Influence of information flow in the formation of economic cycles

A microscopic approach to macroeconomic features is intended. A model for macroeconomic behavior based on the Ausloos-Clippe-Pekalski model is built and investigated. The influence of a discrete time information transfer is investigated. The formation of economic cycles is observed as a function of the time of information delay. Three regions of delay time are recognized: short $t_d \in (2 IS, 4 IS)$ (IS - iteration steps) - the system evolves toward a unique stable equilibrium state, medium $t_d =5 IS$ or $t_d =6 IS$, the system undergoes oscillations: stable concentration cycles appear in the system. For long information flow delay times, $t_d \geq 7$, the systems may crash for most initial concentrations. However, even in the case of long delay time the crash time may be long enough to allow observation of the system evolution and to introduce an appropriate strategy in order to avoid the collapse of the e.g. company concentration. In the long time delay it is also possible to observe an "economy resonance" where despite a long delay time the system evolves for a long time or can even reach a stable state, which insures its existence.Comment: 18 pages,16 figures, to be published in Verhulst 200 Proceedings, M. Ausloos and M. Dirickx, Eds. (in press

Delayed information flow effect in economy systems. An ACP model study

Applying any strategy requires some knowledge about the past state of the system. Unfortunately in the case of economy collecting information is a difficult, expensive and time consuming process. Therefore the information about the system is known at the end of some well defined intervals, e. g. company reports, inflation data, GDP etc. They describe a (market) situation in the past. The time delay is specific to the market branch. It can be very short (e.g. stock market offer is updated every minute or so and this information is immediately available) or long, like months in the case of agricultural market, when the decisions are taken based on the results from the previous harvest. The analysis of the information flow delay can be based on the ACP model of spatial evolution of economic systems. The entities can move on a square lattice and when meeting take one of the two following decisions: merge or create a new entity. The decision is based on the system state, which is known with some time delay. The effect of system's feedback is investigated. We consider the case of company distribution evolution in a heterogenous field. The information flow time delay implies different final states, including cycles.Comment: Presented at APFA

Electrical and thermal transport properties in high T_c superconductors : effects of a magnetic field

Experimental studies of the electric and heat currents in the normal, superconducting and mixed states of high T$_c$ superconductors (HTcS) lead to characterization, complementary to data obtained from equilibrium property based techniques. A magnetic field superimposed on the superconducting sample generates {\it magneto-transport phenomena}, from which an excess electrical resistivity, an excess thermoelectric power, the Hall or the Nernst effect. Different behavioral effects allow one to distinguish various dissipation mechanisms, like quasi particle scattering, vortex motion dissipation and superconductivity fluctuations, in particular when the Corbino geometry is used. Moreover bulk measurements of the thermal conductivity and the electrothermal conductivity in a magnetic field give us sure indications of the order parameter symmetry. The location of the mixed state phase transition lines in the technological phase diagram of HTcS are briefly pointed out through precise measurements performed over broad temperature and magnetic field ranges. The results are mainly reviewed with the aim of defining further investigation lines.Comment: 9 pages, no figures; to appear in Physica

Empirical Analysis of Time Series

Time series occur in many fields of biology, physics, chemistry, engineering. Much work has been recently performed in statistical physics using specific mathematical techniques on various time series pertaining to so-called nonlinear phenomena. Several methods, beyond the Fourier transform, are presented here. To distinguish between noise and deterministic content is the major challenge. Various phenomena are used for illustration. Some emphasis on findings and still questions will be drawn from problems in finance due to the existence (or not) of long-, medium-, short-range (power-law or not) correlations in such economic systems. The Fourier transform, the Hurst rescaled range, the instantaneous detrended fluctuations, the moving averages, and the Zipf-plots analysis methods will be recalled. They raise questions about fractional Brownian motion properties, or in sorting out correlation ranges and predictability. Among spectacular results, the possibility of crash predictions will be indicated when there is an underlying discrete scale invariance. Other time series for meteorology and electronics phenomena are also presented in order to discuss stratus cloud breaking and dielectric breakdown through avalanches for illustration purpose and to indicate that there are other widely open fields of possible investigations.time series; finance; fourier transform; Hurst exponenet; multifractal; detrended fluctuation analysis; moving average; Zipf; crashes

Magnetically controlled ballistic deposition. A model of polydisperse granular packing

The flow and deposition of polydisperse granular materials is simulated through the Magnetic Diffusion Limited Aggregation (MDLA) model. The random walk undergone by an entity in the MDLA model is modified such that the trajectories are ballistic in nature, leading to a magnetically controlled ballistic deposition (MBD) model. This allows to obtain important ingredients about a difficult problem that of the nonequilibrium segregation of polydisperse sandpiles and heterogeneous adsorption of a binary distribution of particles which can interact with each other and with an external field. Our detailed results from many simulations of MBD clusters on a two dimensional triangular lattice above a flat surface in a vertical finite size box for binary systems indicates intriguing variations of the density, ''magnetization'', types of clusters, and fractal dimensions. We derive the field and grain interaction dependent susceptibility and compressibility. We deduce a completely new phase diagram for binary granular piles and discuss its complexity inherent to different grain competition and cluster growth probabilities.Comment: 11 pages, 18 figures, submitted to Physica

A Brownian particle having a fluctuating mass

We focus on the dynamics of a Brownian particle whose mass fluctuates. First we show that the behaviour is similar to that of a Brownian particle moving in a fluctuating medium, as studied by Beck [Phys. Rev. Lett. 87 (2001) 180601]. By performing numerical simulations of the Langevin equation, we check the theoretical predictions derived in the adiabatic limit, and study deviations outside this limit. We compare the mass velocity distribution with truncated Tsallis distributions [J. Stat. Phys. 52 (1988) 479] and find excellent agreement if the masses are chi- squared distributed. We also consider the diffusion of the Brownian particle by studying a Bernoulli random walk with fluctuating walk length in one dimension. We observe the time dependence of the position distribution kurtosis and find interesting behaviours. We point out a few physical cases where the mass fluctuation problem could be encountered as a first approximation for agglomeration- fracture non equilibrium processes.Comment: submitted to PR