Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98851
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Applied Mathematics | en_US |
| dc.creator | Cui, J | en_US |
| dc.creator | Liu, S | en_US |
| dc.creator | Zhou, H | en_US |
| dc.date.accessioned | 2023-06-01T06:04:26Z | - |
| dc.date.available | 2023-06-01T06:04:26Z | - |
| dc.identifier.issn | 1040-7294 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/98851 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Springer New York LLC | en_US |
| dc.rights | © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023 | en_US |
| dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10884-023-10264-4. | en_US |
| dc.subject | Density manifold | en_US |
| dc.subject | Stochastic Hamiltonian flow | en_US |
| dc.subject | Wong–Zakai approximation | en_US |
| dc.title | Stochastic Wasserstein Hamiltonian flows | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 3885 | en_US |
| dc.identifier.epage | 3921 | en_US |
| dc.identifier.volume | 36 | en_US |
| dc.identifier.issue | 4 | en_US |
| dc.identifier.doi | 10.1007/s10884-023-10264-4 | en_US |
| dcterms.abstract | In this paper, we study the stochastic Hamiltonian flow in Wasserstein manifold, the probability density space equipped with L2-Wasserstein metric tensor, via the Wong–Zakai approximation. We begin our investigation by showing that the stochastic Euler–Lagrange equation, regardless it is deduced from either the variational principle or particle dynamics, can be interpreted as the stochastic kinetic Hamiltonian flows in Wasserstein manifold. We further propose a novel variational formulation to derive more general stochastic Wasserstein Hamiltonian flows, and demonstrate that this new formulation is applicable to various systems including the stochastic Schrödinger equation, Schrödinger equation with random dispersion, and Schrödinger bridge problem with common noise. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of dynamics and differential equations, Dec. 2024, v. 36, no. 4, p.3885-3921 | en_US |
| dcterms.isPartOf | Journal of dynamics and differential equations | en_US |
| dcterms.issued | 2024-12 | - |
| dc.identifier.scopus | 2-s2.0-85152906386 | - |
| dc.identifier.eissn | 1572-9222 | en_US |
| dc.description.validate | 202306 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a2051 | - |
| dc.identifier.SubFormID | 46383 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The research is partially supported by Georgia Tech Mathematics Application Portal (GT-MAP) and by research grants NSF DMS-1830225, and ONR N00014-21-1-2891, the start-up funds P0039016 and internal grants (P0041274,P0045336) from Hong Kong Polytechnic University, the CAS AMSS-PolyU Joint Laboratory of Applied Mathematics and the grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (PolyU25302822 for ECS project). | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Cui_Stochastic_Wasserstein_Hamiltonian.pdf | Pre-Published version | 323.96 kB | Adobe PDF | View/Open |
Page views
115
Last Week
0
0
Last month
Citations as of Oct 5, 2025
Downloads
70
Citations as of Oct 5, 2025
SCOPUSTM
Citations
6
Citations as of Oct 24, 2025
WEB OF SCIENCETM
Citations
6
Citations as of Oct 23, 2025
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



