Oberseminar Wahrscheinlichkeitstheorie
Joint research seminar of LMU and TUM in Probability Theory
Students and guests welcome.
Organizers:
Noam
Berger (TUM),
Nina
Gantert
(TUM),
Konstantinos Panagiotou (LMU),
Markus
Heydenreich (LMU),
Sabine
Jansen (LMU),
Franz Merkl
(LMU),
Silke
Rolles (TUM)
Upcoming talks:
| Mon 1 Jun 2026, 15:30: Vitali Wachtel Local limit theorem for Kempermann's oscillating random walk |
| The model of oscillating random walks introduced by Kempermann is one of the simplest example of a Markov chain with discontinuous statistics. We consider the situation when this chain converges, after proper rescaling, towards a skew Brownian motion. In the talk I will discuss the corresponding local limit theorem. |
| Parkring 11, Garching-Hochbrück. Room BC1 2.01.10 (8101.02.110) |
| Mon 1 Jun 2026, 17:00: Dieter Mitsche On the mixing time of random geometric graphs |
| We study the mixing time of the simple random walk on the giant component of supercritical $d$-dimensional random geometric graphs generated by the unit intensity Poisson Point Process in a $d$-dimensional cube of volume $n$. With $r_g$ denoting the threshold for having a giant component, we show that for every $\epsilon>0$ and any $r\geq(1+\epsilon)r_g$, the mixing time of the giant component is with high probability $\Theta(n^{2/d}/r^2)$, thereby closing a gap in the literature. Our analysis also implies that the relaxation time is of the same order. Joint work with M. Kiwi and C. Martinez. |
| Parkring 11, Garching-Hochbrück. Room BC1 2.01.10 (8101.02.110) |
| Mon 8 Jun 2026, 16:30: Adrien Malacan TBA |
| TBA |
| Parkring 11, Garching-Hochbrück. |
| Tue 9 Jun 2026, 16:00: Jakob Maier TBA |
| TBA |
| Parkring 11, Garching-Hochbrück. Room BC1 2.01.10 (8101.02.110) |
| Mon 22 Jun 2026, 16:30: Dylan Chaussoy TBA |
| TBA |
| Theresienstr. 39, München. Room B 252 |
| Mon 29 Jun 2026, 16:30: Johannes Bäumler Estimating the history of a random recursive tree |
| We estimate the arrival time of vertices in a uniform random recursive tree from its unlabeled structure. Using centrality-based rankings, we derive tail bounds for the relative estimation error that are uniform in the vertex and the tree size. For the ranking induced by Jordan centrality, the probability that the estimate exceeds the true arrival time by a factor $S$ decays on the order of $1/S$, while the probability that it is smaller than the true arrival time by a factor $1/S$ decays exponentially in $S$. We introduce a refined centrality measure whose overestimation probability decays on the order of $(\log S)/S^{2}$, at the cost of a heavier lower tail of order $1/S^{2}$. These results identify a tradeoff between upper- and lower-tail performance in arrival-time estimation. Joint work with Simon Briend and Joost Jorritsma |
| Parkring 11, Garching-Hochbrück. Room BC1 2.01.10 (8101.02.110) |