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The aim of our work is to study vertex-reinforced jump processes with super-linear weight function $w(t) = t^\alpha$ , for some $\alpha>1$. On any complete graph $G = (V, E)$, we prove that there is one vertex $v \in V$ such that the total…

Probability · Mathematics 2021-07-23 Olivier Raimond , Tuan-Minh Nguyen

We consider a non-linear vertex-reinforced jump process (VRJP($w$)) on $\mathbb{Z}$ with an increasing measurable weight function $w:[1,\infty)\to [1,\infty)$ and initial weights equal to one. Our main goal is to study the asymptotic…

Probability · Mathematics 2022-08-19 Andrea Collevecchio , Tuan-Minh Nguyen , Stanislav Volkov

We prove that the restriction of the vertex-reinforced jump process to a subset of the vertex set is a mixture of vertex-reinforced jump processes. A similar statement holds for the non-linear hyperbolic supersymmetric sigma model. This is…

Probability · Mathematics 2024-11-12 Margherita Disertori , Franz Merkl , Silke W. W. Rolles

In this paper we introduce a new simple but powerful general technique for the study of edge- and vertex-reinforced processes with super-linear reinforcement, based on the use of order statistics for the number of edge, respectively of…

Probability · Mathematics 2016-06-03 Codina Cotar , Debleena Thacker

We introduce random interlacements for transient vertex-reinforced jump processes on a general graph $G$. Using increasing finite subgraphs $G_n$ of $G$ with wired boundary conditions, we show convergence of the vertex-reinforced jump…

Probability · Mathematics 2019-03-20 Franz Merkl , Silke W. W. Rolles , Pierre Tarrès

We study Vertex-Reinforced-Random-Walk on the complete graph with weights of the form $w(n)=n^\alpha$, with $\alpha>1$. Unlike for the Edge-Reinforced-Random-Walk, which in this case localizes a.s. on 2 sites, here we observe various phase…

Probability · Mathematics 2013-10-08 Michel Benaïm , Olivier Raimond , Bruno Schapira

We prove that the only nearest neighbor jump process with local dependence on the occupation times satisfying the partial exchangeability property is the vertex reinforced jump process, under some technical conditions. This result gives a…

Probability · Mathematics 2015-11-06 Xiaolin Zeng

We consider a class of multi-particle reinforced interacting random walks. In this model, there are some (finite or infinite) particles performing random walks on a given (finite or infinite) connected graph, so that each particle has…

Probability · Mathematics 2013-03-26 Jun Chen

Consider a vertex-reinforced jump process defined on a regular tree, where each vertex has exactly $b$ children, with $b \ge 3$. We prove the strong law of large numbers and the central limit theorem for the distance of the process from the…

Probability · Mathematics 2009-07-29 Andrea Collevecchio

We consider a class of strongly edge-reinforced random walks, where the corresponding reinforcement weight function is nondecreasing. It is known, from Limic and Tarr\`{e}s [Ann. Probab. (2007), to appear], that the attracting edge emerges…

Probability · Mathematics 2016-09-07 Codina Cotar , Vlada Limic

This article studies vertex reinforced random walks that are non-backtracking (denoted VRNBW), i.e. U-turns forbidden. With this last property and for a strong reinforcement, the emergence of a path may occur with positive probability.…

Probability · Mathematics 2017-08-02 Line C. Le Goff , Olivier Raimond

This article introduces a model for interacting vertex-reinforced random walks, each taking values on a complete sub-graph of a locally finite undirected graph. The transition probability for a walk to a given vertex depends on the…

Probability · Mathematics 2025-08-25 Fernando P. A. Prado , Rafael A. Rosales

The goal is to show that an edge-reinforced random walk on a graph of bounded degree, with reinforcement weight function $W$ taken from a general class of reciprocally summable reinforcement weight functions, traverses a random attracting…

Probability · Mathematics 2009-09-29 Vlada Limic , Pierre Tarrès

We consider a continuous-time vertex reinforced jump process on a supercritical Galton-Watson tree. This process takes values in the set of vertices of the tree and jumps to a neighboring vertex with rate proportional to the local time at…

Probability · Mathematics 2012-09-25 Anne-Laure Basdevant , Arvind Singh

This paper concerns the Vertex reinforced jump process (VRJP), the Edge reinforced random walk (ERRW) and their link with a random Schr\"odinger operator. On infinite graphs, we define a 1-dependent random potential $\beta$ extending that…

Probability · Mathematics 2018-07-20 Christophe Sabot , Xiaolin Zeng

We give a simple proof for recurrence of vertex reinforced jump process on \(\mathbb{Z}^d\), under strong reinforcement. Moreover, we show how the previous result implies that linearly edge-reinforced random walk on \ \(\mathbb{Z}^d\) is…

Probability · Mathematics 2019-11-11 Andrea Collevecchio , Xiaolin Zeng

We prove that the linearly edge reinforced random walk (LRRW) on any graph with bounded degrees is recurrent for sufficiently small initial weights. In contrast, we show that for non-amenable graphs the LRRW is transient for sufficiently…

Probability · Mathematics 2014-05-08 Omer Angel , Nicholas Crawford , Gady Kozma

Vertex-Reinforced Random Walk (VRRW), defined by Pemantle (1988a), is a random process in a continuously changing environment which is more likely to visit states it has visited before. We consider VRRW on arbitrary graphs and show that on…

Probability · Mathematics 2016-09-07 Stanislov Volkov

The vertex-reinforced jump process (VRJP) is a form of self-interacting random walk in which the walker is biased towards returning to previously visited vertices with the bias depending linearly on the local time at these vertices. We…

Probability · Mathematics 2021-05-17 Gady Kozma , Ron Peled

We show that the vertex-reinforced jump process on the $d$-dimensional lattice with long-range jumps is transient in any dimension $d$ as long as the initial weights do not decay too fast. The main ingredients in the proof are: an analysis…

Probability · Mathematics 2025-07-22 Margherita Disertori , Franz Merkl , Silke W. W. Rolles
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