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The generalization of Margolus’s block cellular automaton on a hexagonal grid is formulated. Statistical analysis of the results of probabilistic cellular automation for vast variety of this scheme solving the test task of diffusion is done. It is shown that the choice of the hexagon blocks is 25% more efficient than Y-blocks. It is shown that the algorithms have polynomial complexity, and the polynom degree lies within 0.6÷0.8 for parallel computer, and in the range 1.5÷1.7 for serial computer. The effects of embedded into automaton’s field defective cells on the rate of convergence are studied also.

In the article a theory of the implicit iterative line-by-line recurrence method for solving the systems of finite-difference equations which arise as a result of approximation of the two-dimensional elliptic differential equations on a regular grid is stated. On the one hand, the high effectiveness of the method has confirmed in practice. Some complex test problems, as well as several problems of fluid flow and heat transfer of a viscous incompressible liquid, have solved with its use. On the other hand, the theoretical provisions that explain the high convergence rate of the method and its stability are not yet presented in the literature. This fact is the reason for the present investigation. In the paper, the procedure of equivalent and approximate transformations of the initial system of linear algebraic equations (SLAE) is described in detail. The transformations are presented in a matrix-vector form, as well as in the form of the computational formulas of the method. The key points of the transformations are illustrated by schemes of changing of the difference stencils that correspond to the transformed equations. The canonical form of the method is the goal of the transformation procedure. The correctness of the method follows from the canonical form in the case of the solution convergence. The estimation of norms of the matrix operators is carried out on the basis of analysis of structures and element sets of the corresponding matrices. As a result, the convergence of the method is proved for arbitrary initial vectors of the solution of the problem.

The norm of the transition matrix operator is estimated in the special case of weak restrictions on a desired solution. It is shown, that the value of this norm decreases proportionally to the second power (or third degree, it depends on the version of the method) of the grid step of the problem solution area in the case of transition matrix order increases. The necessary condition of the method stability is obtained by means of simple estimates of the vector of an approximate solution. Also, the estimate in order of magnitude of the optimum iterative compensation parameter is given. Theoretical conclusions are illustrated by using the solutions of the test problems. It is shown, that the number of the iterations required to achieve a given accuracy of the solution decreases if a grid size of the solution area increases. It is also demonstrated that if the weak restrictions on solution are violated in the choice of the initial approximation of the solution, then the rate of convergence of the method decreases essentially in full accordance with the deduced theoretical results.

The study of the physiological and pathophysiological processes in the cardiovascular system is one of the important contemporary issues, which is addressed in many works. In this work, several approaches to the mathematical modelling of the blood flow are considered. They are based on the spatial order reduction and/or use a steady-state approach. Attention is paid to the discussion of the assumptions and suggestions, which are limiting the scope of such models. Some typical mathematical formulations are considered together with the brief review of their numerical implementation. In the first part, we discuss the models, which are based on the full spatial order reduction and/or use a steady-state approach. One of the most popular approaches exploits the analogy between the flow of the viscous fluid in the elastic tubes and the current in the electrical circuit. Such models can be used as an individual tool. They also used for the formulation of the boundary conditions in the models using one dimensional (1D) and three dimensional (3D) spatial coordinates. The use of the dynamical compartment models allows describing haemodynamics over an extended period (by order of tens of cardiac cycles and more). Then, the steady-state models are considered. They may use either total spatial reduction or two dimensional (2D) spatial coordinates. This approach is used for simulation the blood flow in the region of microcirculation. In the second part, we discuss the models, which are based on the spatial order reduction to the 1D coordinate. The models of this type require relatively small computational power relative to the 3D models. Within the scope of this approach, it is also possible to include all large vessels of the organism. The 1D models allow simulation of the haemodynamic parameters in every vessel, which is included in the model network. The structure and the parameters of such a network can be set according to the literature data. It also exists methods of medical data segmentation. The 1D models may be derived from the 3D Navier – Stokes equations either by asymptotic analysis or by integrating them over a volume. The major assumptions are symmetric flow and constant shape of the velocity profile over a cross-section. These assumptions are somewhat restrictive and arguable. Some of the current works paying attention to the 1D model’s validation, to the comparing different 1D models and the comparing 1D models with clinical data. The obtained results reveal acceptable accuracy. It allows concluding, that the 1D approach can be used in medical applications. 1D models allow describing several dynamical processes, such as pulse wave propagation, Korotkov’s tones. Some physiological conditions may be included in the 1D models: gravity force, muscles contraction force, regulation and autoregulation.

The paper contains the analysis of the domestic publications issued in 2013–2017 years and devoted to cellular automata. The most of them concern on mathematical modeling. Scientometric schedules for 1990–2017 years have proved relevance of subject. The review allows to allocate the main personalities and the scientific directions/schools in modern Russian science, to reveal their originality or secondness in comparison with world science. Due to the authors choice of national publications basis instead of world, the paper claims the completeness and the fact is that about 200 items from the checked 526 references have an importance for science.

In the Annex to the review provides preliminary information about CA — the Game of Life, a theorem about gardens of Eden, elementary CAs (together with the diagram of de Brujin), block Margolus’s CAs, alternating CAs. Attention is paid to three important for modeling semantic traditions of von Neumann, Zuse and Zetlin, as well as to the relationship with the concepts of neural networks and Petri nets. It is allocated conditional 10 works, which should be familiar to any specialist in CA. Some important works of the 1990s and later are listed in the Introduction.

Then the crowd of publications is divided into categories: the modification of the CA and other network models (29 %), Mathematical properties of the CA and the connection with mathematics (5 %), Hardware implementation (3 %), Software implementation (5 %), Data Processing, recognition and Cryptography (8 %), Mechanics, physics and chemistry (20 %), Biology, ecology and medicine (15 %), Economics, urban studies and sociology (15 %). In parentheses the share of subjects in the array are indicated. There is an increase in publications on CA in the humanitarian sphere, as well as the emergence of hybrid approaches, leading away from the classic CA definition.

Padé approximation is a useful tool for extracting singularity information from a power series. A linear Padé approximant is a rational function and can provide estimates of pole and zero locations in the complex plane. A quadratic Padé approximant has square root singularities and can, therefore, provide additional information such as estimates of branch point locations. In this paper, we discuss numerical aspects of computing quadratic Padé approximants as well as some applications. Two algorithms for computing the coefficients in the approximant are discussed: a direct method involving the solution of a linear system (well-known in the mathematics community) and a recursive method (well-known in the physics community). We compare the accuracy of these two methods when implemented in floating-point arithmetic and discuss their pros and cons. In addition, we extend Luke’s perturbation analysis of linear Padé approximation to the quadratic case and identify the problem of spurious branch points in the quadratic approximant, which can cause a significant loss of accuracy. A possible remedy for this problem is suggested by noting that these troublesome points can be identified by the recursive method mentioned above. Another complication with the quadratic approximant arises in choosing the appropriate branch. One possibility, which is to base this choice on the linear approximant, is discussed in connection with an example due to Stahl. It is also known that the quadratic method is capable of providing reasonable approximations on secondary sheets of the Riemann surface, a fact we illustrate here by means of an example. Two concluding applications show the superiority of the quadratic approximant over its linear counterpart: one involving a special function (the Lambert $W$-function) and the other a nonlinear PDE (the continuation of a solution of the inviscid Burgers equation into the complex plane).

The article provides approaches to evolutionary modelling of synthesis of organised systems and analyses methodological problems of evolutionary computations of this kind. Based on the analysis of works on evolutionary cybernetics, evolutionary theory, systems theory and synergetics, we conclude that there are open problems in formalising the synthesis of organised systems and modelling their evolution. The article emphasises that the theoretical basis for the practice of evolutionary modelling is the principles of the modern synthetic theory of evolution. Our software project uses a virtual computing environment for machine synthesis of problem solving algorithms. In the process of modelling, we obtained the results on the basis of which we conclude that there are a number of conditions that fundamentally limit the applicability of genetic programming methods in the tasks of synthesis of functional structures. The main limitations are the need for the fitness function to track the step-by-step approach to the solution of the problem and the inapplicability of this approach to the problems of synthesis of hierarchically organised systems. We note that the results obtained in the practice of evolutionary modelling in general for the whole time of its existence, confirm the conclusion the possibilities of genetic programming are fundamentally limited in solving problems of synthesizing the structure of organized systems. As sources of fundamental difficulties for machine synthesis of system structures the article points out the absence of directions for gradient descent in structural synthesis and the absence of regularity of random appearance of new organised structures. The considered problems are relevant for the theory of biological evolution. The article substantiates the statement about the biological specificity of practically possible ways of synthesis of the structure of organised systems. As a theoretical interpretation of the discussed problem, we propose to consider the system-evolutionary concept of P.K.Anokhin. The process of synthesis of functional structures in this context is an adaptive response of organisms to external conditions based on their ability to integrative synthesis of memory, needs and information about current conditions. The results of actual studies are in favour of this interpretation. We note that the physical basis of biological integrativity may be related to the phenomena of non-locality and non-separability characteristic of quantum systems. The problems considered in this paper are closely related to the problem of creating strong artificial intelligence.

Difference of software development for parallel computing technology from sequential programming is dicussed. Arguements for introduction of new phases into technology of software engineering are given. These phases are: decomposition of algorithms, assignment of jobs to performers, conducting and mapping of logical to physical performers. Issues of performance evaluation of algorithms are briefly discussed. Decomposition of algorithms and programs into parts that can be executed in parallel is dicussed.

The given work is devoted to the comparison of two tests for homogeneity: chi-square test based on contingency tables of 2 × 2 and test for homogeneity based on asymptotic distributions of the summarized square error of a distribution function estimators in the model of ”dose–effect” dependence. The evaluation of test power is performed by means of computer simulation. In order to design efficiency functions the method of kernel regression estimator based on Nadaray–Watson estimator is used.

Comparative analysis of two numerical methods for simulation of unsteady natural convection and thermal surface radiation within a differentially heated cubical cavity has been carried out. The considered domain of interest had two isothermal opposite vertical faces, while other walls are adiabatic. The walls surfaces were diffuse and gray, namely, their directional spectral emissivity and absorptance do not depend on direction or wavelength but can depend on surface temperature. For the reflected radiation we had two approaches such as: 1) the reflected radiation is diffuse, namely, an intensity of the reflected radiation in any point of the surface is uniform for all directions; 2) the reflected radiation is uniform for each surface of the considered enclosure. Mathematical models formulated both in primitive variables “velocity–pressure” and in transformed variables “vector potential functions – vorticity vector” have been performed numerically using finite volume method and finite difference methods, respectively. It should be noted that radiative heat transfer has been analyzed using the net-radiation method in Poljak approach.

Using primitive variables and finite volume method for the considered boundary-value problem we applied power-law for an approximation of convective terms and central differences for an approximation of diffusive terms. The difference motion and energy equations have been solved using iterative method of alternating directions. Definition of the pressure field associated with velocity field has been performed using SIMPLE procedure.

Using transformed variables and finite difference method for the considered boundary-value problem we applied monotonic Samarsky scheme for convective terms and central differences for diffusive terms. Parabolic equations have been solved using locally one-dimensional Samarsky scheme. Discretization of elliptic equations for vector potential functions has been conducted using symmetric approximation of the second-order derivatives. Obtained difference equation has been solved by successive over-relaxation method. Optimal value of the relaxation parameter has been found on the basis of computational experiments.

As a result we have found the similar distributions of velocity and temperature in the case of these two approaches for different values of Rayleigh number, that illustrates an operability of the used techniques. The efficiency of transformed variables with finite difference method for unsteady problems has been shown.

The well-known evolutionary equation of mathematical physics, which in modern mathematical literature is called the Kuramoto – Sivashinsky equation, is considered. In this paper, this equation is studied in the original edition of the authors, where it was proposed, together with the homogeneous Neumann boundary conditions.

The question of the existence and stability of local attractors formed by spatially inhomogeneous solutions of the boundary value problem under study has been studied. This issue has become particularly relevant recently in connection with the simulation of the formation of nanostructures on the surface of semiconductors under the influence of an ion flux or laser radiation. The question of the existence and stability of second-order equilibrium states has been studied in two different ways. In the first of these, the Galerkin method was used. The second approach is based on using strictly grounded methods of the theory of dynamic systems with infinite-dimensional phase space: the method of integral manifolds, the theory of normal forms, asymptotic methods.

In the work, in general, the approach from the well-known work of D.Armbruster, D.Guckenheimer, F.Holmes is repeated, where the approach based on the application of the Galerkin method is used. The results of this analysis are substantially supplemented and developed. Using the capabilities of modern computers has helped significantly complement the analysis of this task. In particular, to find all the solutions in the fourand five-term Galerkin approximations, which for the studied boundary-value problem should be interpreted as equilibrium states of the second kind. An analysis of their stability in the sense of A. M. Lyapunov’s definition is also given.

In this paper, we compare the results obtained using the Galerkin method with the results of a bifurcation analysis of a boundary value problem based on the use of qualitative analysis methods for infinite-dimensional dynamic systems. Comparison of two variants of results showed some limited possibilities of using the Galerkin method.