No Arabic abstract
Cluster concepts have been extremely useful in elucidating many problems in physics. Percolation theory provides a generic framework to study the behavior of the cluster distribution. In most cases the theory predicts a geometrical transition at the percolation threshold, characterized in the percolative phase by the presence of a spanning cluster, which becomes infinite in the thermodynamic limit. Standard percolation usually deals with the problem when the constitutive elements of the clusters are randomly distributed. However correlations cannot always be neglected. In this case correlated percolation is the appropriate theory to study such systems. The origin of correlated percolation could be dated back to 1937 when Mayer [1] proposed a theory to describe the condensation from a gas to a liquid in terms of mathematical clusters (for a review of cluster theory in simple fluids see [2]). The location for the divergence of the size of these clusters was interpreted as the condensation transition from a gas to a liquid. One of the major drawback of the theory was that the cluster number for some values of thermodynamic parameters could become negative. As a consequence the clusters did not have any physical interpretation [3]. This theory was followed by Frenkels phenomenological model [4], in which the fluid was considered as made of non interacting physical clusters with a given free energy. This model was later improved by Fisher [3], who proposed a different free energy for the clusters, now called droplets, and consequently a different scaling form for the droplet size distribution. This distribution, which depends on two geometrical parameters, has the nice feature that the mean droplet size exhibits a divergence at the liquid-gas critical point.
We reconsider the problem of percolation on an equilibrium random network with degree-degree correlations between nearest-neighboring vertices focusing on critical singularities at a percolation threshold. We obtain criteria for degree-degree correlations to be irrelevant for critical singularities. We present examples of networks in which assortative and disassortative mixing leads to unusual percolation properties and new critical exponents.
We introduce a correlated static model and investigate a percolation transition. The model is a modification of the static model and is characterized by assortative degree-degree correlation. As one varies the edge density, the network undergoes a percolation transition. The percolation transition is characterized by a weak singular behavior of the mean cluster size and power-law scalings of the percolation order parameter and the cluster size distribution in the entire non-percolating phase. These results suggest that the assortative degree-degree correlation generates a global structural correlation which is relevant to the percolation critical phenomena of complex networks.
We present results of numerical and experimental investigation of the electric breakage of a cellular material in pulsed electric fields (PEF). The numerical model simulates the conductive properties of a cellular material by a two-dimensional array of biological cells. The application of an external field in the form of the idealised square pulse sequence with a pulse duration $t_{i}$, and a pulse repetition time $Delta t$ is assumed. The simulation model includes the known mechanisms of temporal and spatial evolution of the conductive properties of different microstructural elements in a tissue. The kinetics of breakage at different values of electric field strength $E$, $t_{i}$ and $Delta t$ was studied in experimental investigation. We propose the hypothesis for the nature of tissue properties evolution after PEF treatment and consider this phenomena as a correlated percolation, which is governed by two key processes: resealing of cells and moisture transfer processes inside the cellular structure. The breakage kinetics was shown to be very sensitive to the repetition times $Delta t$ of the PEF treatment. We observed correlated percolation patterns in a case when $Delta t$ exceeds the characteristic time of the processes of moisture transfer and random percolation patterns in other cases. The long-term mode of the pulse repetition times in PEF treatment allows us to visualize experimentally the macroscopic percolation channels in the sample.
A model named `Colored Percolation has been introduced with its infinite number
The recent proliferation of correlated percolation models---models where the addition of edges/vertices is no longer independent of other edges/vertices---has been motivated by the quest to find discontinuous percolation transitions. The leader in this proliferation is what is known as explosive percolation. A recent proof demonstrates that a large class of explosive percolation-type models does not, in fact, exhibit a discontinuous transition[O. Riordan and L. Warnke, Science, {bf 333}, 322 (2011)]. We, on the other hand, discuss several correlated percolation models, the $k$-core model on random graphs, and the spiral and counter-balance models in two-dimensions, all exhibiting discontinuous transitions in an effort to identify the needed ingredients for such a transition. We then construct mixtures of these models to interpolate between a continuous transition and a discontinuous transition to search for a tricritical point. Using a powerful rate equation approach, we demonstrate that a mixture of $k=2$-core and $k=3$-core vertices on the random graph exhibits a tricritical point. However, for a mixture of $k$-core and counter-balance vertices, heuristic arguments and numerics suggest that there is a line of continuous transitions as the fraction of counter-balance vertices is increased from zero with the line ending at a discontinuous transition only when all vertices are counter-balance. Our results may have potential implications for glassy systems and a recent experiment on shearing a system of frictional particles to induce what is known as jamming.