Consider an $n$ by $n$ random matrix $A$ with i.i.d entries. In this talk, we discuss some results on the magnitude of the smallest singular value of $A$, and, in particular, the problem of estimating the singularity probability when the entries of $A$ are discrete.

We study the set $L(G)$ of cycle lengths that appear in a sparse binomial random graph $G(n,c/n)$ and in a random $d$-regular graph $G_{n,d}$. We show in particular that for most values of $c$, for $G$ drawn from $G(n,c/n)$ the set $L(G)$ contains typically an interval $[\omega(1), (1-o(1))L_{\max}(G)]$, where $L_{\max}(G)$ is the length of a longest cycle (the circumference) of $G$. For the case of random $d$-regular graphs, $d\geq 3$ fixed, we obtain an accurate asymptotic estimate for the probability of $L(G)$ to contain a full interval $[k,n]$ for a fixed $k\geq 3$. Similar results are obtained also for the supercritical case $G(n,(1+\epsilon)/n)$, and for random directed graphs.
A joint work with Yahav Alon and Eyal Lubetzky.

Percolation models were originally introduced to describe the propagation of a fluid in a random medium. In dimension two, the percolation properties of a model are encoded by so-called crossing probabilities (probabilities that certain rectangles are crossed from left to right). In the eighties, Russo, Seymour and Welsh obtained general bounds on crossing probabilities for Bernoulli percolation (the most studied percolation model, where edges of a lattice are independently erased with some given probability $1-p$). These inequalities rapidly became central tools to analyze the critical behavior of the model.
In this talk I will present a new result which extends the Russo-Seymour-Welsh theory to general percolation measures satisfying two properties: symmetry and positive correlation. This is a joint work with Laurin Köhler-Schindler.

In this talk we will discuss some classical and recent results on local limits of random graphs. It is well known that the limiting object of the local structure of the classical Erdos-Renyi random graph is a Galton-Watson tree. This can nicely be formalised in the language of Benjamini-Schramm or Aldous-Steele local weak convergence. Regarding local limits of sparse random planar graphs, there is a smooth transition from a Galton-Watson tree to a Skeleton tree. This talk is based on joint work with Michael Missethan.

We present an exponential improvement to the lower bound on diagonal Ramsey numbers for any fixed number of colors greater than two.
This is a joint work with David Conlon.
 

How does a colony of ants find the shortest path between its nest and a source of food without any means of communication other than the pheromones each ant leave behind itself?
In this joint work with Daniel Kious (Bath) and Bruno Schapira (Marseille), we introduce a new probabilistic model for this phenomenon. In this model, the nest and the source of food are two marked nodes in a finite graph. Ants perform successive random walks from the nest to the food, and the distribution of the $n$th walk depends on the trajectories of the $(n-1)$ previous walks through some linear reinforcement mechanism.
Using stochastic approximation methods, couplings with Pólya urns, and the electric conductances method for random walks on graphs (which I will explain on some simple examples), we prove that, depending on the exact reinforcement rule, the ants may or may not always find the shortest path(s) between their nest and the source food.

We discuss the behavior of geodesics in the continuous models of random geometry known as the Brownian map and the Brownian plane. We say that a point $x$ is a geodesic star with $m$ arms if $x$ is the endpoint of $m$ disjoint geodesics. We prove that the set of all geodesic stars with $m$ arms has dimension $5-m$, for $m=1,2,3,4$. This complements recents results of Miller and Qian, who derived upper bounds for these dimensions.

How much does the chromatic number of the random graph $G(n, 1/2)$ vary? Shamir and Spencer proved that it is contained in some sequence of intervals of length about $n^{1/2}$. Alon improved this slightly to $n^{1/2} / \log n$. Until recently, however, no lower bounds on the fluctuations of the chromatic number of $G(n, 1/2)$ were known, even though the question was raised by Bollobás many years ago. I will talk about the main ideas needed to prove that, at least for infinitely many $n$, the chromatic number of $G(n, 1/2)$ is not concentrated on fewer than $n^{1/2-o(1)}$ consecutive values.
I will also discuss the Zigzag Conjecture, made recently by Bollobás, Heckel, Morris, Panagiotou, Riordan and Smith: this proposes that the correct concentration interval length 'zigzags' between $n^{1/4+o(1)}$ and $n^{1/2+o(1)}$, depending on $n$.
Joint work with Oliver Riordan.

The title of the talk corresponds to a family of interesting random processes, which includes lazy random walks on graphs and much beyond them. Often, a key step in analysing such processes is to estimate their spectral gaps (ie. the difference between two largest eigenvalues). It is thus of interest to understand what else about the chain we can know from the spectral gap. We will present a simple comparison idea that often gives us the best possible estimates. In particular, we re-obtain and improve upon several known results on hitting, meeting, and intersection times; return probabilities; and concentration inequalities for time averages. We then specialize to the graph setting, and obtain sharp inequalities in that setting. This talk is based on work that has been in progress for far too long with Yuval Peres.

In this talk we will consider the extremal values of the stationary distribution of the sparse directed configuration model. Under the assumption of linear $(2+\eta)$-moments on the in-degrees and of bounded out-degrees, we obtain tight comparisons between the maximum value of the stationary distribution and the maximum in-degree. Under the further assumption that the order statistics of the in-degrees have power-law behavior, we show that the upper tail of the stationary distribution also has power-law behavior with the same index. Moreover, these results extend to the PageRank scores of the model, thus confirming a version of the so-called power-law hypothesis. Joint work with Xing Shi Cai, Pietro Caputo and Matteo Quattropani.