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Convergence in Wasserstein distance for empirical measures of semilinear SPDEs

Feng-yu Wang

The Annals of Applied Probability, Volume: 33, Issue: 1

Swansea University Author: Feng-yu Wang

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DOI (Published version): 10.1214/22-aap1807

Abstract

The convergence rate in Wasserstein distance is estimated for the empirical measures of symmetric semilinear SPDEs. Unlike in the finite-dimensional case that the convergence is of algebraic order in time, in the present situation the convergence is of log order with a power given by eigenvalues of...

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Published in: The Annals of Applied Probability
ISSN: 1050-5164
Published: Institute of Mathematical Statistics 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa59501
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last_indexed 2024-11-14T12:15:37Z
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spelling 2023-06-01T12:20:47.6603691 v2 59501 2022-03-05 Convergence in Wasserstein distance for empirical measures of semilinear SPDEs 6734caa6d9a388bd3bd8eb0a1131d0de Feng-yu Wang Feng-yu Wang true false 2022-03-05 The convergence rate in Wasserstein distance is estimated for the empirical measures of symmetric semilinear SPDEs. Unlike in the finite-dimensional case that the convergence is of algebraic order in time, in the present situation the convergence is of log order with a power given by eigenvalues of the underlying linear operator. Journal Article The Annals of Applied Probability 33 1 Institute of Mathematical Statistics 1050-5164 1 2 2023 2023-02-01 10.1214/22-aap1807 http://dx.doi.org/10.1214/22-aap1807 COLLEGE NANME COLLEGE CODE Swansea University 2023-06-01T12:20:47.6603691 2022-03-05T03:23:52.1180203 Faculty of Science and Engineering School of Mathematics and Computer Science - Mathematics Feng-yu Wang 1 59501__22528__f8aea41a78954d3c9dbfde3e78e50580.pdf Wang.pdf 2022-03-05T03:26:46.2374485 Output 285988 application/pdf Accepted Manuscript true true eng
title Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
spellingShingle Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
Feng-yu Wang
title_short Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
title_full Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
title_fullStr Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
title_full_unstemmed Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
title_sort Convergence in Wasserstein distance for empirical measures of semilinear SPDEs
author_id_str_mv 6734caa6d9a388bd3bd8eb0a1131d0de
author_id_fullname_str_mv 6734caa6d9a388bd3bd8eb0a1131d0de_***_Feng-yu Wang
author Feng-yu Wang
author2 Feng-yu Wang
format Journal article
container_title The Annals of Applied Probability
container_volume 33
container_issue 1
publishDate 2023
institution Swansea University
issn 1050-5164
doi_str_mv 10.1214/22-aap1807
publisher Institute of Mathematical Statistics
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Mathematics{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Mathematics
url http://dx.doi.org/10.1214/22-aap1807
document_store_str 1
active_str 0
description The convergence rate in Wasserstein distance is estimated for the empirical measures of symmetric semilinear SPDEs. Unlike in the finite-dimensional case that the convergence is of algebraic order in time, in the present situation the convergence is of log order with a power given by eigenvalues of the underlying linear operator.
published_date 2023-02-01T02:26:34Z
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score 11.04748

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