Abstract:In this paper we prove that, within the framework of RCD * (K, N ) spaces with N < ∞, the entropic cost (i.e. the minimal value of the Schrödinger problem) admits: -a threefold dynamical variational representation, in the spirit of the Benamou-Brenier formula for the Wasserstein distance;-a Hamilton-Jacobi-Bellman dual representation, in line with Bobkov-Gentil-Ledoux and Otto-Villani results on the duality between Hamilton-Jacobi and continuity equation for optimal transport; -a Kantorovich-type duality formu… Show more
“…shown in [5,9] for Setting 1-(a) and in [14] for rather general metric measure spaces including Setting 1-(b). By the very definition of ϑ ε t and since ε log ρ ε t = ϕ ε t + ψ ε t , this implies…”
Section: )mentioning
confidence: 99%
“…Namely: -all the regularity and integrability results concerning Schrödinger potentials and entropic interpolations mentioned in Section 2 as well as the dynamic representation of the entropic cost; -the regularizing and contraction properties of (T t ); -the existence of 'good' cut-off functions; -the Benamou-Brenier formula and the Bochner-Lichnerowicz-Weitzenböck inequality. The reader is addressed to [13], [14] for the first point and to [10] for all the others.…”
Section: Final Remarks and Commentsmentioning
confidence: 99%
“…Next lemma provides related regularity and growth controls. Its proof is strongly inspired by [12], [13], [14] and [19]; we thus address the reader to these articles for more details.…”
We present a pathwise proof of the HWI inequality which is based on entropic interpolations rather than displacement ones. Unlike the latter, entropic interpolations are regular both in space and time. Consequently, our approach is closer to the Otto-Villani heuristics, presented in the first part of the article [23], than the original rigorous proof presented in the second part of [23].Ric V,N := Ric g − (N − n)Hess(1.4)Relative entropy. For any two probability measures p and r on a measurable space Z the relative entropy of p with respect to r is defined bywhere it is understood that this quantity is infinite when p is not absolutely continuous with respect to r. In our case, Z will be X, X × X or C([0, 1], X).
“…shown in [5,9] for Setting 1-(a) and in [14] for rather general metric measure spaces including Setting 1-(b). By the very definition of ϑ ε t and since ε log ρ ε t = ϕ ε t + ψ ε t , this implies…”
Section: )mentioning
confidence: 99%
“…Namely: -all the regularity and integrability results concerning Schrödinger potentials and entropic interpolations mentioned in Section 2 as well as the dynamic representation of the entropic cost; -the regularizing and contraction properties of (T t ); -the existence of 'good' cut-off functions; -the Benamou-Brenier formula and the Bochner-Lichnerowicz-Weitzenböck inequality. The reader is addressed to [13], [14] for the first point and to [10] for all the others.…”
Section: Final Remarks and Commentsmentioning
confidence: 99%
“…Next lemma provides related regularity and growth controls. Its proof is strongly inspired by [12], [13], [14] and [19]; we thus address the reader to these articles for more details.…”
We present a pathwise proof of the HWI inequality which is based on entropic interpolations rather than displacement ones. Unlike the latter, entropic interpolations are regular both in space and time. Consequently, our approach is closer to the Otto-Villani heuristics, presented in the first part of the article [23], than the original rigorous proof presented in the second part of [23].Ric V,N := Ric g − (N − n)Hess(1.4)Relative entropy. For any two probability measures p and r on a measurable space Z the relative entropy of p with respect to r is defined bywhere it is understood that this quantity is infinite when p is not absolutely continuous with respect to r. In our case, Z will be X, X × X or C([0, 1], X).
“…[41,45]), optimal transport theory (e.g. [5,16,18,20,21,32,44,51,54,55,58]), data sciences (e.g. [34,39,40,56,57,62,63] see also the book [28] and references therein).…”
This paper exploit the equivalence between the Schrödinger Bridge problem (Léonard in J Funct Anal 262:1879–1920, 2012; Nelson in Phys Rev 150:1079, 1966; Schrödinger in Über die umkehrung der naturgesetze. Verlag Akademie der wissenschaften in kommission bei Walter de Gruyter u, Company, 1931) and the entropy penalized optimal transport (Cuturi in: Advances in neural information processing systems, pp 2292–2300, 2013; Galichon and Salanié in: Matching with trade-offs: revealed preferences over competing characteristics. CEPR discussion paper no. DP7858, 2010) in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a priori estimates which are consistent in the limit when the regularization parameter goes to zero. In particular, we find a new proof of the existence of maximizing entropic-potentials and therefore, the existence of a solution of the Schrödinger system. Our method extends also when we have more than two marginals: the main new result is the proof that the Sinkhorn algorithm converges even in the continuous multi-marginal case. This provides also an alternative proof of the convergence of the Sinkhorn algorithm in two marginals.
“…Our dynamical framework is however equivalent, as observed in numerous papers -see for instance [20, Section IV], [26,Cor. 5.8] or the introduction of [27].…”
This paper is concerned with six variational problems and their mutual connections: The quadratic Monge-Kantorovich optimal transport, the Schrödinger problem, Brenier's relaxed model for incompressible fluids, the so-called Brödinger problem recently introduced by M. Arnaudon & al. [3], the multiphase Brenier model, and the multiphase Brödinger problem. All of them involve the minimization of a kinetic action and/or a relative entropy of some path measures with respect to the reversible Brownian motion. As the viscosity parameter ν → 0 we establish Gammaconvergence relations between the corresponding problems, and prove the convergence of the associated pressures arising from the incompressibility constraints. We also present new results on the time-convexity of the entropy for some of the dynamical interpolations. Along the way we extend previous results by H. Lavenant [30] and J-D. Benamou & al. [10].
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