Abstract
We use probabilistic methods to study properties of mean-field models, which arise as large-scale limits of certain particle systems with mean-field interaction. The underlying particle system is such that n particles move forward on the real line. Specifically, each particle 'jumps forward' at some time points, with the instantaneous rate of jumps given by a decreasing function of the particle's location quantile within the overall distribution of particle locations. A mean-field model describes the evolution of the particles' distribution when n is large. It is essentially a solution to an integro-differential equation within a certain class. Our main results concern the existence and uniqueness of-and attraction to-mean-field models which are traveling waves, under general conditions on the jump-rate function and the jump-size distribution.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 245-274 |
| Number of pages | 30 |
| Journal | Advances in Applied Probability |
| Volume | 55 |
| Issue number | 1 |
| Early online date | Sep 27 2022 |
| DOIs | |
| State | Published - Mar 27 2023 |
Keywords
- Particle system
- asymptotic behavior
- distributed system synchronization
- mean-field model dynamics
ASJC Scopus subject areas
- Statistics and Probability
- Applied Mathematics
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