A regularity theory for stochastic partial differential equations with a super-linear diffusion coefficient and a spatially homogeneous colored noise
Jae-Hwan Choi and
Beom-Seok Han
Stochastic Processes and their Applications, 2021, vol. 135, issue C, 1-30
Abstract:
Existence, uniqueness, and regularity of a strong solution are obtained for stochastic PDEs with a colored noise F and its super-linear diffusion coefficient: du=(aijuxixj+biuxi+cu)dt+ξ|u|1+λdF,(t,x)∈(0,∞)×Rd, where λ≥0 and the coefficients depend on (ω,t,x). The strategy of handling nonlinearity of the diffusion coefficient is to find a sharp estimation for a general Lipschitz case and apply it to the super-linear case. Moreover, investigation for the estimate provides a range of λ, a sufficient condition for the unique solvability, where the range depends on the spatial covariance of F and the spatial dimension d.
Keywords: Stochastic partial differential equation; Nonlinear; Spatially homogeneous Gaussian noise; Hölder regularity; Lp regularity (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304414921000120
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:135:y:2021:i:c:p:1-30
Ordering information: This journal article can be ordered from
http://http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spa.2021.01.006
Access Statistics for this article
Stochastic Processes and their Applications is currently edited by T. Mikosch
More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().