Virginia Tech
First Exit Time Analysis for the Stochastic Reaction Diffusion Process in a One Dimensional Domain
Abstract
dc:description.abstractRecent advances in modeling stochastic reaction–diffusion (RD) process have focused on particle-based and master equation formulations. While these models offer strong theoretical foundation, a practical challenge remains: how does the choice of spatial discretization affect the accuracy and computational efficiency of simulation results, particularly when estimating first exit times. This thesis addresses this research gap by investigating the accuracy of first exit time estimates in one-dimensional stochastic RD systems. We design and analyze three simplified models using stochastic simulations: (1) model 1: pure diffusion, (2) model 2: diffusion with monomolecular reaction, and (3) model 3: diffusion with bimolecular reaction. We conduct theoretical study for the mean first exit times and evaluate them based on these models. Our results show that strictly following the Gillespie SSA is not necessary to obtain accurate results under certain conditions and a moderate discretizations size (e.g., K ≥ 5) already provides highly accurate estimates for first exit times. Our results can guide efficient and accurate simulation of RD systems.
Degree
thesis:*- Name thesis:degree_name
- Master of Science
- Level thesis:degree_level
- masters
- Discipline thesis:degree_discipline
- Computer Science & Applications
- Department dc:contributor.department
- Computer Science and#38; Applications
- Grantor dc:publisher
- Virginia Tech
- Year dc:date.issued
- 2025
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Zhou, Daodao
- Chair dc:contributor.committeechair
-
- Cao, Young
- Committee members dc:contributor.committeemember
-
- Onufriev, Alexey
- Sandu, Adrian
Subjects
dc:subject × 3Rights
dc:rights- Statement dc:rights
-
- In Copyright
- Licence dc:rights.uri
- Language dc:language.iso
- en
Identifiers
dc:identifier.*- Dc Identifier Other
- vt_gsexam:44772
- OAI identifier oai:identifier
- oai:vtechworks.lib.vt.edu:10919/138271