Skip to content
DraconiticResearch
Search Sources API
194,161 studies31 sourcesUpdated 56 min ago
PreprintCC BY 4.0arXiv

Optimal transportation under McKean-Vlasov dynamics

Abstract

We study a broad class of stochastic transport problems under controlled McKean-Vlasov dynamics, allowing control of both drift and volatility, with weak terminal constraints. In contrast to the classical Schrödinger problem, the reference dynamics depend on the evolving law of the process, leading to nonlinear optimization problems on path space, while the terminal constraint is formulated through weak optimal transport, permitting a flexible treatment of distributional targets. This framework encompasses several problems of current interest, including the mean field Schrödinger problem, martingale optimal transport, and Schrödinger-Bass bridges. We establish three main results. First, we prove the existence of optimal controls under general coercivity, continuity, and convexity assumptions. Second, we derive a convex dual representation that extends weak Kantorovich duality and stochastic optimal transport duality to controlled McKean-Vlasov dynamics. Finally, for the mean field Schrödinger problem, we prove convergence, at the level of value functions, of the associated finite-particle Schrödinger bridge problems to the mean field limit, thereby identifying the nonlinear problem as the exact infinite-particle limit of finite-particle Schrödinger bridges. As a byproduct, we establish the existence of an optimal mean field Schrödinger potential, providing a variational foundation for duality in nonlinear stochastic transport.

Related

  1. Projected McKean--Vlasov Dynamics for Entropic Weak Optimal Transport
    Nathan Sauldubois, Xin Zhang
    arXivPreprintarXiv licenceFull textOptimisation & controlProbabilityarXiv
  2. Solution to a fully coupled McKean-Vlasov forward-backward stochastic difference equation and applications to optimal control with law-delay
    Duocheng Wang
    arXivPreprintarXiv licenceFull textProbabilityarXiv
  3. Soft-confinement approximation of no-flux McKean-Vlasov dynamics
    Geuntaek Seo, Yeoneung Kim, Beomjun Choi
    arXivPreprintarXiv licenceFull textAnalysis & PDEsProbabilityarXiv
  4. State-law dynamics of McKean-Vlasov stochastic reaction-diffusion equations on ℝn: pullback random attractors and zero-noise stability
    Guifen Liu, Yangrong Li
    arXivPreprintarXiv licenceFull textAnalysis & PDEsProbabilityarXiv
  5. Learning Generative Dynamics with Soft Path-Law Constraints: A McKean-Vlasov FBSDE Approach
    Samer El Boustany, Samy Mekkaoui, Yadh Hafsi +2
    arXivPreprintCC BY 4.0Full textOptimisation & controlStatisticsarXiv
BibTeX
@misc{hernandez2026optimal,
  title = {{Optimal transportation under McKean-Vlasov dynamics}},
  author = {Camilo Hernández and Ludovic Tangpi},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.17626},
  eprint = {2610.17626},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.17626},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Optimal transportation under McKean-Vlasov dynamics
AU  - Camilo Hernández
AU  - Ludovic Tangpi
PY  - 2026
DA  - 2026/10/13
PB  - arXiv
DO  - 10.48550/arxiv.2610.17626
UR  - https://arxiv.org/abs/2610.17626
AB  - We study a broad class of stochastic transport problems under controlled McKean-Vlasov dynamics, allowing control of both drift and volatility, with weak terminal constraints. In contrast to the classical Schrödinger problem, the reference dynamics depend on the evolving law of the process, leading to nonlinear optimization problems on path space, while the terminal constraint is formulated through weak optimal transport, permitting a flexible treatment of distributional targets. This framework encompasses several problems of current interest, including the mean field Schrödinger problem, martingale optimal transport, and Schrödinger-Bass bridges. We establish three main results. First, we prove the existence of optimal controls under general coercivity, continuity, and convexity assumptions. Second, we derive a convex dual representation that extends weak Kantorovich duality and stochastic optimal transport duality to controlled McKean-Vlasov dynamics. Finally, for the mean field Schrödinger problem, we prove convergence, at the level of value functions, of the associated finite-particle Schrödinger bridge problems to the mean field limit, thereby identifying the nonlinear problem as the exact infinite-particle limit of finite-particle Schrödinger bridges. As a byproduct, we establish the existence of an optimal mean field Schrödinger potential, providing a variational foundation for duality in nonlinear stochastic transport.
ER  -