Search results for "Brownian bridge"
showing 5 items of 5 documents
Hard-wall interactions in soft matter systems: Exact numerical treatment
2011
An algorithm for handling hard-wall interactions in simulations of driven diffusive particle motion is proposed. It exploits an exact expression for the one-dimensional transition probability in the presence of a hard (reflecting) wall and therefore is numerically exact in the sense that it does not introduce any additional approximation beyond the usual discretization procedures. Studying two standard situations from soft matter systems, its performance is compared to the heuristic approaches used in the literature.
On first exit times and their means for Brownian bridges
2017
For a Brownian bridge from $0$ to $y$ we prove that the mean of the first exit time from interval $(-h,h), \,\, h>0,$ behaves as $O(h^2)$ when $h \downarrow 0.$ Similar behavior is seen to hold also for the 3-dimensional Bessel bridge. For Brownian bridge and 3-dimensional Bessel bridge this mean of the first exit time has a puzzling representation in terms of the Kolmogorov distribution. The result regarding the Brownian bridge is applied to prove in detail an estimate needed by Walsh to determine the convergence of the binomial tree scheme for European options.
De Rham–Hodge–Kodaira Operator on Loop Groups
1997
AbstractWe consider a based loop group Le(G) over a compact Lie groupG, endowed with its pinned Wiener measureν(the law of the Brownian bridge onG) and we shall calculate the Ricci curvature for differentialn-forms over Le(G). A type of Bochner–Weitzenböck formula for general differentialn-forms (or Shigekawa identity) will be established.
BROWNIAN DYNAMICS SIMULATIONS WITHOUT GAUSSIAN RANDOM NUMBERS
1991
We point out that in a Brownian dynamics simulation it is justified to use arbitrary distribution functions of random numbers if the moments exhibit the correct limiting behavior prescribed by the Fokker-Planck equation. Our argument is supported by a simple analytical consideration and some numerical examples: We simulate the Wiener process, the Ornstein-Uhlenbeck process and the diffusion in a Φ4 potential, using both Gaussian and uniform random numbers. In these examples, the rate of convergence of the mean first exit time is found to be nearly identical for both types of random numbers.
Self-normalized and randomly centered spectral estimates
1996
We review some limit theory for the periodogram and for integrated versions of it and explain the use of random normalizing and centering techniques.