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Fractional stochastic partial differential equation for random tangent fields on the sphere

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posted on 2025-03-04, 04:47 authored by VV Anh, Andriy OlenkoAndriy Olenko, YG Wang
This paper develops a fractional stochastic partial differential equation (SPDE) to model the evolution of a random tangent vector field on the unit sphere. The SPDE is governed by a fractional diffusion operator to model the Lévy-type behaviour of the spatial solution, a fractional derivative in time to depict the inter-mittency of its temporal solution, and is driven by vector-valued fractional Brownian motion on the unit sphere to characterize its temporal long-range dependence. The solution to the SPDE is presented in the form of the Karhunen–Loève expansion in terms of vector spherical harmonics. Its covariance matrix function is established as a tensor field on the unit sphere that is an expansion of Legendre tensor kernels. The variance of the increments and approximations to the solutions are studied and convergence rates of the approximation errors are given. It is demonstrated how these convergence rates depend on the decay of the power spectrum and variances of the fractional Brownian motion.

Funding

This research was partially supported under the Australian Research Council's Discovery Projects funding scheme (project number DP160101366). The third author acknowledges the support of funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement no 757983).

History

Publication Date

2021-09-24

Journal

Theory of Probability and Mathematical Statistics

Volume

104

Pagination

3-22

Publisher

American Mathematical Society

ISSN

0094-9000

Rights Statement

First published in Theor. Probability and Math. Statist. 104 (September 2021), published by the American Mathematical Society. © 2021 Taras Shevchenko National University of Kyiv. “An author’s accepted manuscript (AAM) or other draft version of the work, either before or after peer review, may be reproduced under a CC BY Creative Commons License by any means for educational and scientific purposes by the author(s). This means that the pre-publication draft of the work may be posted on the author’s personal website, contributed to the author’s institutional repository, and/or posted on pre-print servers such as arXiv.org, all provided that no commercial use of the material is made (no fees may be charged for access to or use of the material) and no derivative works are included.”

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