F→S transition) and back from synchronized flow to free flow (S→F transition) as well as on speed oscillations in synchronized flow at the bottleneck. In the simulation approach, the identification of F→S and S→F transitions at an unexpected bottleneck has been made in accordance with Kerner's three-phase traffic theory. The presented simulation methodology allows us both the prediction of the unexpected bottleneck that suddenly occurs on a highway and the distinguishing of the origin of the unexpected bottleneck, i.e., whether the unexpected bottleneck has occurred due to a MB or a SV.

Traditional geological search methods going to be ineffective. The exploration depth of kimberlite bodies and ore deposits has increased significantly. The only direct exploration method is to drill a system of wells to the depths that provide access to the enclosing rocks. Due to the high cost of drilling, the role of inter-well survey methods has increased. They allows to increase the mean well spacing without significantly reducing the kimberlite or ore body missing probability. The method of inter-well radio wave survey is effective to search for high contrast conductivity objects. The physics of the method based on the dependence of the electromagnetic wave propagation on the propagation medium conductivity. The source and receiver of electromagnetic radiation is an electric dipole, they are placed in adjacent wells. The distance between the source and receiver is known. Therefore we could estimate the medium absorption coefficient by the rate of radio wave amplitude decrease. Low electrical resistance rocks corresponds to high absorption of radio waves. The inter-well measurement data allows to estimate an effective electrical resistance (or conductivity) of the rock. Typically, the source and receiver are immersed in adjacent wells synchronously. The value of the of the electric field amplitude measured at the receiver site allows to estimate the average value of the attenuation coefficient on the line connecting the source and receiver. The measurements are taken during stops, approximately every 5 m. The distance between stops is much less than the distance between adjacent wells. This leads to significant spatial anisotropy in the measured data distribution. Drill grid covers a large area, and our point is to build a three-dimensional model of the distribution of the electrical properties of the inter-well space throughout the whole area. The anisotropy of spatial distribution makes hard to the use of standard geostatistics approach. To build a three-dimensional model of attenuation coefficient, we used one of machine learning theory methods, the method of nearest neighbors. In this method, the value of the absorption coefficient at a given point is calculated by $k$ nearest measurements. The number $k$ should be determined from additional reasons. The spatial distribution anisotropy effect can be reduced by changing the spatial scale in the horizontal direction. The scale factor $\lambda$ is one yet external parameter of the problem. To select the parameters $k$ and $\lambda$ values we used the determination coefficient. To demonstrate the absorption coefficient three-dimensional image construction we apply the procedure to the inter-well radio wave survey data. The data was obtained at one of the sites in Yakutia.

Kuramoto model of non-linearly coupled oscillators provides a simple but effective approach to the study of the synchronization phenomenon in complex systems. In the present article we consider a particular Kuramoto model with three non-identical oscillators associated with a multi-cell radial profile of the solar meridional circulation. The top and the bottom oscillators are coupled through the middle one. The main difference of the present Kuramoto model from the previous ones consists in the non-identical coupling: coupling coefficients which tie the middle oscillator with the top and the bottom ones are different. We investigate how the value of the coupling asymmetry of the middle oscillator influences the synchronization. In the present model the synchronization conditions appear to be different the classical Kuramoto model allowing the synchronization to be reached with weaker coupling. We perform a reconstruction of coupling coefficients from the phase difference between the top and the bottom oscillators, assuming that the synchronization is reached and the natural frequencies are known. The absolute cumulative coupling is uniquely determined by the phase difference between the top and the bottom oscillators and the coupling asymmetry of the middle oscillator. In general case, higher values of the coupling asymmetry of the middle oscillator correspond to lower cumulative coupling. A unique coupling reconstruction with unknown coupling asymmetry is possible in general case only for the weak cumulative coupling. Deviations from the general case are discussed. We perform a model simulation with natural frequencies estimated from the velocities of the solar meridional flow. Heliseismological observations of the deep flow may be attributed either to the middle cell or to the deep one. We discuss the difference between these two cases in terms of the coupling reconstruction.

We derive a new model of circadian oscillations in Neurospora crassa, which is suitable to analyze both temporal and spatial dynamics of proteins responsible for mechanism of rythms. The model is based on the non-linear interplay between proteins FRQ and WCC which are products of transcription of frequency and white collar genes forming a feedback loop comprised both positive and negative elements. The main component of oscillations mechanism is supposed to be time-delay in biochemical reactions of transcription. We show that the model accounts for various features observed in Neurospora’s experiments such as entrainment by light cycles, phase shift under light pulse, robustness to action of fluctuations and so on. Wave patterns excited during spatial development of the system are studied. It is shown that the wave of synchronization of biorythms arises under basal transcription factors.

The article proposes a method of joint analysis of multidimensional financial time series based on the evaluation of the set of properties of stock quotes in a sliding time window and the subsequent averaging of property values for all analyzed companies. The main purpose of the analysis is to construct measures of joint behavior of time series reacting to the occurrence of a synchronous or coherent component. The coherence of the behavior of the characteristics of a complex system is an important feature that makes it possible to evaluate the approach of the system to sharp changes in its state. The basis for the search for precursors of sharp changes is the general idea of increasing the correlation of random fluctuations of the system parameters as it approaches the critical state. The increments in time series of stock values have a pronounced chaotic character and have a large amplitude of individual noises, against which a weak common signal can be detected only on the basis of its correlation in different scalar components of a multidimensional time series. It is known that classical methods of analysis based on the use of correlations between neighboring samples are ineffective in the processing of financial time series, since from the point of view of the correlation theory of random processes, increments in the value of shares formally have all the attributes of white noise (in particular, the “flat spectrum” and “delta-shaped” autocorrelation function). In connection with this, it is proposed to go from analyzing the initial signals to examining the sequences of their nonlinear properties calculated in time fragments of small length. As such properties, the entropy of the wavelet coefficients is used in the decomposition into the Daubechies basis, the multifractal parameters and the autoregressive measure of signal nonstationarity. Measures of synchronous behavior of time series properties in a sliding time window are constructed using the principal component method, moduli values of all pairwise correlation coefficients, and a multiple spectral coherence measure that is a generalization of the quadratic coherence spectrum between two signals. The shares of 16 large Russian companies from the beginning of 2010 to the end of 2016 were studied. Using the proposed method, two synchronization time intervals of the Russian stock market were identified: from mid-December 2013 to mid- March 2014 and from mid-October 2014 to mid-January 2016.