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The work belongs to the direction of experimental mathematics, which investigates the properties of mathematical objects by the computing facilities of a computer. The base is an exponential map, its topological properties (Cantor's bouquets) differ from properties of polynomial and rational complex-valued functions. The subject of the study are the character and features of the Fatou and Julia sets, as well as the equilibrium points and orbits of the zero of three iterated complex-valued mappings: $f:z \to (1+ \mu) \exp (iz)$, $g : z \to \big(1+ \mu |z - z^*|\big) \exp (iz)$, $h : z \to \big(1+ \mu (z - z^* )\big) \exp (iz)$, with $z,\mu \in \mathbb{C}$, $z^* : \exp (iz^*) = z^*$. For a quasilinear map g having no analyticity characteristic, two bifurcation transitions were discovered: the creation of a new equilibrium point (for which the critical value of the linear parameter was found and the bifurcation consists of “fork” type and “saddle”-node transition) and the transition to the radical transformation of the Fatou set. A nontrivial character of convergence to a fixed point is revealed, which is associated with the appearance of “valleys” on the graph of convergence rates. For two other maps, the monoperiodicity of regimes is significant, the phenomenon of “period doubling” is noted (in one case along the path $39\to 3$, in the other along the path $17\to 2$), and the coincidence of the period multiplicity and the number of sleeves of the Julia spiral in a neighborhood of a fixed point is found. A rich illustrative material, numerical results of experiments and summary tables reflecting the parametric dependence of maps are given. Some questions are formulated in the paper for further research using traditional mathematics methods.

The problem of online convex optimization naturally occurs in cases when there is an update of statistical information. The mirror descent method is well known for non-smooth optimization problems. Mirror descent is an extension of the subgradient method for solving non-smooth convex optimization problems in the case of a non-Euclidean distance. This paper is devoted to a stochastic variant of recently proposed Mirror Descent methods for convex online optimization problems with convex Lipschitz (generally, non-smooth) functional constraints. This means that we can still use the value of the functional constraint, but instead of (sub)gradient of the objective functional and the functional constraint, we use their stochastic (sub)gradients. More precisely, assume that on a closed subset of $n$-dimensional vector space, $N$ convex Lipschitz non-smooth functionals are given. The problem is to minimize the arithmetic mean of these functionals with a convex Lipschitz constraint. Two methods are proposed, for solving this problem, using stochastic (sub)gradients: adaptive method (does not require knowledge of Lipschitz constant neither for the objective functional, nor for the functional of constraint) and non-adaptivemethod (requires knowledge of Lipschitz constant for the objective functional and the functional of constraint). Note that it is allowed to calculate the stochastic (sub)gradient of each functional only once. In the case of non-negative regret, we find that the number of non-productive steps is $O$($N$), which indicates the optimality of the proposed methods. We consider an arbitrary proximal structure, which is essential for decisionmaking problems. The results of numerical experiments are presented, allowing to compare the work of adaptive and non-adaptive methods for some examples. It is shown that the adaptive method can significantly improve the number of the found solutions.

In this paper, we consider the conjugate gradient method for solving the problem of minimizing a quadratic function with additive noise in the gradient. Three concepts of noise were considered: antagonistic noise in the linear term, stochastic noise in the linear term and noise in the quadratic term, as well as combinations of the first and second with the last. It was experimentally obtained that error accumulation is absent for any of the considered concepts, which differs from the folklore opinion that, as in accelerated methods, error accumulation must take place. The paper gives motivation for why the error may not accumulate. The dependence of the solution error both on the magnitude (scale) of the noise and on the size of the solution using the conjugate gradient method was also experimentally investigated. Hypotheses about the dependence of the error in the solution on the noise scale and the size (2-norm) of the solution are proposed and tested for all the concepts considered. It turned out that the error in the solution (by function) linearly depends on the noise scale. The work contains graphs illustrating each individual study, as well as a detailed description of numerical experiments, which includes an account of the methods of noise of both the vector and the matrix.

The paper presents a numerical solution to the heat wave motion problem for a degenerate second-order nonlinear parabolic equation with a source term. The nonlinearity is conditioned by the power dependence of the heat conduction coefficient on temperature. The problem for the case of two spatial variables is considered with the boundary condition specifying the heat wave motion law. A new solution algorithm based on an expansion in radial basis functions and the boundary element method is proposed. The solution is constructed stepwise in time with finite difference time approximation. At each time step, a boundary value problem for the Poisson equation corresponding to the original equation at a fixed time is solved. The solution to this problem is constructed iteratively as the sum of a particular solution to the nonhomogeneous equation and a solution to the corresponding homogeneous equation satisfying the boundary conditions. The homogeneous equation is solved by the boundary element method. The particular solution is sought by the collocation method using inhomogeneity expansion in radial basis functions. The calculation algorithm is optimized by parallelizing the computations. The algorithm is implemented as a program written in the C++ language. The parallel computations are organized by using the OpenCL standard, and this allows one to run the same parallel code either on multi-core CPUs or on graphic CPUs. Test cases are solved to evaluate the effectiveness of the proposed solution method and the correctness of the developed computational technique. The calculation results are compared with known exact solutions, as well as with the results we obtained earlier. The accuracy of the solutions and the calculation time are estimated. The effectiveness of using various systems of radial basis functions to solve the problems under study is analyzed. The most suitable system of functions is selected. The implemented complex computational experiment shows higher calculation accuracy of the proposed new algorithm than that of the previously developed one.

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.

Investigation of occurrence of diffusion instability in a set of three reaction–diffusion equations is carried out. In the general case the condition for both Turing and wave instabilities are obtained. Qualitative properties of the system, in which the bifurcation of each of the two types can take place, are clarified. In numerical experiments it is shown that if the corresponding conditions are met in the nonlinear model, spatiotemporal patterns are formed, which are predicted by linear analysis.

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.

The paper provides a solution of the two-parameter task of joint signal and noise estimation at data analysis within the conditions of the Rice distribution by the techniques of mathematical statistics: the maximum likelihood method and the variants of the method of moments. The considered variants of the method of moments include the following techniques: the joint signal and noise estimation on the basis of measuring the 2-nd and the 4-th moments (MM24) and on the basis of measuring the 1-st and the 2-nd moments (MM12). For each of the elaborated methods the explicit equations’ systems have been obtained for required parameters of the signal and noise. An important mathematical result of the investigation consists in the fact that the solution of the system of two nonlinear equations with two variables — the sought for signal and noise parameters — has been reduced to the solution of just one equation with one unknown quantity what is important from the view point of both the theoretical investigation of the proposed technique and its practical application, providing the possibility of essential decreasing the calculating resources required for the technique’s realization. The implemented theoretical analysis has resulted in an important practical conclusion: solving the two-parameter task does not lead to the increase of required numerical resources if compared with the one-parameter approximation. The task is meaningful for the purposes of the rician data processing, in particular — the image processing in the systems of magnetic-resonance visualization. The theoretical conclusions have been confirmed by the results of the numerical experiment.

Equations of motion in Newtonian and Hamiltonian forms are used for classical molecular dynamics simulation of particle system time evolution. When Newton equations of motion are used for finding of particle coordinates and velocities in $N$-particle system it takes to solve $3N$ ordinary differential equations of second order at every time step. Traditionally numerical schemes of Verlet method are used for solving Newtonian equations of motion of molecular dynamics. A step of integration is necessary to decrease for Verlet numerical schemes steadiness conservation on sufficiently large time intervals. It leads to a significant increase of the volume of calculations. Numerical schemes of Verlet method with Hamiltonian conservation control (the energy of the system) at every time moment are used in the most software packages of molecular dynamics for numerical integration of equations of motion. It can be used two complement each other approaches to decrease of computational time in molecular dynamics calculations. The first of these approaches is based on enhancement and software optimization of existing software packages of molecular dynamics by using of vectorization, parallelization and special processor construction. The second one is based on the elaboration of efficient methods for numerical integration for equations of motion. A procedure for constructing of explicit, implicit and symmetric symplectic numerical schemes with given approximation accuracy in relation to integration step for solving of molecular dynamic equations of motion in Hamiltonian form is proposed in this work. The approach for construction of proposed in this work procedure is based on the following points: Hamiltonian formulation of equations of motion; usage of Taylor expansion of exact solution; usage of generating functions, for geometrical properties of exact solution conservation, in derivation of numerical schemes. Numerical experiments show that obtained in this work symmetric symplectic third-order accuracy scheme conserves basic properties of the exact solution in the approximate solution. It is more stable for approximation step and conserves Hamiltonian of the system with more accuracy at a large integration interval then second order Verlet numerical schemes.

Verification results of supersonic turbulent jets computational characteristics are presented. Numerical simulation of axisymmetric nozzle operating is realized using FlowVision CFD. Open test cases for CFD are used. The test cases include Seiner tests with exit Mach number of 2.0 both fully-expanded and under-expanded $(P/P_0 = 1.47)$. Fully-expanded nozzle investigated with wide range of flow temperature (300…3000 K). The considered studies include simulation downstream from the nozzle exit diameter. Next numerical investigation is presented at an exit Mach number of 2.02 and a free-stream Mach number of 2.2. Geometric model of convergent- divergent nozzle rebuilt from original Putnam experiment. This study is set with nozzle pressure ratio of 8.12 and total temperature of 317 K.

The paper provides a comparison of obtained FlowVision results with experimental data and another current CFD studies. A comparison of the calculated characteristics and experimental data indicates a good agreement. The best coincidence with Seiner's experimental velocity distribution (about 7 % at far field for the first case) obtained using two-equation $k–\varepsilon$ standard turbulence model with Wilcox compressibility correction. Predicted Mach number distribution at $Y/D = 1$ for Putnam nozzle presents accuracy of 3 %.

General guidelines for simulation of supersonic turbulent jets in the FlowVision software are formulated in the given paper. Grid convergence determined the optimal cell rate. In order to calculate the design regime, it is recommended to build a grid, containing not less than 40 cells from the axis of symmetry to the nozzle wall. In order to calculate an off-design regime, it is necessary to resolve the shock waves. For this purpose, not less than 80 cells is required in the radial direction. Investigation of the influence of turbulence model on the flow characteristics has shown that the version of the SST $k–\omega$ turbulence model implemented in the FlowVision software essentially underpredicts the axial velocity. The standard $k–\varepsilon$ model without compressibility correction also underpredicts the axial velocity. These calculations agree well with calculations in other CFD codes using the standard $k–\varepsilon$ model. The in-home $k–\varepsilon$ turbulence model KEFV with compressibility correction a little bit overpredicts the axial velocity. Since, the best results are obtained using the standard $k–\varepsilon$ model combined with the Wilcox compressibility correction, this model is recommended for the problems discussed.

The developed methodology can be regarded as a basis for numerical investigations of more complex nozzle flows.