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The effectiveness of communication and data transmission systems (CSiPS), which are an integral part of modern systems in almost any field of science and technology, largely depends on the stability of the frequency of the generated signals. The signals generated in the CSiPD can be considered as processes, the frequency of which changes under the influence of a combination of external influences. Changing the frequency of the signals leads to a decrease in the signal-tonoise ratio (SNR) and, consequently, a deterioration in the characteristics of the signal-to-noise ratio, such as the probability of a bit error and bandwidth. It is most convenient to consider the description of such changes in the frequency of signals as random processes, the apparatus of which is widely used in the construction of mathematical models describing the functioning of systems and devices in various fields of science and technology. Moreover, in many cases, the characteristics of a random process, such as the distribution law, mathematical expectation, and variance, may be unknown or known with errors that do not allow us to obtain estimates of the signal parameters that are acceptable in accuracy. The article proposes an algorithm for solving the problem of determining the characteristics of a random process (signal frequency) based on a set of samples of its frequency, allowing to determine the sample mean, sample variance and the distribution law of frequency deviations in the general population. The basis of this algorithm is the comparison of the values of the observed random process measured over a certain time interval with a set of the same number of random values formed on the basis of model distribution laws. Distribution laws based on mathematical models of these systems and devices or corresponding to similar systems and devices can be considered as model distribution laws. When forming a set of random values for the accepted model distribution law, the sample mean value and variance obtained from the measurement results of the observed random process are used as mathematical expectation and variance. The feature of the algorithm is to compare the measured values of the observed random process ordered in ascending or descending order and the generated sets of values in accordance with the accepted models of distribution laws. The results of mathematical modeling illustrating the application of this algorithm are presented.

The possibilities of cellular automata simulation applied to herbs and dwarf shrubs are described. Basicprinciples of discrete description of the ontogenesis of plants on which the mathematical modeling based are presents. The review discusses the main research results obtained with the use of models that revealing the patterns of functioning of populations and communities. The CAMPUS model and the results of computer experiment to study the growth of two clones of lingonberry with different geometry of the shoots are described. The paper is dedicated to the works of the founder of the direction of prof. A. S. Komarov. A list of his major publications on this subject is given.

We consider an application of the Message Passing Interface (MPI) technology for parallelization of the program code which solves equation of the linear elasticity theory. The solution of this equation describes the propagation of elastic waves in demormable rigid bodies. The solution of such direct problem of seismic wave propagation is of interest in seismics and geophysics. Our implementation of solver uses grid-characteristic method to make simulations. We consider technique to reduce time of communication between MPI processes during the simulation. This is important when it is necessary to conduct modeling in complex problem formulations, and still maintain the high level of parallelism effectiveness, even when thousands of processes are used. A solution of the problem of effective communication is extremely important when several computational grids with arbirtrary geometry of contacts between them are used in the calculation. The complexity of this task increases if an independent distribution of the grid nodes between processes is allowed. In this paper, a generalized approach is developed for processing contact conditions in terms of nodes reinterpolation from a given section of one grid to a certain area of the second grid. An efficient way of parallelization and establishing effective interprocess communications is proposed. For provided example problems we provide wave fileds and seismograms for both 2D and 3D formulations. It is shown that the algorithm can be realized both on Cartesian and on structured (curvilinear) computational grids. The considered statements demonstrate the possibility of carrying out calculations taking into account the surface topographies and curvilinear geometry of curvilinear contacts between the geological layers. Application of curvilinear grids allows to obtain more accurate results than when calculating only using Cartesian grids. The resulting parallelization efficiency is almost 100% up to 4096 processes (we used 128 processes as a basis to find efficiency). With number of processes larger than 4096, an expected gradual decrease in efficiency is observed. The rate of decline is not great, so at 16384 processes the parallelization efficiency remains at 80%.

We propose a three-component discrete-time model of the phytoplankton-zooplankton community, in which toxic and non-toxic species of phytoplankton compete for resources. The use of the Holling functional response of type II allows us to describe an interaction between zooplankton and phytoplankton. With the Ricker competition model, we describe the restriction of phytoplankton biomass growth by the availability of external resources (mineral nutrition, oxygen, light, etc.). Many phytoplankton species, including diatom algae, are known not to release toxins if they are not damaged. Zooplankton pressure on phytoplankton decreases in the presence of toxic substances. For example, Copepods are selective in their food choices and avoid consuming toxin-producing phytoplankton. Therefore, in our model, zooplankton (predator) consumes only non-toxic phytoplankton species being prey, and toxic species phytoplankton only competes with non-toxic for resources.

We study analytically and numerically the proposed model. Dynamic mode maps allow us to investigate stability domains of fixed points, bifurcations, and the evolution of the community. Stability loss of fixed points is shown to occur only through a cascade of period-doubling bifurcations. The Neimark – Sacker scenario leading to the appearance of quasiperiodic oscillations is found to realize as well. Changes in intrapopulation parameters of phytoplankton or zooplankton can lead to abrupt transitions from regular to quasi-periodic dynamics (according to the Neimark – Sacker scenario) and further to cycles with a short period or even stationary dynamics. In the multistability areas, an initial condition variation with the unchanged values of all model parameters can shift the current dynamic mode or/and community composition.

The proposed discrete-time model of community is quite simple and reveals dynamics of interacting species that coincide with features of experimental dynamics. In particular, the system shows behavior like in prey-predator models without evolution: the predator fluctuations lag behind those of prey by about a quarter of the period. Considering the phytoplankton genetic heterogeneity, in the simplest case of two genetically different forms: toxic and non-toxic ones, allows the model to demonstrate both long-period antiphase oscillations of predator and prey and cryptic cycles. During the cryptic cycle, the prey density remains almost constant with fluctuating predators, which corresponds to the influence of rapid evolution masking the trophic interaction.

Bistability is a fundamental property of nonlinear systems and is found in many applied and theoretical studies of biological systems (populations and communities). In the simplest case it is expressed in the coexistence of diametrically opposed alternative stable equilibrium states of the system, and which of them will be achieved depends on the initial conditions. Bistability in simple models can lead to quad-stability as models become more complex, for example, when adding genetic, age and spatial structure. This occurs in different models from completely different subject area and leads to very interesting, often counterintuitive conclusions. In this article, we review such situations. The paper deals with bifurcations leading to bi- and quad-stability in mathematical models of the following biological objects. The first one is the system of two populations coupled by migration and under the action of natural selection, in which all genetic diversity is associated with a single diallelic locus with a significant difference in fitness for homo- and heterozygotes. The second is the system of two limited populations described by the Bazykin model or the Ricker model and coupled by migration. The third is a population with two age stages and density-dependent regulation of birth rate which is determined either only by population density, or additionally depends on the genetic structure of adjacent generations. We found that all these models have similar scenarios for the birth of equilibrium states that correspond to the formation of spatiotemporal inhomogeneity or to the differentiation by phenotypes of individuals from different age stages. Such inhomogeneity is a consequence of local bistability and appears as a result of a combination of pitchfork bifurcation (period doubling) and saddle-node bifurcation.

We developed a model of honeybee colony foraging based on reaction – diffusion equations. Employed bees transmit information about their food sources using dance, and job seekers in the hive can choose any dance they like and thus join the exploitation of the corresponding source. We consider two strategies of dance selection: a targeted one, when bees analyze information on the dance floor and choose the most energetic and longest dance corresponding to the most profitable source, and a simple random choice of the first dance they encounter. Modelling showed that the greatest profit (food influx into the hive) is provided by the random choice of dance, as paradoxical as it may seem at first glance. Optimization of profit by each agent for itself (targeted choice of dances) is rather a disadvantage for the colony, and “non-optimality” in dance choice can be the result of useful evolutionary adaptation.

Langevin Dynamics, Monte Carlo, and all-atom Molecular Dynamics simulations in implicit solvent require a reliable source of pseudorandom numbers generated at each step of calculation. We present the two main approaches for implementation of pseudorandom number generators on a GPU. In the first approach, inherent in CPU-based calculations, one PRNG produces a stream of pseudorandom numbers in each thread of execution, whereas the second approach builds on the ability of different threads to communicate, thus, sharing random seeds across the entire device. We exemplify the use of these approaches through the development of Ran2, Hybrid Taus, and Lagged Fibonacci algorithms. As an application-based test of randomness, we carry out LD simulations of N independent harmonic oscillators coupled to a stochastic thermostat. This model allows us to assess statistical quality of pseudorandom numbers. We also profile performance of these generators in terms of the computational time, memory usage, and the speedup factor (CPU/GPU time).

А new cloud center of parallel computing is to be created in the Laboratory of Information Technologies (LIT) of the Joint Institute for Nuclear Research JINR) what is expected to improve significantly the efficiency of numerical calculations and expedite the receipt of new physically meaningful results due to the more rational use of computing resources. To optimize a scheme of parallel computations at a cloud environment it is necessary to test this scheme for various combinations of equipment parameters (processor speed and numbers, throughput оf а communication network etc). As a test problem, the parallel MPI algorithm for calculations of the long Josephson junctions (LDJ) is chosen. Problems of evaluating the impact of abovementioned factors of computing mean on the computing speed of the test problem are solved by simulation with the simulation program SyMSim developed in LIT.

The simulation of the LDJ calculations in the cloud environment enable users without a series of test to find the optimal number of CPUs with a certain type of network run the calculations in a real computer environment. This can save significant computational time in countable resources. The main parameters of the model were obtained from the results of the computational experiment conducted on a special cloud-based testbed. Computational experiments showed that the pure computation time decreases in inverse proportion to the number of processors, but depends significantly on network bandwidth. Comparison of results obtained empirically with the results of simulation showed that the simulation model correctly simulates the parallel calculations performed using the MPI-technology. Besides it confirms our recommendation: for fast calculations of this type it is needed to increase both, — the number of CPUs and the network throughput at the same time. The simulation results allow also to invent an empirical analytical formula expressing the dependence of calculation time by the number of processors for a fixed system configuration. The obtained formula can be applied to other similar studies, but requires additional tests to determine the values of variables.

The review and systematization of current papers on the mathematical modeling of population dynamics allow us to conclude the key interests of authors are two or three main research lines related to the description and analysis of the dynamics of both local structured populations and systems of interacting homogeneous populations as ecological community in physical space. The paper reviews and systematizes scientific studies and results obtained within the framework of dynamics of structured and interacting populations to date. The paper describes the scientific idea progress in the direction of complicating models from the classical Malthus model to the modern models with various factors affecting population dynamics in the issues dealing with modeling the local population size dynamics. In particular, they consider the dynamic effects that arise as a result of taking into account the environmental capacity, density-dependent regulation, the Allee effect, complexity of an age and a stage structures. Particular attention is paid to the multistability of population dynamics. In addition, studies analyzing harvest effect on structured population dynamics and an appearance of the hydra effect are presented. The studies dealing with an appearance and development of spatial dissipative structures in both spatially separated populations and communities with migrations are discussed. Here, special attention is also paid to the frequency and phase multistability of population dynamics, as well as to an appearance of spatial clusters. During the systematization and review of articles on modeling the interacting population dynamics, the focus is on the “prey–predator” community. The key idea and approaches used in current mathematical biology to model a “prey–predator” system with community structure and harvesting are presented. The problems of an appearance and stability of the mosaic structure in communities distributed spatially and coupled by migration are also briefly discussed.

A model of biogeochemical cycles for nutrient transformation in the ecosystem of a water body has been developed using the example of the Lake Teletskoye (TL) to assess its assimilation potential in the absence of direct measurements for total nitrogen and phosphorus concentrations, instead of which the corresponding simulated data. The validity is justified by checking the adequacy of the simulation results to the data of average monthly long-term observations for all variables of the state for model. The model was calibrated with taking into account data from observations of water quality in 1985–2003, as well as a scenario version of the hydrological regime in 2016. The analysis of the intra-annual changeability of state variables, nitrogen and phosphorus inputs and outputs in TL water is given. The preliminary values of the permissible load N and P on the lake is accessed. The model analysis showed that the lake has practically no assimilation potential with respect to phosphorus compounds. The corresponding values of concentrations are equal to: P_tot. = 0.013 gP/m³, which is equal to the average annual content over the period of 18-year observations. The threshold content of N_tot. = 0.895 gN/m³. The assimilation potential for nitrogen is small, within the second significant digit after the decimal point, bearing in mind that its simulated average annual value is 0.836 gN/m³. The results of simulation indicate that the TL waters, due to the low water temperatures, along with their unique purity, differ in an extremely poorly developed community of hydrobionts. In the case of other lakes, the increase of anthropogenic pressure could be mitigated by utilization due to the vital activity of sufficiently developed hydrobionts communities. Here, there is no sufficient self-purification resource, and a relatively small increase in anthropogenic load can lead to a violation of the sustainability.