Maximum distributions of bridges of noncolliding Brownian paths

Abstract

The one-dimensional Brownian motion starting from the origin at time $t=0$, conditioned to return to the origin at time $t=1$ and to stay positive during time interval $0<t<1$, is called the Bessel bridge with duration 1. We consider the $N$-particle system of such Bessel bridges conditioned never to collide with each other in $0<t<1$, which is the continuum limit of the vicious walk model in watermelon configuration with a wall. Distributions of maximum-values of paths attained in the time interval $t\in (0,1)$ are studied to characterize the statistics of random patterns of the repulsive paths on the spatio-temporal plane. For the outermost path, the distribution function of maximum value is exactly determined for general $N$. We show that the present $N$-path system of noncolliding Bessel bridges is realized as the positive-eigenvalue process of the $2N\times 2N$ matrix-valued Brownian bridge in the symmetry class C. Using this fact computer simulations are performed and numerical results on the $N$-dependence of the maximum-value distributions of the inner paths are reported. The present work demonstrates that the extreme-value problems of noncolliding paths are related with the random matrix theory, representation theory of symmetry, and the number theory.

REVTeX4, 34 pages, 12 figures, title changed and minor corrections made for publication in Phys. Rev. E

References in corpus (5)

• Symmetry of matrix-valued stochastic processes and noncolliding diffusion particle systems
• Exact distribution of the maximal height of p vicious walkers
• Nonintersecting Brownian excursions
• Noncolliding Brownian Motion and Determinantal Processes
• Two Bessel Bridges Conditioned Never to Collide, Double Dirichlet Series, and Jacobi Theta Function

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• Noncolliding Brownian Motion with Drift and Time-Dependent Stieltjes-Wigert Determinantal Point Process
• Persistence of Random Walk Records
• Bessel process, Schramm-Loewner evolution, and Dyson model
• Extreme value distributions of noncolliding diffusion processes