
TL;DR
This paper extends Xia Chen's results on the parabolic Anderson model by providing a method to compute Lyapunov exponents for all moments of order p ≥ 2, where p is any real number.
Contribution
It introduces an extension of Xia Chen's work to include all real moments p ≥ 2 for the model's Lyapunov exponents.
Findings
Extended the calculation of Lyapunov exponents to all real moments p ≥ 2
Provided a generalized approach for the parabolic Anderson model with fractional Gaussian noise
Enhanced understanding of the model's moment behavior across a continuous range of p
Abstract
We consider the parabolic Anderson model which is driven by a Gaussian noise fractional in time and having certain scaling property in the spatial variables. Recently, Xia Chen has obtained exact Lyapunov exponent for all moments of positive integer orders. In this note, we explain how to extend Xia Chen's result for all moments of order , where is any real number at least 2.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
