46 research outputs found

    Limit theorems for vertex-reinforced jump processes on regular trees

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    Consider a vertex-reinforced jump process defined on a regular tree, where each vertex has exactly bb children, with b3b \ge 3. We prove the strong law of large numbers and the central limit theorem for the distance of the process from the root. Notice that it is still unknown if vertex-reinforced jump process is transient on the binary tree.Comment: 26 pages. Accepted for publication in Electronic Journal of Probabilit

    On the transience of processes defined on Galton--Watson trees

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    We introduce a simple technique for proving the transience of certain processes defined on the random tree G\mathcal{G} generated by a supercritical branching process. We prove the transience for once-reinforced random walks on G\mathcal{G}, that is, a generalization of a result of Durrett, Kesten and Limic [Probab. Theory Related Fields 122 (2002) 567--592]. Moreover, we give a new proof for the transience of a family of biased random walks defined on G\mathcal{G}. Other proofs of this fact can be found in [Ann. Probab. 16 (1988) 1229--1241] and [Ann. Probab. 18 (1990) 931--958] as part of more general results. A similar technique is applied to a vertex-reinforced jump process. A by-product of our result is that this process is transient on the 3-ary tree. Davis and Volkov [Probab. Theory Related Fields 128 (2004) 42--62] proved that a vertex-reinforced jump process defined on the bb-ary tree is transient if b4b\ge 4 and recurrent if b=1b=1. The case b=2b=2 is still open.Comment: Published at http://dx.doi.org/10.1214/009117905000000837 in the Annals of Probability (http://www.imstat.org/aop/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Limit Theorems for Reinforced Jump Processes on Regular Trees

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    Consider a vertex-reinforced jump process defined on a regular tree, where each vertex has exactly b children, with b >= 3. We prove the strong law of large numbers and the central limit theorem for the distance of the process from the root. Notice that it is still unknown if vertex-reinforced jump process is transient on the binary tree.Reinforced random walks, stochastic processes, strong law of large numbers, central limit theorem

    Bounds on the Speed and on Regeneration Times for Certain Processes on Regular Trees

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    We develop a technique that provides a lower bound on the speed of transient random walk in a random environment on regular trees. A refinement of this technique yields upper bounds on the first regeneration level and regeneration time. In particular, a lower and upper bound on the covariance in the annealed invariance principle follows. We emphasize the fact that our methods are general and also apply in the case of once-reinforced random walk. Durrett, Kesten and Limic (2002) prove an upper bound of the form b/(b+δ)b/(b+\delta) for the speed on the bb-ary tree, where δ\delta is the reinforcement parameter. For δ>1\delta>1 we provide a lower bound of the form γ2b/(b+δ)\gamma^2 b/(b+\delta), where γ\gamma is the survival probability of an associated branching process.Comment: 21 page

    Bounds on the speed and on regeneration times for certain processes on regular trees

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    We develop a technique that provides a lower bound on the speed of transient random walk in a random environment on regular trees. A refinement of this technique yields upper bounds on the first regeneration level and regeneration time. In particular, a lower and upper bound on the covariance in the annealed invariance principle follows. We emphasize the fact that our methods are general and also apply in the case of once-reinforced random walk. Durrett, Kesten and Limic [11] prove an upper bound of the form b/(b + d) for the speed on the b-ary tree, where d is the reinforcement parameter. For d > 1 we provide a lower bound of the form g^2b/(b + d), where g is the survival probability of an associated branching process.Random walk in a random environment; once edge-reinforced random walk; lower bound on the speed; regeneration times; regular trees.

    On the speed of once-reinforced biased random walk on trees

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    We study the asymptotic behaviour of once-reinforced biased random walk (ORbRW) on Galton-Watson trees. Here the underlying (unreinforced) random walk has a bias towards or away from the root. We prove that in the setting of multiplicative once-reinforcement the ORbRW can be recurrent even when the underlying biased random walk is ballistic. We also prove that, on Galton-Watson trees without leaves, the speed is positive in the transient regime. Finally, we prove that, on regular trees, the speed of the ORbRW is monotone decreasing in the reinforcement parameter when the underlying random walk has high speed, and the reinforcement parameter is small

    On a preferential attachment and generalized Pólya's urn model

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    We study a general preferential attachment and Pólya's urn model. At each step a new vertex is introduced, which can be connected to at most one existing vertex. If it is disconnected, it becomes a pioneer vertex. Given that it is not disconnected, it joins an existing pioneer vertex with probability proportional to a function of the degree of that vertex. This function is allowed to be vertex-dependent, and is called the reinforcement function. We prove that there can be at most three phases in this model, depending on the behavior of the reinforcement function. Consider the set whose elements are the vertices with cardinality tending a.s. to infinity. We prove that this set either is empty, or it has exactly one element, or it contains all the pioneer vertices. Moreover, we describe the phase transition in the case where the reinforcement function is the same for all vertices. Our results are general, and in particular we are not assuming monotonicity of the reinforcement function. Finally, consider the regime where exactly one vertex has a degree diverging to infinity. We give a lower bound for the probability that a given vertex ends up being the leading one, i.e. its degree diverges to infinity. Our proofs rely on a generalization of the Rubin construction given for edge-reinforced random walks, and on a Brownian motion embedding.Preferential attachment; Reinforcement processes; Species sampling sequence; Pólya's urn process

    Phase transitions for edge-reinforced random walks on the half-line

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    We study the behaviour of a class of edge-reinforced random walks {on Z+\mathbb{Z}_+}, with heterogeneous initial weights, where each edge weight can be updated only when the edge is traversed from left to right. We provide a description for different behaviours of this process and describe phase transitions that arise as trade-offs between the strength of the reinforcement and that of the initial weights. Our result aims to complete the ones given by Davis~\cite{Davis89, Davis90}, Takeshima~\cite{Takeshima00, Takeshima01} and Vervoort~\cite{Vervoort00}.Comment: 16 pages, 1 figur
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