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Elisabetta Candellero

Publications and source records attributed to Elisabetta Candellero.

14 recordsLinked to original sources

First Passage Percolation with Recovery

First passage percolation with recovery is a process aimed at modeling the spread of epidemics. On a graph $G$ place a red particle at a reference vertex $o$ and colorless particles (seeds) at all other vertices. The red particle starts spreading a \emph{red first passage percolation} of rate $1$, while all seeds are dormant. As soon as a seed is reached by the process, it turns red and starts spreading {red first passage percolation}. All vertices are equipped with independent exponential clocks ringing at rate $γ>0$, when a clock rings the corresponding \emph{red vertex turns black}. For $t\geq 0$, let $H_t$ and $M_t$ denote the size of the longest red path and of the largest red cluster present at time $t$. %, respectively. If $G$ is the semi-line, then for all $γ>0$ almost surely $\limsup_{t}\frac{H_t\log\log t}{\log t}=1 $ and $\liminf_{t}H_t=0$. In contrast, if $G$ is an infinite Galton-Watson tree with offspring mean $\mathbf{m}>1$ then, for all $γ>0$, almost surely $\liminf_{t}\frac{H_t\log t}{t}\geq\mathbf{m}-1 $ and $\liminf_{t}\frac{M_t\log\log t}{t}\geq \mathbf{m}-1$, while $\limsup_{t} \frac{M_t}{e^{c t}}\leq 1$, for all $c>\mathbf{m} -1$. Also, almost surely as $t\to \infty$, for all $γ>0$ $H_t$ is of order at most $t$. Furthermore, if we restrict our attention to bounded-degree graphs, then for any $\varepsilon>0$ there is a critical value $γ_c>0$ so that for all $γ>γ_c$, almost surely $\limsup_{t}\frac{M_t}{t}\leq \varepsilon $.

math.PR

Martin boundaries and asymptotic behavior of branching random walks

Let $G$ be an infinite, locally finite graph. We investigate the relation between supercritical, transient branching random walk and the Martin boundary of its underlying random walk. We show results regarding the typical asymptotic directions taken by the particles, and as a consequence we find a new connection between $t$-Martin boundaries and standard Martin boundaries. Moreover, given a subgraph $U$ we study two aspects of branching random walks on $U$: when the trajectories visit $U$ infinitely often (survival) and when they stay inside $U$ forever (persistence). We show that there are cases, when $U$ is not connected, where the branching random walk does not survive in $U$, but the random walk on $G$ converges to the boundary of $U$ with positive probability. In contrast, the branching random walk can survive in $U$ even though the random walk eventually exits $U$ almost surely. We provide several examples and counterexamples.

math.PR

First passage percolation in hostile environment is not monotone

We study a natural growth process with competition, modeled by two first passage percolation processes, $FPP_1$ and $FPP_λ$, spreading on a graph. $FPP_1$ starts at the origin and spreads at rate $1$, whereas $FPP_λ$ starts from a random set of \emph{inactive seeds} distributed as Bernoulli percolation of parameter $μ\in (0,1)$. A seed of $FPP_λ$ gets activated when one of the two processes attempts to occupy its location, and from this moment onwards spreads at some fixed rate $λ>0$. In previous works~[17, 3, 7] it has been shown that when both $μ$ or $λ$ are small enough, then $FPP_1$ \emph{survives} (i.e., it occupies an infinite set of vertices) with positive probability. It might seem intuitive that decreasing $μ$ or $λ$ is beneficial to $FPP_1$. However, we prove that, in general, this is indeed false by constructing a graph for which the probability that $FPP_1$ survives is not a monotone function of $μ$ or $λ$, implying the existence of multiple phase transitions. This behavior contrasts with other natural growth processes such as the $2$-type Richardson model.

math.PR

On the boundary at infinity for branching random walk

We prove that supercritical branching random walk on a transient graph converges almost surely under rescaling to a random measure on the Martin boundary of the graph. Several open problems and conjectures about this limiting measure are presented.

math.PR

The number of ends of critical branching random walks

We investigate the number of topological ends of the trace of branching random walk (BRW) on a graph, giving a sufficient condition for the trace to have infinitely many ends. We then describe some interesting examples of non-symmetric BRWs with just one end.

math.PR

Coexistence of competing first passage percolation on hyperbolic graphs

We study a natural growth process with competition, which was recently introduced to analyze MDLA, a challenging model for the growth of an aggregate by diffusing particles. The growth process consists of two first-passage percolation processes $\text{FPP}_1$ and $\text{FPP}_λ$, spreading with rates $1$ and $λ>0$ respectively, on a graph $G$. $\text{FPP}_1$ starts from a single vertex at the origin $o$, while the initial configuration of $\text{FPP}_λ$ consists of infinitely many \emph{seeds} distributed according to a product of Bernoulli measures of parameter $μ>0$ on $V(G)\setminus \{o\}$. $\text{FPP}_1$ starts spreading from time 0, while each seed of $\text{FPP}_λ$ only starts spreading after it has been reached by either $\text{FPP}_1$ or $\text{FPP}_λ$. A fundamental question in this model, and in growth processes with competition in general, is whether the two processes coexist (i.e., both produce infinite clusters) with positive probability. We show that this is the case when $G$ is vertex transitive, non-amenable and hyperbolic, in particular, for any $λ>0$ there is a $μ_0=μ_0(G,λ)>0$ such that for all $μ\in(0,μ_0)$ the two processes coexist with positive probability. This is the first non-trivial instance where coexistence is established for this model. We also show that $\text{FPP}_λ$ produces an infinite cluster almost surely for any positive $λ,μ$, establishing fundamental differences with the behavior of such processes on $\mathbb{Z}^d$.

math.PR

Abelian oil and water dynamics does not have an absorbing-state phase transition

The oil and water model is an interacting particle system with two types of particles and a dynamics that conserves the number of particles, which belongs to the so-called class of Abelian networks. Widely studied processes in this class are sandpiles models and activated random walks, which are known (at least for some choice of the underlying graph) to undergo an absorbing-state phase transition. This phase transition characterizes the existence of two regimes, depending on the particle density: a regime of fixation at low densities, where the dynamics converges towards an absorbing state and each particle jumps only finitely many times, and a regime of activity at large densities, where particles jump infinitely often and activity is sustained indefinitely. In this work we show that the oil and water model is substantially different than sandpiles models and activated random walks, in the sense that it does not undergo an absorbing-state phase transition and is in the regime of fixation at all densities. Our result works in great generality: for any graph that is vertex transitive and for a large class of initial configurations.

math.PR

Percolation and isoperimetry on roughly transitive graphs

In this paper we study percolation on a roughly transitive graph G with polynomial growth and isoperimetric dimension larger than one. For these graphs we are able to prove that p_c < 1, or in other words, that there exists a percolation phase. The main results of the article work for both dependent and independent percolation processes, since they are based on a quite robust renormalization technique. When G is transitive, the fact that p_c < 1 was already known before. But even in that case our proof yields some new results and it is entirely probabilistic, not involving the use of Gromov's theorem on groups of polynomial growth. We finish the paper giving some examples of dependent percolation for which our results apply.

math.PR

Coupling of Brownian motions in Banach spaces

Consider a separable Banach space $ \mathcal{W}$ supporting a non-trivial Gaussian measure $μ$. The following is an immediate consequence of the theory of Gaussian measure on Banach spaces: there exist (almost surely) successful couplings of two $\mathcal{W}$-valued Brownian motions $ \mathbf{B}$ and $\widetilde{\mathbf{B}}$ begun at starting points $\mathbf{B}(0)$ and $\widetilde{\mathbf{B}}(0)$ if and only if the difference $\mathbf{B}(0)-\widetilde{\mathbf{B}}(0)$ of their initial positions belongs to the Cameron-Martin space $\mathcal{H}_μ $ of $\mathcal{W}$ corresponding to $μ$. For more general starting points, can there be a "coupling at time $\infty$", such that almost surely $\|\mathbf{B}(t)-\widetilde{\mathbf{B}}(t)\|_{\mathcal{W}} \to 0$ as $t\to\infty$? Such couplings exist if there exists a Schauder basis of $ \mathcal{W}$ which is also a $\mathcal{H}_μ $-orthonormal basis of $\mathcal{H}_μ $. We propose (and discuss some partial answers to) the question, to what extent can one express the probabilistic Banach space property "Brownian coupling at time $\infty$ is always possible" purely in terms of Banach space geometry?

math.PR

Bootstrap percolation and the geometry of complex networks

On a geometric model for complex networks (introduced by Krioukov et al.) we investigate the bootstrap percolation process. This model consists of random geometric graphs on the hyperbolic plane having $N$ vertices, a dependent version of the Chung-Lu model. The process starts with infection rate $p=p(N)$. Each uninfected vertex with at least $\mathbf{r}\geq 1$ infected neighbors becomes infected, remaining so forever. We identify a function $p_c(N)=o(1)$ such that a.a.s.\ when $p\gg p_c(N)$ the infection spreads to a positive fraction of vertices, whereas when $p\ll p_c(N)$ the process cannot evolve. Moreover, this behavior is "robust" under random deletions of edges.

math.PR

Clustering and the hyperbolic geometry of complex networks

Clustering is a fundamental property of complex networks and it is the mathematical expression of a ubiquitous phenomenon that arises in various types of self-organized networks such as biological networks, computer networks or social networks. In this paper, we consider what is called the global clustering coefficient of random graphs on the hyperbolic plane. This model of random graphs was proposed recently by Krioukov et al. as a mathematical model of complex networks, under the fundamental assumption that hyperbolic geometry underlies the structure of these networks. We give a rigorous analysis of clustering and characterize the global clustering coefficient in terms of the parameters of the model. We show how the global clustering coefficient can be tuned by these parameters and we give an explicit formula for this function.

math.PR

Oil and water: a two-type internal aggregation model

We introduce a two-type internal DLA model which is an example of a non-unary abelian network. Starting with n "oil" and n "water" particles at the origin, the particles diffuse in Z according to the following rule: whenever some site x has at least 1 oil and at least 1 water particle present, it "fires" by sending 1 oil particle and 1 water particle each to an independent random neighbor x+1 or x-1. Firing continues until every site has at most one type of particles. We establish the correct order for several statistics of this model and identify the scaling limit under assumption of existence.

math.PR

Branching Random Walks on Free Products of Groups

We study certain phase transitions of branching random walks (BRW) on Cayley graphs of free products. The aim of this paper is to compare the size and structural properties of the trace, i.e., the subgraph that consists of all edges and vertices that were visited by some particle, with those of the original Cayley graph. We investigate the phase when the growth parameter $λ$ is small enough such that the process survives but the trace is not the original graph. A first result is that the box-counting dimension of the boundary of the trace exists, is almost surely constant and equals the Hausdorff dimension which we denote by $Φ(λ)$. The main result states that the function $Φ(λ)$ has only one point of discontinuity which is at $λ_{c}=R$ where $R$ is the radius of convergence of the Green function of the underlying random walk. Furthermore, $Φ(R)$ is bounded by one half the Hausdorff dimension of the boundary of the original Cayley graph and the behaviour of $Φ(R)-Φ(λ)$ as $λ\uparrow R$ is classified. In the case of free products of infinite groups the end-boundary can be decomposed into words of finite and words of infinite length. We prove the existence of a phase transition such that if $λ\leq \tildeλ_{c}$ the end boundary of the trace consists only of infinite words and if $λ>\tildeλ_{c}$ it also contains finite words. In the last case, the Hausdorff dimension of the set of ends (of the trace and the original graph) induced by finite words is strictly smaller than the one of the ends induced by infinite words.

math.PR

Phase Transitions for Random Walk Asymptotics on Free Products of Groups

Suppose we are given finitely generated groups $Γ_1,...,Γ_m$ equipped with irreducible random walks. Thereby we assume that the expansions of the corresponding Green functions at their radii of convergence contain only logarithmic or algebraic terms as singular terms up to sufficiently large order (except for some degenerate cases). We consider transient random walks on the free product {$Γ_1 \ast ... \astΓ_m$} and give a complete classification of the possible asymptotic behaviour of the corresponding $n$-step return probabilities. They either inherit a law of the form $\varrho^{nδ} n^{-λ_i} \log^{κ_i}n$ from one of the free factors $Γ_i$ or obey a $\varrho^{nδ} n^{-3/2}$-law, where $\varrho<1$ is the corresponding spectral radius and $δ$ is the period of the random walk. In addition, we determine the full range of the asymptotic behaviour in the case of nearest neighbour random walks on free products of the form $\Z^{d_1}\ast ... \ast \Z^{d_m}$. Moreover, we characterize the possible phase transitions of the non-exponential types $n^{-λ_i}\log^{κ_i}n$ in the case $Γ_1\astΓ_2$.

math.PR