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October 20, 2009 Ron Peled
Gravitational Allocation to Poisson Points Chatterjee Sourav, Peled Ron, Peres Yuval and Romik Dan. Gravitational allocation to Poisson points. To appear in Annals of Mathematics. Chatterjee Sourav, Peled Ron, Peres Yuval and Romik Dan. Phase Transitions in Gravitational Allocation. These articles, in turn, borrow many ideas from the seminal work: Nazarov Fedor, Sodin Mikhail, Volberg Alexander. Transportation to random zeroes by the gradient flow. Geometric and Functional Anal- ysis Vol 17-3, 887-935, 2007 (An older version 1 can be found in http://www.arxiv.org/abs/math/ The idea for the gravitational allocation was proposed in: Sodin Mikhail and Tsirelson Boris. Random complex zeroes II: Perturbed lattice. Israel J. Math. 152 (2006), 105–124. Our analysis in the second paper requires the understanding of a special type of Quadrature Formulas, the so called Chebyshev-type quadrature formulas. They are surveyed and some facts developed for them in: Peled Ron. Simple Universal Bounds for Chebyshev-Type Quadratures. Ajtai,
Komlos and Tusnady (1984) showed that any matching between n uniform
independent points in the square of sidelength sqrt(n) and a lattice
with n points in this square, will necessarily have average matching
distance growing at least like sqrt(log(n)). Leighton and Shor (1986)
analyzed the same problem with worst matching distance replacing
average matching distance and obtained log(n)^(3/4). Talagrand (1994)
continued on their work and showed that the behavior in 3 dimensions
and higher is much better. He gave very precise control on the best
matchings. Holroyd and Peres (1995) showed equivalence of equivariant allocations and "extra head rules" (which are an interesting concept in their own right). In the same paper they introduced the first deterministic equivariant allocation - the stable marriage of Poisson and Lebesgue. Later analyzed more in a joint paper with Hoffman. Liggett (2000) and Holroyd and Liggett (2001) showed that any equivariant allocation for the Poisson process in dimensions 1 and 2 will necessarily have cells with high diameter with density which is only polynomially small. This is similar to the situation in finite volume that the works cited above of Ajtai,Komlos and Tusnady, Leighton and Schor and Talagrand explore. Adam Timar (Invariant matchings of exponential tail on coin flips in Z^d, 2009) shows that one can have equivariant matchings with excellent tail bounds for the matching distance, when matching open and closed sites of a percolation on Z^d, d>=3, or when matching points of a Poisson process in 3 dimensions and higher. The method here is completely different than in the other papers. Nice pictures and some brief explanations can be found on my homepage at: http://www.cims.nyu.edu/~ and on Dan Romik's homepage at: http://www.math.ucdavis.edu/~ David Mason
Self-Normalized Processes Limit Theory and Statistical Applications I have attached these chapters as pdf files, which I downloaded from the University of Washington library. (http://www.math.csi.cuny.edu/probability//Files/DavidMason-F09/) For basic information about Levy processes I suggest a look at Chapter 15 of Foundations of Modern Probability by by Olav Kallenberg. Also the first two sections of each of the attached Maller and Mason papers should helpful too. Elena Kosygina, Oct. 27 2009
There are very few prerequisites one needs for this talk. I shall explain the model and some of the basics. One really useful thing to look up would be the correspondence between branching processes and random walks. For example (just to keep the same notation), one can look at our preprint (on which the talk will be based): arXiv:0908.4356v1 [math.PR], Sections 1 and 2. Tuesday, September 22, 4:00 PM, Rm. 5417. Speaker: Fredrik Johansson, KTH Title: Optimal Holder exponent for the SLE path References for graduate students (the first is a good introduction to SLE): Random planar curves and Schramm-Loewner evolutions (Werner): http://arxiv.org/ Optimal Holder exponent for the SLE path (Johansson&Lawler): http:// Mulltifractal analysis of the reverse flow for the Schramm-Lowener evolution (Lawler): http://www.math. May 12, 2009
Speaker: David Nualart, University of Kansas Title: Central limit theorems for functionals of Gaussian processes. References related to the talk: 1. D. Nualart and S. Ortiz-Latorre: Central limit theorems for multiple stochastic integrals and Malliavin calculus. Stochastic Processes and their Applications, 118 (2008) 614--628. 2. D. Nualart and G. Peccati: Central limit theorems for sequences of multiple stochastic integrals. Annals of Probability, 33 (2005) 177--193. 3. S. Darses, I. Nourdin and D. Nualart: Limit theorems for nonlinear functionals of Volterra processes via white noise analysis. Preprint http://arxiv.org/pdf/ 4. D. Nualart: Stochastic integration with respect to fractional Brownian motion and applications. Contemp. Math., 336 (2003) 3--39. April 21, 2009 4pm
Speaker: Souvik Ghosh, Columbia University Title: LARGE DEVIATION PRINCIPLE FOR A CLASS OF LONG RANGE DEPENDENT INFINITELY DIVISIBLE PROCESS References: Alparslan,
U.T., Samorodnitsky, G. (2007) {\sl Ruin probability with certain
stationary stable claims generated by conservative flows\/}, Advances in Applied Probability. 39, 360--384. Ghosh,
S. (2008){\sl The effect of memory on large deviations of moving
average processes and infinitely divisible processes \/}, Thesis,
Cornell University. Mikosch, T., Samorodnitsky, G. (2000) {\sl The supremum of a negative drift random walk with dependent heavy-tailed steps\/}, The Annals of Probability. 10, 1025--1064. Rosinski, J., Samorodnitsky, G. (1996) {\sl Classes of mixing stable processes \/}, Bernoulli. 2, 365--377. March 31, 2009 at 4:00 PM
Speaker: Jose Blanchet, Columbia University Title: Algorithms and Large Deviations Abstract: This talk concentrates on the interplay between large deviations theory and the design of efficient stochastic simulation algorithms that are aimed at both estimating rare-event probabilities and sampling stochastic processes conditional on a rare event. The point is designing simulation estimators that can be easily implemented and whose coefficient of variation remains uniformly bounded as the event becomes rarer and rarer. Typically, a large deviations result is helpful to guide the construction of the estimator, but, as we shall see, the complexity analysis of the algorithm often demands a refinement of the underlying large deviations argument behind the rare-event probability of interest. In this talk we illustrate the techniques both in light and heavy-tailed stochastic processes. Applications to stochastic networks will be given as motivation. Here are some useful refrences:
paper joint paper with Jingchen and the second is not my paper but it was among the first papers of Paul Dupuis and his co-authors that dealt with this problem. In the talk I will present an approach that is different from that of Paul, but this would do for background on the problem. By the time of the talk it is very likely that a new paper will be posted on my webpage related to the stuff on light tails. I'll point to that then. Heavy tails: Rare-event Simulation for Multidimensional Regularly Varying Random Walks (with J. C. Liu). http://www.people.fas.harvard. Light tails: Dynamic importance sampling for queueing networks. Paul Dupuis, Ali Devin Sezer, and Hui Wang: Ann. Appl. Probab. Volume 17, Number 4 (2007), 1306-1346. February 24, 2009 Dmitry Dolgopyat, University of Maryland
The paper is available at arXiv:0806.3236 The background information can be found in the book David Ruelle Thermodynamic Formalism: The Mathematical Structure of Equilibrium Statistical Mechanics (Cambridge Mathematical Library), Chapter 5. December 9, 2008 Julien Dubedat
The talk is based on the introductory text http://arxiv.org/pdf/math/0310326v1 Pawel Hitczenko, November 11, 2008
The talk is based on the paper available at: Jingchen Liu, September 23, 2008
For students (and others) interested in material for this talk, please consult: Peter Carr, March 4 2008
On Schr¨dinger’s equation, 3-dimensional Bessel Rama Cont, March 11 2008
My talk will be based on Chapter 5 of our book Financial Modelling with Jump Processes http://www.cmap.polytechnique.fr/~rama/Jumps/ and the paper by Kallsen & Tankov Characterization of dependence of multidimensional Lévy processes using Lévy copulas Journal of Multivariate Analysis Volume 97, Issue 7, August 2006, Pages 1551-1572 |