All issues

At present modern quantum technologies can get a new twist of development, which will certainly give an opportunity to obtain solutions for numerous problems that previously could not be solved in the framework of “traditional” paradigms and computational models. All mankind stands at the threshold of the so-called “second quantum revolution”, and its short-term and long-term consequences will affect virtually all spheres of life of a global society. Such directions and branches of science and technology as materials science, nanotechnology, pharmacology and biochemistry in general, modeling of chaotic dynamic processes (nuclear explosions, turbulent flows, weather and long-term climatic phenomena), etc. will be directly developed, as well as the solution of any problems, which reduce to the multiplication of matrices of large dimensions (in particular, the modeling of quantum systems). However, along with extraordinary opportunities, quantum technologies carry with them certain risks and threats, in particular, the scrapping of all information systems based on modern achievements in cryptography, which will entail almost complete destruction of secrecy, the global financial crisis due to the destruction of the banking sector and compromise of all communication channels. Even in spite of the fact that methods of so-called “post-quantum” cryptography are already being developed today, some risks still need to be realized, since not all long-term consequences can be calculated. At the same time, one should be prepared to all of the above, including by training specialists working in the field of quantum technologies and understanding all their aspects, new opportunities, risks and threats. In this connection, this article briefly describes the current state of quantum technologies, namely, quantum sensorics, information transfer using quantum protocols, a universal quantum computer (hardware), and quantum computations based on quantum algorithms (software). For all of the above, forecasts are given for the development of the impact on various areas of human civilization.

The results of verification carried out for investigations of hydrodynamic effect on reentry conicalsegmental space vehicle are presented in the paper. The program complex Flow Vision is used for this analysis. The purpose of the study is verification of using Flow Vision program complex for problem solving mentioned above on the base of comparison between calculated and experimental data, obtained on the Apollo landing models and new development reentry spacecraft of manned transporting spaceship designed by RSC Energia. The comparison was carried out through the data of pressure values on spacecraft model surfaces during its water landing and inertia center motion parameters.

The results of study show good agreement between experimental and calculated data of force effects on vehicle construction during water landing and its motion parameters in the water medium. Computer simulation sufficiently well reproduces influence of initial velocities & water entry angles variations on water landing process.

Using of computer simulation provides simultaneous acquisition of all data information needed for investigation of water landing peculiarities during construction design, notably, hydrodynamic effects for structural strength calculations, parameters and dynamics of center mass motion and vehicle revolution around center mass for estimation water landing conditions, as well as vehicle stability after landing.

Obtained results confirm suitability of using Flow Vision program complex for water landing vehicle investigations and investigations of influence of different landing regimes through wide initial condition change range, that permits considerably decrease extent of expensive experimental tests and realize landing conditions which are sufficiently complicated for realizing in model physical experiments.

Ultrasound examination of material properties is a precision method for determining their elastic and strength properties in connection with the small wavelength formed in the material after impact of a laser beam. In this paper, the wave processes arising during these measurements are considered in detail. It is shown that full-wave numerical modeling allows us to study in detail the types of waves, topological characteristics of their profile, speed of arrival of waves at various points, identification the types of waves whose measurements are most optimal for examining a sample made of a specific material of a particular shape, and to develop measurement procedures.

To carry out full-wave modeling, a grid-characteristic method on structured grids was used in this work and a hyperbolic system of equations that describes the propagation of elastic waves in the material of the thin plate under consideration on a specific example of a ratio of thickness to width of 1:10 was solved.

To simulate an elastic front that arose in the plate due to a laser beam, a model of the corresponding initial conditions was proposed. A comparison of the wave effects that arise during its use in the case of a point source and with the data of physical experiments on the propagation of laser ultrasound in metal plates was made.

A study was made on the basis of which the characteristic topological features of the wave processes under consideration were identified and revealed. The main types of elastic waves arising due to a laser beam are investigated, the possibility of their use for studying the properties of materials is analyzed. A method based on the analysis of multiple waves is proposed. The proposed method for studying the properties of a plate with the help of multiple waves on synthetic data was tested, and it showed good results.

It should be noted that most of the studies of multiple waves are aimed at developing methods for their suppression. Multiple waves are not used to process the results of ultrasound studies due to the complexity of their detection in the recorded data of a physical experiment.

Due to the use of full wave modeling and analysis of spatial dynamic wave processes, multiple waves are considered in detail in this work and it is proposed to divide materials into three classes, which allows using multiple waves to obtain information about the material of the plate.

The main results of the work are the developed problem statements for the numerical simulation of the study of plates of a finite thickness by laser ultrasound; the revealed features of the wave phenomena arising in plates of a finite thickness; the developed method for studying the properties of the plate on the basis of multiple waves; the developed classification of materials.

The results of the studies presented in this paper may be of interest not only for developments in the field of ultrasonic non-destructive testing, but also in the field of seismic exploration of the earth's interior, since the proposed approach can be extended to more complex cases of heterogeneous media and applied in geophysics.

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.

Investigation of logical deterministic cellular automata models of population dynamics allows to reveal detailed individual-based mechanisms. The search for such mechanisms is important in connection with ecological problems caused by overexploitation of natural resources, environmental pollution and climate change. Classical models of population dynamics have the phenomenological nature, as they are “black boxes”. Phenomenological models fundamentally complicate research of detailed mechanisms of ecosystem functioning. We have investigated the role of fecundity and duration of resources regeneration in mechanisms of population growth using four models of ecosystem with one species. These models are logical deterministic cellular automata and are based on physical axiomatics of excitable medium with regeneration. We have modeled catastrophic death of population arising from increasing of resources regeneration duration. It has been shown that greater fecundity accelerates population extinction. The investigated mechanisms are important for understanding mechanisms of sustainability of ecosystems and biodiversity conservation. Prospects of the presented modeling approach as a method of transparent multilevel modeling of complex systems are discussed.

The paper has a goal to identify a set of parameters of the environment and infrastructure with the most significant impact on institutional-matrices that dominate in different countries. Parameters of environmental conditions includes raw statistical indices, which were directly derived from the databases of open access, as well as complex integral indicators that were by method of principal components. Efficiency of discussed parameters in task of dominant institutional matrices type recognition (X or Y type) was evaluated by a number of methods based on machine learning. It was revealed that greatest informational content is associated with parameters characterizing risk of natural disasters, level of urbanization and the development of transport infrastructure, the monthly averages and seasonal variations of temperature and precipitation.

A previously developed model that describes the dynamics of social tension in a society divided into two groups: the elite and the people was considered. This model took into account the impact of economic situation changes and the elite–people interaction. The model has been modified by including in the equation describing the tension of the people, a term that takes into account the adaptation of the people to the current situation.

The model coefficients estimation is an important task, the solution of which allows obtaining information about the nature of the interaction between elite and people. We believe that the solution of the system of model equations with optimal coefficients is closest to the values of the indicator characterizing social tension. We used the normalized level of homicide rate as an indicator of social tension.

The model contains seven coefficients. Two coefficients characterizing the influence of economic situation changes on elite and people are taken equal to each other and the same for all countries. We obtained their estimations using a simplified model that takes into account only the change in the economic situation and allows an analytical solution.

The Bayesian approach was used to estimate the remaining five coefficients of model for post-Soviet countries. The prior probability densities of the four coefficients for all countries under consideration were taken to be the same. The prior probability density of fifth coefficient was considered to depend on the regime of government (authoritarian or «transitional»). We assumed that the calculated tension matches with the corresponding indicator of tension in cases where the difference between them does not exceed 5%.

The calculations showed that for the post-Soviet countries, a good coincidence was obtained between the calculated values of the people tension and the normalized level of homicide rate. The coincidence is satisfactory only on average.

The following main results was obtained at the work: under the influence of some «significant» events in 40% of post-Soviet countries, there was a rapid change in the nature of interaction between the elite and the people; regional feature have some influence on the elite–people interaction; the type of government does not significantly affect the elite–people interaction; the method for assessing the stability of the country by the value of the model coefficients is proposed.

The article deals with the development of a methodological approach to forecasting and modeling the socioeconomic consequences of viral epidemics in conditions of heterogeneous economic development of territorial systems. The relevance of the research stems from the need for rapid mechanisms of public management and stabilization of adverse epidemiological situation, taking into account the spatial heterogeneity of the spread of COVID-19, accompanied by a concentration of infection in large metropolitan areas and territories with high economic activity. The aim of the work is to substantiate a methodology to assess the spatial heterogeneity of the spread of coronavirus infection, find poles of its growth, emerging spatial clusters and zones of their influence with the assessment of inter-territorial relationships, as well as simulate the effects of worsening epidemiological situation on the dynamics of economic development of regional systems. The peculiarity of the developed approach is the spatial clustering of regional systems by the level of COVID-19 incidence, conducted using global and local spatial autocorrelation indices, various spatial weight matrices, and L.Anselin mutual influence matrix based on the statistical information of the Russian Federal State Statistics Service. The study revealed a spatial cluster characterized by high levels of infection with COVID-19 with a strong zone of influence and stable interregional relationships with surrounding regions, as well as formed growth poles which are potential poles of further spread of coronavirus infection. Regression analysis using panel data not only confirmed the impact of COVID-19 incidence on the average number of employees in enterprises, the level of average monthly nominal wages, but also allowed to form a model for scenario prediction of the consequences of the spread of coronavirus infection. The results of this study can be used to form mechanisms to contain the coronavirus infection and stabilize socio-economic at macroeconomic and regional level and restore the economy of territorial systems, depending on the depth of the spread of infection and the level of economic damage caused.

In the first section of the paper a definition of presentation (perception) functions — components of individual’s subjective view of the world — are proposed. Using the basic psychophysical law formulated by S. Stevens, and relying on the hypotheses of socialization, rationality, individual choice, complexity of informational influences, dynamics of ideas and perceptions, and accessibility, formal dependence was derived allowing to calculate the function of presentation (perception) for probabilistic indicators (with known distribution function or subjective probability) and of interval type. In the second and third sections parameters of the presentation function according to surveys of the U.S. population related to the war in Korea, Vietnam, and Iraq are estimated.

In the present article we explore the process of changing the level of approval of a political leader under the influence of the processes taking place in online platforms (social networks, forums, etc.). The driver of these changes is the interaction of users, through which they can exchange opinions with each other and formulate their position in relation to the political leader. In addition to interpersonal interaction, we will consider such factors as the information impact, expressed in the creation of an information flow with a given power and polarity (positive or negative, in the context of influencing the image of a political leader), as well as the presence of a group of agents (opinion leaders), supporting the leader, or, conversely, negatively affecting its representation in the media space.

The mathematical basis of the presented research is the Kirman model, which has its roots in biology and initially found its application in economics. Within the framework of this model it is considered that each user is in one of the two possible states, and a Markov jump process describing transitions between these states is given. For the problem under consideration, these states are 0 or 1, depending on whether a particular agent is a supporter of a political leader or not. For further research, we find its diffusional approximation, known as the Jacoby process. With the help of spectral decomposition for the infinitesimal operator of this process we have an opportunity to find an analytical representation for the transition probability density.

Analyzing the probabilities obtained in this way, we can assess the influence of individual factors of the model: the power and direction of the information flow, available to online users and relevant to the tasks of rating formation, as well as the number of supporters or opponents of the politician. Next, using the found eigenfunctions and eigenvalues, we derive expressions for the evaluation of conditional mathematical expectations of a politician’s rating, which can serve as a basis for building forecasts that are important for the formation of a strategy of representing a political leader in the online environment.