Interacting measure-valued diffusions and their long-term behavior

The focus of this dissertation is a class of random processes known as interacting measure-valued stochastic processes. These processes are related to another class of stochastic processes known as superprocesses. Both superprocesses and interacting measure-valued stochastic processes arise natura...

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Main Author: Gill, Hardeep Singh
Language:English
Published: University of British Columbia 2011
Online Access:http://hdl.handle.net/2429/36923
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-BVAU.-369232013-06-05T04:19:49ZInteracting measure-valued diffusions and their long-term behaviorGill, Hardeep SinghThe focus of this dissertation is a class of random processes known as interacting measure-valued stochastic processes. These processes are related to another class of stochastic processes known as superprocesses. Both superprocesses and interacting measure-valued stochastic processes arise naturally from branching particle systems as scaling limits. A branching particle system is a collection of particles that propagate randomly through space, and that upon death give birth to a random number of particles (children). Therefore when the populations of the particle system and branching rate are large one can often use a superprocess to approximate it and carry out calculations that would be very difficult otherwise. There are many branching particle systems which do not satisfy the strong independence assumptions underlying superprocesses and thus are more difficult to study mathematically. This dissertation attempts to address two measure-valued processes with different types of dependencies (interactions) that the associated particles exhibit. In both cases, the method used to carry out this work is called Perkins' historical stochastic calculus, and has never before been used to investigate interacting measure-valued processes of these types. That is, we construct the measure-valued stochastic process associated with an interacting branching particle system directly without taking a scaling limit. The first type of interaction we consider is when all particles share a common chaotic drift from being immersed in the same medium, as well as having other types of individual interactions. The second interaction involves particles that attract to or repel from the center of mass of the entire population. For measure-valued processes with this latter interaction, we study the long-term behavior of the process and show that it displays some types of equilibria.University of British Columbia2011-08-26T17:52:20Z2011-08-26T17:52:20Z20112011-08-262011-11Electronic Thesis or Dissertationhttp://hdl.handle.net/2429/36923eng
collection NDLTD
language English
sources NDLTD
description The focus of this dissertation is a class of random processes known as interacting measure-valued stochastic processes. These processes are related to another class of stochastic processes known as superprocesses. Both superprocesses and interacting measure-valued stochastic processes arise naturally from branching particle systems as scaling limits. A branching particle system is a collection of particles that propagate randomly through space, and that upon death give birth to a random number of particles (children). Therefore when the populations of the particle system and branching rate are large one can often use a superprocess to approximate it and carry out calculations that would be very difficult otherwise. There are many branching particle systems which do not satisfy the strong independence assumptions underlying superprocesses and thus are more difficult to study mathematically. This dissertation attempts to address two measure-valued processes with different types of dependencies (interactions) that the associated particles exhibit. In both cases, the method used to carry out this work is called Perkins' historical stochastic calculus, and has never before been used to investigate interacting measure-valued processes of these types. That is, we construct the measure-valued stochastic process associated with an interacting branching particle system directly without taking a scaling limit. The first type of interaction we consider is when all particles share a common chaotic drift from being immersed in the same medium, as well as having other types of individual interactions. The second interaction involves particles that attract to or repel from the center of mass of the entire population. For measure-valued processes with this latter interaction, we study the long-term behavior of the process and show that it displays some types of equilibria.
author Gill, Hardeep Singh
spellingShingle Gill, Hardeep Singh
Interacting measure-valued diffusions and their long-term behavior
author_facet Gill, Hardeep Singh
author_sort Gill, Hardeep Singh
title Interacting measure-valued diffusions and their long-term behavior
title_short Interacting measure-valued diffusions and their long-term behavior
title_full Interacting measure-valued diffusions and their long-term behavior
title_fullStr Interacting measure-valued diffusions and their long-term behavior
title_full_unstemmed Interacting measure-valued diffusions and their long-term behavior
title_sort interacting measure-valued diffusions and their long-term behavior
publisher University of British Columbia
publishDate 2011
url http://hdl.handle.net/2429/36923
work_keys_str_mv AT gillhardeepsingh interactingmeasurevalueddiffusionsandtheirlongtermbehavior
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