Propagation of chaos for mean field Schr"odinger problems
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Abstract (arXiv)
In this work, we study the mean field Schr"odinger problem from a purely probabilistic point of view by exploiting its connection to stochastic control theory for McKean-Vlasov diffusions. Our main result shows that the mean field Schr"odinger problem arises as the limit of ``standard'' Schr"odinger problems over interacting particles. Due to the stochastic maximum principle and a suitable penalization procedure, the result follows as a consequence of novel (quantitative) propagation of chaos results for forward-backwards particle systems. The approach described in the paper seems flexible enough to address other questions in the theory. For instance, our stochastic control technique further allows us to solve the mean field Schr"odinger problem and characterize its solution, the mean field Schr"odinger bridge, by a forward-backward planning equation.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Apr 2023.
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridgecited by 12
- 2025Schr"odinger bridge for generative AI: Soft-constrained formulation and convergence analysiscited by 2
- 2026Mean-Field Path-Integral Diffusion: From Samples to Interacting Agentscited by 2
- 2026Nonlocal Mean Field Schr"odinger Bridge with Learned Interactionscited by 1
- 2026Schr"odinger Bridges over Kinetic Swarming Modelscited by 0
- 2026Schr"odinger Bridges over Kinetic Swarming Models26 Aug 2026
- 2026Nonlocal Mean Field Schr"odinger Bridge with Learned Interactions2 Jun 2026
- 2026Mean-Field Path-Integral Diffusion: From Samples to Interacting Agents23 Feb 2026
- 2025Schr"odinger bridge for generative AI: Soft-constrained formulation and convergence analysis13 Oct 2025
- 2025Modeling Cell Dynamics and Interactions with Unbalanced Mean Field Schr"odinger Bridge16 May 2025