Donsker-Varadhan large deviations for path-distribution dependent SPDEs
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Article number | 125000 |
Journal / Publication | Journal of Mathematical Analysis and Applications |
Volume | 499 |
Issue number | 1 |
Online published | 26 Jan 2021 |
Publication status | Published - 1 Jul 2021 |
Link(s)
Abstract
As an important tool characterizing the long time behavior of Markov processes, the Donsker-Varadhan LDP (large deviation principle) does not directly apply to distribution dependent SDEs/SPDEs since the solutions are not standard Markovian. We establish this type LDP for several different models of distribution dependent SDEs/SPDEs which may also with memories, by comparing the original equations with the corresponding distribution independent ones. As preparations, the existence, uniqueness and exponential convergence are also investigated for path-distribution dependent SPDEs which should be interesting by themselves.
Research Area(s)
- Donsker-Varadhan LDP, Path-distribution dependent SDEs, Warsserstein distance
Citation Format(s)
Donsker-Varadhan large deviations for path-distribution dependent SPDEs. / Ren, Panpan; Wang, Feng-Yu.
In: Journal of Mathematical Analysis and Applications, Vol. 499, No. 1, 125000, 01.07.2021.
In: Journal of Mathematical Analysis and Applications, Vol. 499, No. 1, 125000, 01.07.2021.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review