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The Brownian Web and Net

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The Brownian Web and Net The Brownian web and net Jan M. Swart Institute of Information Theory and Automation of the ASCR (UTIA)´ The Brownian web and net – p.1/39 The diagonal square lattice We start with the diagonal square lattice. The Brownian web and net – p.2/39 Arrows With probability 1/2 we draw an arrow to the left. The Brownian web and net – p.3/39 Arrows . and with the same probability to the right. The Brownian web and net – p.4/39 Arrows We do this for every point. The Brownian web and net – p.5/39 Paths We are interested in paths along arrows. The Brownian web and net – p.6/39 Diffusive scaling We scale space with ε, time with ε2, and let ε → 0. The Brownian web and net – p.7/39 The Brownian web In the limit we obtain the Brownian web. The Brownian web and net – p.8/39 Random walk paths Discrete paths along arrows are random walks. The Brownian web and net – p.9/39 Brownian paths In the Brownian web, paths are Brownian motions. The Brownian web and net – p.10/39 Brownian motion 1827: The botanist Robert Brown observes the irregular motion of small particles submerged in water. 1905: Albert Einstein explains the motion as being caused by the collision of water molecules with the particle. In good approximation, the motion should be a Markov process with normally distributed increments. Early 1920-ies: Norbert Wiener constructs a probability measure on the space of continuous paths which has the properties postulated by Einstein. Present: (mathematical) Brownian motion is one of the cornerstones of modern probability theory. The Brownian web and net – p.11/39 Coalescing Brownian motions Paths started at different points coalesce. The Brownian web and net – p.12/39 Coalescing Brownian motions Paths started at different points coalesce. The Brownian web and net – p.13/39 Coalescing Brownian motions Paths started at different points coalesce. The Brownian web and net – p.14/39 Coalescing Brownian motions Paths started at different points coalesce. The Brownian web and net – p.15/39 Coalescing Brownian motions Paths started at different points coalesce. The Brownian web and net – p.16/39 Construction The Brownian web can be constructed in two steps: Construct an infinite sequence of coalescing Brownian paths whose starting points fill up space. Take all paths that occur as the limits of these paths. The result can be described as “coalescing Brownian mo- tions, started from every point in space and time”. The Brownian web and net – p.17/39 Applications River systems Lines of descent Evolution of interfaces Coalescing particles The Brownian web and net – p.18/39 History of the Brownian web R. Arratia (1979): one-dimensional voter model. B. Tóth and W. Werner (1998): true self-repellent motion L.R. Fontes, L.G.R. Isopi, C.M. Newman and K. Ravishankar (2002–): one-dimensional Potts model. The Brownian web and net – p.19/39 Paths started at time zero Coalescing Brownian motions started everywhere on the line. The Brownian web and net – p.20/39 Point with two outgoing paths There exist random points from where there starts more than one path. The Brownian web and net – p.21/39 Special points Special points are classified according to the number of incoming and outgoing paths. There exists 7 types of special points. The Brownian web and net – p.22/39 Dual arrows Forward and dual arrows. The Brownian web and net – p.23/39 Dual Brownian web Approximation of the forward and dual Brownian web. The Brownian web and net – p.24/39 Dual Brownian web Forward and dual paths started from fixed times. The Brownian web and net – p.25/39 Special points revisited Structure of dual paths at special points. The Brownian web and net – p.26/39 Adding branching With probability ε, we draw two arrows at a point. We scale diffusively and let ε → 0. The Brownian web and net – p.27/39 The Brownian net In the limit we obtain the Brownian net. The Brownian web and net – p.28/39 Left and right random walks In the discrete approximation, we draw left-most paths in blue and right-most paths in red. The Brownian web and net – p.29/39 Left and right paths In the limit, left-most and a right-most paths are Brownian motions with drift −1 and +1, respectively. The Brownian web and net – p.30/39 Left and right paths The interaction between left-most and right-most paths is described by the stochastic differential equation (SDE): d = 1 d l + 1 d s d Lt {Lt6=Rt} Bt {Lt=Rt} Bt − t, d = 1 d r + 1 d s + d Rt {Lt6=Rt} Bt {Lt=Rt} Bt t, l r s where Bt, Bt , Bt are independent Brownian motions, and Lt and Rt are subject to the constraint that Lt ≤ Rt for all t ≥ T := inf{u ≥ 0 : Lu ≤ Ru}. The Brownian web and net – p.31/39 Left Brownian web The left-most paths form a left-most Brownian web. The Brownian web and net – p.32/39 Right Brownian web ...and the right-most paths form a right-most Brownian web. The Brownian web and net – p.33/39 Left-right Brownian web Together, they are known as the “left-right Brownian web”. The Brownian web and net – p.34/39 Construction of the Brownian net ‘Hopping construction’ [Sun & S. 2008]: 1. Couple a left and right Brownian web using the “left-right SDE”. 2. Add all finite concatenations of left-most and right-most paths. 3. Add all limits of paths from step 2. Alternative constructions: ‘wedge construction’, ‘mesh construction’ [Sun & S. 2008]; ‘marking construction’ [Newman, Ravishankar & Schertzer 2008]. The Brownian web and net – p.35/39 The branching-coalescing point set The paths in the Brownian net started at time zero form the ‘branching-coalescing point set’. The Brownian web and net – p.36/39 The branching-coalescing point set Markov process taking values in the closed subsets of the real line. Equilibrium law: Poisson point set with intensity 2. At each deterministic time t > 0 locally finite. There exists random times when the process is not locally finite. The Brownian web and net – p.37/39 Special points of the Brownian net Modulo symmetry, there exist 9 types of special points of the Brownian net. [Schertzer, Sun & S. 2009]. The Brownian web and net – p.38/39 The End Thank you! The Brownian web and net – p.39/39.
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