Stochastic Analysis Seminar
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Mon, 10/10/2011 14:15 |
Lucian Beznea (Simion Stoilow Institute of Mathematics of the Romanian Academy) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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Mon, 10/10/2011 15:45 |
Jiri Cerny (ETH Zurich) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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The vacant set is the set of vertices not visited by a random walk on a graph G before a given time T. In the talk, I will discuss properties of this random subset of the graph, the phase transition conjectured in its connectivity properties (in the `thermodynamic limit' when the graph grows), and the relation of the problem to the random interlacement percolation. I will then concentrate on the case when G is a large-girth expander or a random regular graph, where the conjectured phase transition (and much more) can be proved. |
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Mon, 17/10/2011 14:15 |
Janosch Ortmann (University of Warwick) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We establish a large deviations principle for the block sizes of a uniformly random non-crossing partition. As an application we obtain a variational formula for the maximum of the support of a compactly supported probability measure in terms of its free cumulants, provided these are all non-negative. This is useful in free probability theory, where sometimes the R-transform is known but cannot be inverted explicitly to yield the density. |
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Mon, 17/10/2011 15:45 |
Yann Ollivier (Paris Sud Orsay Universite) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We define a notion of discrete Ricci curvature for a metric measure space by looking at whether "small balls are closer than their centers are". In a Riemannian manifolds this gives back usual Ricci curvature up to scaling. This definition is very easy to apply in a series of examples such as graphs (eg the discrete cube has positive curvature). We are able to generalize several Riemannian theorems in positive curvature, such as concentration of measure and the log-Sobolev inequality. This definition also allows to prove new theorems both in the Riemannian and discrete case: for example improved bounds on spectral gap of the Laplace-Beltrami operator, and fast convergence results for some Markov Chain Monte Carlo methods |
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Mon, 24/10/2011 14:15 |
Marta Sanz-Sole (Universitat de Barcelona) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We consider nonlinear stochastic wave equations in dimension d\le 3. Using Malliavin Calculus, we give upper bounds for the small eigenvalues of the inverse of two point densities.These provide a rate of degeneracy when points go close to each other. Then, we analyze the consequences of this result on lower estimates for hitting probabilities. |
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Mon, 24/10/2011 15:45 |
Jean-Francois Le Gall (Universite of Paris sud and Institut Universitaire de France) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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Planar maps are graphs embedded in the plane, considered up to continuous deformation. They have been studied extensively in combinatorics, and they have also significant geometrical applications. Particular cases of planar maps are p-angulations, where each face (meaning each component of the complement of edges) has exactly p adjacent edges. Random planar maps have been used in theoretical physics, where they serve as models of random geometry.Our goal is to discuss the convergence in distribution of rescaled random planar maps viewed as random metric spaces.More precisely, we consider a random planar map M(n) which is uniformly distributed over the set of all p-angulations with n vertices. We equip the set of vertices of M(n) with the graph distance rescaled by the factor n to the power -1/4. Both in the case p=3 and when p>3 is even, we prove that the resulting random metric spaces converge as n tends to infinity to a universal object called the Brownian map. This convergence holds in the sense of the Gromov-Hausdorff distance between compact metric spaces. In the particular case of triangulations (p=3), this solves an open problem stated by Oded Schramm in his 2006 ICM paper. As a key tool, we use bijections between planar maps and various classes of labeled trees |
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Mon, 31/10/2011 14:15 |
(University of Oxford) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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In the recent series of papers Kleban, Simmons, and Ziff gave a non-rigorous
computation (base on Conformal Field Theory) of probabilities of several
connectivity events for critical percolation. In particular they showed that
the probability that there is a percolation cluster connecting two points on
the boundary and a point inside the domain can be
factorized in therms of pairwise connection probabilities. We are going to use
SLE techniques to rigorously compute probabilities of several connectivity
events and prove the factorization formula. |
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Mon, 31/10/2011 15:45 |
Irina Ignatiouk (Universite Cergy) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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To identify the Martin boundary for a transient Markov chain with Green's function G(x,y), one has to identify all possible limits Lim G(x,y_n)/G(0,y_n) with y_n "tending to infinity". For homogeneous random walks, these limits are usually obtained from the exact asymptotics of Green's function G(x,y_n). For non-homogeneous random walks, the exact asymptotics af Green's function is an extremely difficult problem. We discuss several examples where Martin boundary can beidentified by using large deviation technique. The minimal Martin boundary is in general not homeomorphic to the "radial" compactification obtained by Ney and Spitzer for homogeneous random walks in Z^d : convergence of a sequence of points y_n toa point on the Martin boundary does not imply convergence of the sequence y_n/|y_n| on the unit sphere. Such a phenomenon is a consequence of non-linear optimal large deviation trajectories. |
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Mon, 07/11/2011 14:15 |
Anton Thalmaier (University of Luxembourg) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We describe a construction of the Brownian measure on Jordan curves with respect to the Weil-Petersson metric. The step from Brownian motion on the diffeomorphism group of the circle to Brownian motion on Jordan curves in the complex plane requires probabilistic arguments well beyond the classical theory of conformal welding, due to the lacking quasi-symmetry of canonical Brownian motion on Diff(S1). A new key step in our construction is the systematic use of a Kählerian diffusion on the space of Jordan curves for which the welding functional gives rise to conformal martingales. |
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Mon, 07/11/2011 15:45 |
Simon Harris (University of Bath) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We will consider a branching Brownian motion where particles have a drift $-\rho$, binary branch at rate $\beta$ and are killed if they hit the origin. This process is supercritical if $\beta>\rho^2/2$ and we will discuss the survival probability in the regime as criticality is approached. (Joint work with Elie Aidekon) |
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Mon, 14/11/2011 14:15 |
Nicolas Fournier (Université Paris Est) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We
consider the forest fire process on Z: on each site, seeds and matches fall at
random, according to some independent Poisson processes. When a seed falls on a
vacant site, a tree immediately grows. When a match falls on an occupied site, a
fire destroys immediately the corresponding occupied connected component. We
are interested in the asymptotics of rare fires. We prove that, under
space/time re-scaling, the process converges (as matches become rarer and
rarer) to a limit forest fire process. |
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Mon, 14/11/2011 15:45 |
Danyu Yang (University of Oxford) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We treat the first n terms of general orthogonal series evolving with n as the partial sum process, and proved that under Menshov-Rademacher condition, the partial sum process can be enhanced into a geometric 2-rough process. For Fourier series, the condition can be improved, with an equivalent condition on limit function identified. |
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Mon, 21/11/2011 14:15 |
Radek Erban (University of Oxford) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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Several stochastic simulation algorithms (SSAs) have been recently proposed for modelling reaction-diffusion processes in cellular and molecular biology. In this talk, two commonly used SSAs will be studied. The first SSA is an on-lattice model described by the reaction-diffusion master equation. The second SSA is an off-lattice model based on the simulation of Brownian motion of individual molecules and their reactive collisions. The connections between SSAs and the deterministic models (based on reaction- diffusion PDEs) will be presented. I will consider chemical reactions both at a surface and in the bulk. I will show how the "microscopic" parameters should be chosen to achieve the correct "macroscopic" reaction rate. This choice is found to depend on which SSA is used. I will also present multiscale algorithms which use models with a different level of detail in different parts of the computational domain |
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Mon, 21/11/2011 15:45 |
Krzysztof Bogdan (Institute of Mathematics of the Polisch Academy of Sciences and Wrocław University of Technology) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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I will report joint work with Wolfhard Hansen, Tomasz Jakubowski, Sebastian Sydor and Karol Szczypkowski on perturbations of semigroups and integral kernels, ones which produce comparable semigroups and integral kernels. |
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Mon, 28/11/2011 14:15 |
Claudio Landim |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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We present some recent results on the metastability of continuous time Markov chains on finite sets using potential theory. This approach is applied to the case of supercritical zero range processes. |
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Mon, 28/11/2011 15:45 |
Steffen Dereich (Marburg University) |
Stochastic Analysis Seminar |
Oxford-Man Institute |
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The
notion quantization originates from information theory, where it refers to the
approximation of a continuous signal on a discrete set. Our research on
quantization is mainly motivated by applications in quadrature problems. In
that context, one aims at finding for a given probability measure $\mu$ on a
metric space a discrete approximation that is supported on a finite number of
points, say $N$, and is close to $\mu$ in a Wasserstein metric. The
talk is based on joint work with Michael Scheutzow (TU Berlin) and Reik
Schottstedt (U Marburg). |
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