EconPapers    
Economics at your fingertips  
 

Traversing the Schrödinger Bridge Strait: Robert Fortet’s Marvelous Proof Redux

Montacer Essid () and Michele Pavon ()
Additional contact information
Montacer Essid: New York University
Michele Pavon: Università di Padova

Journal of Optimization Theory and Applications, 2019, vol. 181, issue 1, No 2, 23-60

Abstract: Abstract In the early 1930s, Erwin Schrödinger, motivated by his quest for a more classical formulation of quantum mechanics, posed a large deviation problem for a cloud of independent Brownian particles. He showed that the solution to the problem could be obtained through a system of two linear equations with nonlinear coupling at the boundary (Schrödinger system). Existence and uniqueness for such a system, which represents a sort of bottleneck for the problem, was first established by Fortet in 1938/1940 under rather general assumptions by proving convergence of an ingenious but complex approximation method. It is the first proof of what are nowadays called Sinkhorn-type algorithms in the much more challenging continuous case. Schrödinger bridges are also an early example of the maximum entropy approach and have been more recently recognized as a regularization of the important optimal mass transport problem. Unfortunately, Fortet’s contribution is by and large ignored in contemporary literature. This is likely due to the complexity of his approach coupled with an idiosyncratic exposition style and due to missing details and steps in the proofs. Nevertheless, Fortet’s approach maintains its importance to this day as it provides the only existing algorithmic proof, in the continuous setting, under rather mild assumptions. It can be adapted, in principle, to other relevant optimal transport problems. It is the purpose of this paper to remedy this situation by rewriting the bulk of his paper with all the missing passages and in a transparent fashion so as to make it fully available to the scientific community. We consider the problem in $${\mathbb {R}}^d$$ R d rather than in $${\mathbb {R}}$$ R and use as much as possible his notation to facilitate comparison.

Keywords: Schrödinger system; Large deviations; Iterative algorithm (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s10957-018-1436-9 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:181:y:2019:i:1:d:10.1007_s10957-018-1436-9

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2

Access Statistics for this article

Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull

More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2019-11-06
Handle: RePEc:spr:joptap:v:181:y:2019:i:1:d:10.1007_s10957-018-1436-9