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                  Toronto Probability Seminar 2007-08 
                    held at the Fields Institute 
                  Organizers 
                    Bálint 
                    Virág , Benedek 
                    Valkó 
                    University of Toronto, Mathematics and Statistics  
                  
                  For questions, scheduling, or to be added to the mailing 
                    list, contact the organizers at: 
                    probsem-at-math-dot-toronto-dot-edu 
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                   2008 
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                   Speaker and Talk Title 
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                June 16 
                  4:10-5  
                  Fields Library  | 
                Eckhard Schlemm, FU Berlin (visiting U 
                  of T)  
                  will present a talk about his masters thesis (Diplomarbeit) 
                  on First-passage percolation on widh-two stretches 
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                   Tuesday,  
                    April 8, 2008 
                    4:30 p.m. 
                    215 Huron,  
                    Room 1018  
                    *Note Unusual Time and Place* 
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                   Mate Matolcsi (Renyi Institute of Mathematics, Hungary) 
                    The real polarization problem 
                    We study a conjecture of Benitez, Sarantopoulos and Tonge 
                    concerning a lower bound on the norm of products of real linear 
                    functioanls. The conjecture is that the lower-bound is attained 
                    if and only if the vectors corresponding to the functionals 
                    are orthogonal. There are several approaches to the problem, 
                    analytic (Revesz, Pappas, 2004), geometric (Matolcsi, 2005), 
                    and probabilistic (Frenkel, 2007), yielding partial results. 
                    The probabilistic approach of Fernkel, 2007, deduces a lower 
                    bound from the following theorem: If X1, ... , Xn are jointly 
                    Gaussian random variables with zero expectation, then E(X1^2 
                    ... Xn^2) >= EX1^2 ... EXn^2. Equality holds if and only 
                    if they are independent or at least one of them is almost 
                    surely zero. A similar result for higher moments would imply 
                    the conjecture. 
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                Monday,  
                  March 24, 2008 4:00 pm,  
                  Stewart Libary Fields | 
                Lincoln Chayes, UCLA 
                  On the absence of ferromagnetizm in typical 2D ferromagnets. | 
               
               
                Monday,  
                  March 17, 2008 10:10 am,  
                  215 Huron St. | 
                B. Valko and B. Virag, University 
                  of Toronto 
                  The Brownian Carousel 
                  In the fourth and final part of this epic trilogy we explain 
                  some details of the proof of that connects random matrices 
                  to hyperbolic Brownian motion. | 
               
               
                Monday,  
                  March 10, 2008 4:00 pm,  
                  Stewart Libary Fields | 
                 
                   B. Valko and B. Virag, University of Toronto 
                    The Brownian Carousel, part 2b. 
                    The eigenvalues of a random Hermitian matrix form a random 
                    set of points on the real line. As the matrix size converges 
                    to infinity, the eigenvalues, after appropriate scaling, converge 
                    to a point process. 
                    The possible limit processes, called Sine-beta processes, 
                    are fundamental objects of probability theory. They are famous 
                    for their conjectured relationship to the Riemann zeta zeros, 
                    Dirichlet eigenvalues of Euclidean domains, random Young tableaux, 
                    and non-colliding walks. This series of informal talks is 
                    about a new description of these processes in terms of Brownian 
                    motion in the hyperbolic plane, called the Brownian carousel. 
                    We plan to have three lectures: 
                    1. Introduction to random matrix eigenvalues, definition and 
                    basic properties of the Brownian Carousel 
                    2. Computing with the Brownian carousel; continuity, phase 
                    transitions, Dyson's predictions 
                    3. Convergence of finite random matrix eigenvalues to the 
                    Brownian carousel 
                  
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                Monday,  
                  March 3, 2008 4:00 pm,  
                  Room TBA | 
                B. Valko and B. Virag, University 
                  of Toronto 
                  The Brownian Carousel, part 2 | 
               
               
                Monday,  
                  Feb. 25, 2008 4:30 pm,  
                  Stewart Libary Fields | 
                B. Valko and B. Virag, University 
                  of Toronto 
                  The Brownian Carousel 
                  The eigenvalues of a random Hermitian matrix form a random 
                  set of points on the real line. As the matrix size converges 
                  to infinity, the eigenvalues, after appropriate scaling, converge 
                  to a point process. 
                  The possible limit processes, called Sine-beta processes, are 
                  fundamental objects of probability theory. They are famous for 
                  their conjectured relationship to the Riemann zeta zeros, Dirichlet 
                  eigenvalues of Euclidean domains, random Young tableaux, and 
                  non-colliding walks. 
                  This series of informal talks is about a new description of 
                  these processes in terms of Brownian motion in the hyperbolic 
                  plane, called the Brownian carousel. We plan to have three lectures: 
                  1. Introduction to random matrix eigenvalues, definition and 
                  basic properties of the Brownian Carousel 
                  2. Computing with the Brownian carousel; continuity, phase transitions, 
                  Dyson's predictions 
                  3. Convergence of finite random matrix eigenvalues to the Brownian 
                  carousel | 
               
               
                Monday,  
                  Feb. 11, 2008 4:30 pm,  
                  Stewart Libary Fields | 
                 
                   Brian Rider (University of Colorado at Boulder) 
                    Diffusion at RMT's hard edge 
                    The RMT hard edge refers to the behavior of the minimal eigenvalues 
                    of a (natural) one-parameter generalization of Gaussian sample 
                    covariance matrices. We show that, in the large dimensional 
                    limit, the law of these points are shared by that of the spectrum 
                    of a certain random second-orderdifferential operator. The 
                    latter may be viewed as  
                    the generator of a Brownian motion with white noise drift. 
                    By a Riccati transform, we get a second diffusion description 
                    of the hard edge in terms of hitting times. 
                    This is joint work with J. Ramirez and should be compared 
                    with slightly less recent results of J. Ramirez, B. Virag, 
                    and myself on the RMT "soft" edge. 
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                Monday,  
                  Feb. 4, 2008 4:10pm,  
                  Stewart Libary Fields | 
                Omer Angel (University of 
                  Toronto) 
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                Monday,  
                  Dec. 10, 2007 4:10pm,  
                  Stewart Libary Fields | 
                James Mingo (Queen's University) 
                  Free Cumulants: First and Second Order 
                  Twenty years ago Voiculescu showed that the limiting distribution 
                  of sums and products of some ensembles of random matrices could 
                  be computed using some algebraic methods of "free" 
                  probability. At the core of free probability are the "free" 
                  cumulants. In recent years I have developed with Roland Speicher 
                  a theory of second order cumulants to do for global fluctuations 
                  what Voiculescu's theory did for limiting distributions. | 
               
               
                Monday,  
                  Dec. 3, 2007 4:10pm,  
                  Stewart Libary Fields | 
                Omer Angel (University of 
                  Toronto) 
                  Minimal Spanning Trees revisited 
                  Given a graph with weighted edges it is easy to find the spanning 
                  tree with minimal total weight. If the graph is the complete 
                  graph K_n and the weights are independent uniform on [0,1] the 
                  MST weight converges in distribution to \zeta(3). I will discuss 
                  two variation on this result. 
                  If the diameter of the tree is constrained to be at most 
                    K, what is the minimal weight? Turns out that there is a transition 
                    at K=\log_2\log n. 
                  If the edges are presented sequentially, and an algorythm 
                    must make a decision on each edge with only partial information, 
                    what can be achieved? Some heuristics lead to algorithms related 
                    to coalescent pocesses. I will give some bounds on the optimal 
                    expected weight. 
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                Monday,  
                  Nov. 26, 2007 4:10pm,  
                  Room 210  
                  Fields | 
                Balazs Szegedy, University 
                  of Toronto 
                  Forcing Randomness. 
                  A surprising theorem by Chung, Graham and Wilson says that if 
                  a graph has edge density close to 1/2 and four cycle density 
                  close to 1/16 than the structure of the graph is close to "random 
                  looking". The natural question arises: What structures 
                  can be forced upon a graph by a finite family of subgraph densities? 
                  These structures are interesting combinations of algebraic structure 
                  andrandomness. We present recent results in this topic. This 
                  is joint work with Laszlo Lovasz. | 
               
               
                Monday,  
                  Nov. 19, 2007 4:10pm,  
                  Stewart Library 
                  Fields | 
                Manjunath Krisnapur (University 
                  of Toronto) 
                  From random matrices to random analytic functions. 
                  Peres and Virag proved that the zeros of the power series 
                  a_0+za_1+z^2a_2+..., with i.i.d. standard complex Gaussian coefficients 
                  is a determinantal point process on the unit disk. Extending 
                  this result, I proved recently that the singular points of the 
                  power series A_0+zA_1+z^2A_2+..., where A_i are k x k matrices 
                  with i.i.d. standard complex Gaussian coefficients, is also 
                  determinantal. As this was presented as conjecture in earlier 
                  talks, the emphasis will be on the proof and its connection 
                  to truncations of unitary random matrices sampled according 
                  to Haar measure. | 
               
               
                Monday,  
                  Oct. 29, 2007 4:10pm,  
                  Stewart Library Fields | 
                Mathieu Merle (University 
                  of British Columbia) 
                   Voter, Lotka-Volterra models and super-Brownian motion 
                  Voter model was initially interpreted as representing the spread 
                  of an opinion, but as the Lotka-Volterra model, it can be also 
                  be interpreted as a stochastic model for competition species. 
                  Super-Brownian motion is a model for population undergoing both 
                  spatial displacement and a continuous branching phenomenon. 
                  Recently, it was shown by Bramson, Cox, Durrett, Le Gall and 
                  Perkins that these objects are closely related, as super-Brownian 
                  motion appears at the scaling limit of both voter and Lotka-Volterra 
                  models, in dimension greater than two. 
                  Then, know properties of super-Brownian motion can be exploited 
                  in order to gain information on these discrete models. We will 
                  see how this leads to asymptotic results for the hitting probabilities 
                  of the voter model started with a single one, in dimensions 
                  2 and 3. We will also briefly survey recent work of Cox and 
                  Perkins, who obtain results on survival and coexistence for 
                  the Lotka-Volterra model in dimension greater than 3. | 
               
               
                Monday,  
                  Oct. 15, 2007 
                  4:10pm,  
                  Stewart Library  
                  Fields | 
                Gidi Amir (University of Toronto) 
                  Excited random walk against a wall  
                   We analyze random walk in the upper half of a three dimensional 
                  lattice which goes down whenever it encounters a new vertex, 
                  reflects on the plane $z=0$, and behaves like a simple random 
                  walk otherwise. a.k.a. excited random walk. We show that it 
                  is recurrent with an expected number of returns of $\sqrt{\log 
                  n}$ (Joint work with Itai Benjamini and Gady Kozma)  | 
               
               
                Monday,  
                  Oct. 1, 2007  
                  4:10pm,  
                  Stewart Library  
                  Fields  | 
                 
                   Gabor Pete (Microsoft Research)  
                    The exact noise and dynamical sensitivity of critical percolation, 
                    via the Fourier spectrum 
                    Let each site of the triangular lattice (or edge of the \Z^2 
                    lattice) have an independent Poisson clock switching between 
                    open and closed. So, at any given moment, the configuration 
                    is just critical percolation. In particular, the probability 
                    of a left-right open crossing in an n*n box is roughly 1/2, 
                    and, on the infinite lattice, almost surely there are only 
                    finite open clusters. 
                     
                    In the box, how long do we have to wait before we lose essentially 
                    all correlation between having a left-right open crossing 
                    now and then? In the infinite lattice, are there random exceptional 
                    times when there are infinite clusters? In joint work with 
                    Christophe Garban and Oded Schramm, we give quite complete 
                    answers: e.g., exceptional times do exist on both lattices, 
                    and the Hausdorff dimension of their set is computed to be 
                    31/36 for the triangular lattice. 
                     
                    The indicator function of a percolation crossing event is 
                    a function on the hypercube {-1,+1}^{sites or edges}, and 
                    thus it has a Fourier-Walsh expansion. Our proofs are based 
                    on giving sharp estimates on the ``weight'' of the Fourier 
                    coefficients at different frequencies.  
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