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We consider a dynamical process on a graph $G$, in which vertices are infected (randomly) at a rate which depends on the number of their neighbours that are already infected. This model includes bootstrap percolation and first-passage percolation as its extreme points. We give a precise description of the evolution of this process on the graph $mathbb{Z}^2$, significantly sharpening results of Dehghanpour and Schonmann. In particular, we determine the typical infection time up to a constant factor for almost all natural values of the parameters, and in a large range we obtain a stronger, sharp threshold.
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We study survival among two competing types in two settings: a planar growth model related to two-neighbour bootstrap percolation, and a system of urns with graph-based interactions. In the planar growth model, uncoloured sites are given a colour at rate $0$, $1$ or $infty$, depending on whether they have zero, one, or at least two neighbours of that colour. In the urn scheme, each vertex of a graph $G$ has an associated urn containing some number of either blue or red balls (but not both). At each time step, a ball is chosen uniformly at random from all those currently present in the system, a ball of the same colour is added to each neighbouring urn, and balls in the same urn but of different colours annihilate on a one-for-one basis. We show that, for every connected graph $G$ and every initial configuration, only one colour survives almost surely. As a corollary, we deduce that in the two-type growth model on $mathbb{Z}^2$, one of the colours only infects a finite number of sites with probability one. We also discuss generalisations to higher dimensions and multi-type processes, and list a number of open problems and conjectures.
We consider an evolving preferential attachment random graph model where at discrete times a new node is attached to an old node, selected with probability proportional to a superlinear function of its degree. For such schemes, it is known that the graph evolution condenses, that is a.s. in the limit graph there will be a single random node with infinite degree, while all others have finite degree. In this note, we establish a.s. law of large numbers type limits and fluctuation results, as $nuparrowinfty$, for the counts of the number of nodes with degree $kgeq 1$ at time $ngeq 1$. These limits rigorously verify and extend a physical picture of Krapivisky, Redner and Leyvraz (2000) on how the condensation arises with respect to the degree distribution.
In this article, we try to give an answer to the simple question: ``textit{What is the critical growth rate of the dimension $p$ as a function of the sample size $n$ for which the Central Limit Theorem holds uniformly over the collection of $p$-dimensional hyper-rectangles ?}. Specifically, we are interested in the normal approximation of suitably scal
Nacre is a layered, iridescent lining found inside many mollusk shells, with a unique brick-and-mortar periodic structure at the sub-micron scale, and remarkable resistance to fracture. Despite extensive studies, it remains unclear how nacre forms. Here we present 20-nm, 2{deg}-resolution Polarization-dependent Imaging Contrast (PIC) images of shells from 15 mollusk shell species, mapping nacre tablets and their orientation patterns, showing where new crystal orientations appear and how they propagate across organic sheets as nacre grows. In all shells we found stacks of co-oriented aragonite (CaCO3) tablets arranged into vertical columns or staggered diagonally. Only near the nacre-prismatic boundary are disordered crystals nucleated, as spherulitic aragonite. Overgrowing nacre tablet crystals are most frequently co-oriented with the underlying spherulitic aragonite or with another tablet, connected by mineral bridges. Therefore aragonite crystal growth in nacre is epitaxial or near-epitaxial, with abrupt or gradual changes in orientation, with c-axes within 20{deg}. Based on these data, we propose that there is one mineral bridge per tablet, and that bridge-tilting is a possible mechanism to introduce small, gradual or abrupt changes in the orientation of crystals within a stack of tablets as nacre grows.
Jigsaw percolation is a nonlocal process that iteratively merges connected clusters in a deterministic puzzle graph by using connectivity properties of a random people graph on the same set of vertices. We presume the Erdos--Renyi people graph with edge probability p and investigate the probability that the puzzle is solved, that is, that the process eventually produces a single cluster. In some generality, for puzzle graphs with N vertices of degrees about D (in the appropriate sense), this probability is close to 1 or small depending on whether pD(log N) is large or small. The one dimensional ring and two dimensional torus puzzles are studied in more detail and in many cases the exact scaling of the critical probability is obtained. The paper settles several conjectures posed by Brummitt, Chatterjee, Dey, and Sivakoff who introduced this model.
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