TY - JOUR
T1 - Stochastic Wasserstein Hamiltonian Flows
AU - Cui, Jianbo
AU - Liu, Shu
AU - Zhou, Haomin
N1 - Funding Information:
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).
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/4/18
Y1 - 2023/4/18
N2 - 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.
AB - 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.
KW - Density manifold
KW - Stochastic Hamiltonian flow
KW - Wong–Zakai approximation
UR - http://www.scopus.com/inward/record.url?scp=85152906386&partnerID=8YFLogxK
U2 - 10.1007/s10884-023-10264-4
DO - 10.1007/s10884-023-10264-4
M3 - Journal article
AN - SCOPUS:85152906386
SN - 1040-7294
JO - Journal of Dynamics and Differential Equations
JF - Journal of Dynamics and Differential Equations
ER -