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EN
Chaotic dynamics and routes to chaos of domain walls in magnetic bub­ble garnet materials in the presence of in-plane fields were investigated nu­merically using Slonczewski's equations of motion. Connection between the structure of the wall and the character of the attractor was found. The in-plane field can play a role of the factor controlling chaos.
EN
The motion of domain walls in thin garnet films was investigated numerically using Slonczewski's equations of wall motion for the case of periodic drive field. The type of the wall motion was analyzed by observation of phase trajectories and spatio-temporal diagrams. It was found that depending on the period and amplitude of the drive field the motion of the wall is periodic or chaotic, reflecting the character of the dynamical processes connected with horizontal Bloch lines in the wall.
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The SIRS Model of Epidemic Spreading in Virtual Society

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EN
The phenomenon of epidemic spreading in a real social network is described and investigated numerically. On the basis of data concerning amount of time devoted daily to social interactions, the influence of human activity on spreading process is investigated in the frame of SIRS model. It was found that the activity of an individual is positively correlated with its connectivity and the relation has power law form. The influence of control measures on the spreading process is investigated as a function of initial conditions. The cost-effectiveness of mass immunizations campaigns and target vaccinations is compared. It was found that the form of activity distribution has significant influence on the spreading phenomena in the network.
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EN
We propose a model of elections based on the Sznajd model of social interactions in the stochastic Ravasz-Barabási hierarchical network. The results of numerical calculations for the population described by this model were compared with statistical analysis of elections' results to the lower house of Parliament held in Poland in the years of 2001, 2005 and 2007. It is shown that the distribution of votes among candidates for the whole country as well as for the district of Warsaw has the log-normal character. The results from Poland are compared with other countries: Brazil and India. For all the cases log-normal distribution of votes for the candidates from each political party is shown. The probability of gaining a number of votes as a function of the number of the candidate on the list is presented.
EN
A quantitative analysis of spatio-temporal diagrams, which describe the dynamics of a chosen, spatially extended dynamic system (a domain wall in a thin magnetic garnet film) is presented. Two quantifiers characterizing such diagrams - a correlation function and power spectrum density function - were calculated using solutions of equations of motion. It was found that introducing these quantifiers to the analysis of spatio-temporal diagrams enables one to effectively characterize the type and the properties of motion of the considered system.
EN
Dynamics of a neural network in the form of a linear chain of artificial neurons S_i∈(-1,1) influenced by an external sinusoidal stimulation is investigated as a function of the range k of synaptic connections with random values. Time evolution of the network is periodic for small k, however, clusters of neurons oscillating with a triple period of external stimulation, with quasiperiodic or with chaotic time evolution may occur. For increasing k the number and width of the chaotic clusters increase and for k >4 the chaotic motion occurs in the whole network. A route to chaos in the considered system is discussed.
EN
The route to chaos of domain wall in thin magnetic film, which is described by Słonczewski's equations of motion, is analyzed numerically. Hagedorn's model of surface stray field is applied. Ranges of periodic and chaotic wall motion as a function of constant in time, drive field are found. Comparison of results with those obtained for Hubert's model of the stray field is made.
EN
In the paper thermodynamic properties of an artificial neural network are analyzed in a way analogous to spin glasses theory. Synaptic connections are calculated numerically according to the Hebb rule and their distribution is obtained for different characteristics of stored patterns. The phase diagrams and magnetization are established in dependence on the temperature of the network and the external field (threshold). It was showed that changing control parameters typical of artificial neural network (i.e. number of stored patterns and pattern bias level) one obtains the results similar to the Sherrington-Kirkpatrick model of spin glass.
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