Dirichlet boundary conditions for a class of non-Markovian Gaussian stochastic processes
Abstract
Varying conditions at boundaries can give rise to interesting effects on a stochastic system. For example, the first passage time of a non-Markovian stochastic process with boundaries has many practical applications. In this talk, we consider a class of non-Markovian white noise processes that has recently been applied to various complex systems ranging in size from nanoscales to gigameters. The probability density function (PDF) under Dirichlet conditions for this class of stochastic processes with memory is evaluated in closed form using white noise analysis. The PDF that vanishes at a boundary is then used to calculate physically interesting properties such as the survival probability and first passage time of fluctuating observables. In particular, we obtain the first passage time density for stochastic processes with different types of memory behavior.
Downloads
Published
Issue
Section
License
By submitting their manuscript to the Samahang Pisika ng Pilipinas (SPP) for consideration, the Authors warrant that their work is original, does not infringe on existing copyrights, and is not under active consideration for publication elsewhere.
Upon acceptance of their manuscript, the Authors further agree to grant SPP the non-exclusive, worldwide, and royalty-free rights to record, edit, copy, reproduce, publish, distribute, and use all or part of the manuscript for any purpose, in any media now existing or developed in the future, either individually or as part of a collection.
All other associated economic and moral rights as granted by the Intellectual Property Code of the Philippines are maintained by the Authors.








