Full metadata
Title
From Stochastic N Particle Systems to Deterministic Differential Equations - with Applications to Econophysics and Averaging Dynamics
Description
The mechanisms behind the emergence of collective behaviors arising from physics, biology, economics and many other related fields have drawn a lot of attention among the applied math community in the last few decades. Broadly speaking, collective behaviors in natural, life and social sciences are all modelled by interacting particle systems, in which a bulk of N particles are engaging in some simple binary pairwise interactions. In this dissertation, some prototypical interacting particle systems having applications in econophysics and statistical averaging dynamics are investigated. It is also emphasized that there is an increasing tendency among the applied math community to apply tools or concepts for studying many particle systems to the (rigorous) investigation of artificial (deep) neural networks.
Date Created
2022
Contributors
- Cao, Fei (Author)
- Motsch, Sebastien S.M. (Thesis advisor)
- Lanchier, Nicolas N.L. (Committee member)
- Jones, Donald D.J. (Committee member)
- Hahn, Paul P.H. (Committee member)
- Fricks, John J.F. (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
214 pages
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.168641
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2022
Field of study: Applied Mathematics
System Created
- 2022-08-22 05:38:58
System Modified
- 2022-08-22 05:39:21
- 1 year 8 months ago
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