On the Relation Between Optimal Transport and Schrödinger Bridges: A Stochastic Control Viewpoint

Yongxin Chen, Tryphon T Georgiou, Michele Pavon

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107 Scopus citations


We take a new look at the relation between the optimal transport problem and the Schrödinger bridge problem from a stochastic control perspective. Our aim is to highlight new connections between the two that are richer and deeper than those previously described in the literature. We begin with an elementary derivation of the Benamou–Brenier fluid dynamic version of the optimal transport problem and provide, in parallel, a new fluid dynamic version of the Schrödinger bridge problem. We observe that the latter establishes an important connection with optimal transport without zero-noise limits and solves a question posed by Eric Carlen in 2006. Indeed, the two variational problems differ by a Fisher information functional. We motivate and consider a generalization of optimal mass transport in the form of a (fluid dynamic) problem of optimal transport with prior. This can be seen as the zero-noise limit of Schrödinger bridges when the prior is any Markovian evolution. We finally specialize to the Gaussian case and derive an explicit computational theory based on matrix Riccati differential equations. A numerical example involving Brownian particles is also provided.

Original languageEnglish (US)
Pages (from-to)671-691
Number of pages21
JournalJournal of Optimization Theory and Applications
Issue number2
StatePublished - May 1 2016

Bibliographical note

Funding Information:
Research partially supported by the NSF under Grant ECCS-1509387, the AFOSR under Grants FA9550-12-1-0319, and FA9550-15-1-0045 and by the University of Padova Research Project CPDA 140897. Part of the research of M.P. was conducted during a stay at the Courant Institute of Mathematical Sciences of the New York University whose hospitality is gratefully acknowledged.

Publisher Copyright:
© 2015, Springer Science+Business Media New York.


  • Optimal transport
  • Schrödinger bridge
  • Stochastic control


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