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start [2026/04/16 09:25]
Igor Kortchemski |
start [2026/05/06 11:44] (Version actuelle)
Djalil Chafaï |
| Along the way, I will discuss several key probabilistic tools, including the configuration model, branching process approximations, and local weak convergence, and explain how they combine to yield asymptotic counting results.// | Along the way, I will discuss several key probabilistic tools, including the configuration model, branching process approximations, and local weak convergence, and explain how they combine to yield asymptotic counting results.// |
| * 27 avril 2026. ** [Attention, exceptionnellement à 14h] [[https://www.robinkhanfir.com/|Robin Khanfir (McGill)]]**. **The Brownian tree is the only uniformly self-similar binary tree.**\\ //The Brownian tree is the scaling limit of many random tree models for which the square of the diameter is of the order of the number of vertices. In contrast to this universality, proofs of such convergences commonly rely on model-specific methods. To provide a conceptual understanding of the universality of the Brownian tree, we show that it is uniquely characterized by a uniform self-similar decomposition property. This leads to a general proof scheme for convergences to the Brownian tree that does not require the computation of finite-dimensional limit distributions. This talk is based on a work in progress.// | * 27 avril 2026. ** [Attention, exceptionnellement à 14h] [[https://www.robinkhanfir.com/|Robin Khanfir (McGill)]]**. **The Brownian tree is the only uniformly self-similar binary tree.**\\ //The Brownian tree is the scaling limit of many random tree models for which the square of the diameter is of the order of the number of vertices. In contrast to this universality, proofs of such convergences commonly rely on model-specific methods. To provide a conceptual understanding of the universality of the Brownian tree, we show that it is uniquely characterized by a uniform self-similar decomposition property. This leads to a general proof scheme for convergences to the Brownian tree that does not require the computation of finite-dimensional limit distributions. This talk is based on a work in progress.// |
| * 11 mai 2026. **[[https://www.ceremade.dauphine.fr/~massoulie/|Brune Massoulié (Dauphine)]]**. **Titre à préciser.**\\ //// | * 11 mai 2026. **[[https://www.ceremade.dauphine.fr/~massoulie/|Brune Massoulié (Dauphine)]]**. **An introduction to some self-repelling processes.**\\ //Self-repelling walks and processes are stochastic processes that are influenced by their past behaviour, in a way that makes them try to avoid their past trajectory. In this talk, I will first present a toy model for self-repelling random walks introduced by Toth and Werner, which allows to present results and methods that generalise to more complex models. I will then present the « true » self-avoiding walk (TSAW) and state the results from an article by Toth in 1995. Last, I will informally present the « true » self-repelling motion, which was constructed by Toth and Werner in 1998, and was proved to be the limit of the TSAW very recently by Kosygina and Peterson.// |
| * **Année 2024-2025.** | * **Année 2024-2025.** |
| * **Organisateurs[[organisation|.]]** [[https://djalil.chafai.net/|Djalil Chafaï]] et [[https://www.normalesup.org/~dumaz/|Laure Dumaz]] | * **Organisateurs[[organisation|.]]** [[https://djalil.chafai.net/|Djalil Chafaï]] et [[https://www.normalesup.org/~dumaz/|Laure Dumaz]] |