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We investigate the optimal mass transport problem associated to the following "ballistic" cost functional on phase space $M\times M^*$, $$ b_T(v, x):=\inf\{\langle v, \gamma (0)\rangle +\int_0^TL(\gamma (t), {\dot \gamma}(t))\, dt, \gamma…

Analysis of PDEs · Mathematics 2017-06-13 Nassif Ghoussoub

For a given Lagrangian $L:[0,T]\times M\times M^\ast\rightarrow \mathbb{R}_+$ and probability measures $\mu\in\mathcal{P}(M^\ast)$, $\nu\in \mathcal{P}(M)$, we introduce the stochastic ballistic transportation problems…

Analysis of PDEs · Mathematics 2017-12-04 Alistair Barton , Nassif Ghoussoub

We study the Lagrangian formulation of a class of the Monge-Kantorovich optimal transportation problem. It can be considered a stochastic optimal transportation problem for absolutely continuous stochastic processes. A cost function and…

Optimization and Control · Mathematics 2023-01-02 Toshio Mikami , Haruka Yamamoto

We study the optimal transport problem in the Euclidean space where the cost function is given by the value function associated with a Linear Quadratic minimization problem. Under appropriate assumptions, we generalize Brenier's Theorem…

Optimization and Control · Mathematics 2011-05-23 Ahed Hindawi , Ludovic Rifford , Jean-Baptiste Pomet

In machine learning and computer vision, optimal transport has had significant success in learning generative models and defining metric distances between structured and stochastic data objects, that can be cast as probability measures. The…

Machine Learning · Computer Science 2020-10-20 Anton Mallasto , Markus Heinonen , Samuel Kaski

We study optimal transportation of measures on compact manifolds for costs defined from convex Lagrangians. We prove that optimal transportation can be interpolated by measured Lipschitz laminations, or geometric currents. The methods are…

Dynamical Systems · Mathematics 2007-05-23 Patrick Bernard , Boris Buffoni

In this paper, we study the optimal transportation for generalized Lagrangian $L=L(x, u,t)$, and consider the cost function as following: $$c(x, y)=\inf_{\substack{x(0)=x\\x(1)=y\\u\in\mathcal{U}}}\int_0^1L(x(s), u(x(s),s), s)ds.$$ Where…

Dynamical Systems · Mathematics 2013-12-03 Ji Li , Jianlu Zhang

The optimal (Monge-Kantorovich) transportation problem is discussed from several points of view. The Lagrangian formulation extends the action of the {\em Lagrangian} $L(v,x,t)$ from the set of orbits in $\R^n$ to a set of measure-valued…

Mathematical Physics · Physics 2007-05-23 Gershon Wolansky

We consider a class of convex optimization problems modelling temporal mass transport and mass change between two given mass distributions (the so-called dynamic formulation of unbalanced transport), where we focus on those models for which…

Optimization and Control · Mathematics 2018-03-13 Bernhard Schmitzer , Benedikt Wirth

A new pairwise cost function is proposed for the optimal transport barycenter problem, adopting the form of the minimal action between two points, with a Lagrangian that takes into account an underlying probability distribution. Under this…

Computation · Statistics 2025-11-11 Zichu Wang , Esteban G. Tabak

We consider an optimal transport problem on the unit simplex whose solutions are given by gradients of exponentially concave functions and prove two main results. First, we show that the optimal transport is the large deviation limit of a…

Probability · Mathematics 2020-07-07 Soumik Pal , Ting-Kam Leonard Wong

The fundamental theorem of classical optimal transport establishes strong duality and characterizes optimizers through a complementary slackness condition. Milestones such as Brenier's theorem and the Kantorovich-Rubinstein formula are…

Probability · Mathematics 2025-01-28 Mathias Beiglböck , Gudmund Pammer , Lorenz Riess , Stefan Schrott

We investigate the optimal transport problem between probability measures when the underlying cost function is understood to satisfy a least action principle, also known as a Lagrangian cost. These generalizations are useful when connecting…

Machine Learning · Computer Science 2024-06-04 Aram-Alexandre Pooladian , Carles Domingo-Enrich , Ricky T. Q. Chen , Brandon Amos

Performing thermodynamic tasks within finite time while minimizing thermodynamic costs is a central challenge in stochastic thermodynamics. Here, we develop a unified framework for optimizing the thermodynamic cost of performing various…

Statistical Mechanics · Physics 2025-09-16 Kaito Tojo , Rihito Nagase , Ken Funo , Takahiro Sagawa

We provide a solution to the problem of optimal transport by Brownian martingales in general dimensions whenever the transport cost satisfies certain subharmonic properties in the target variable, as well as a stochastic version of the…

Analysis of PDEs · Mathematics 2020-10-07 Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer

We present a dynamical version for the multi-marginal optimal transport problem with infimal convolution cost, using the theory of Wasserstein barycentres. We show, how our formulation relates to the dynamical version of the multi-marginal…

Optimization and Control · Mathematics 2025-12-16 Friedemann Krannich

Optimal transport (OT) theory focuses, among all maps $T:\mathbb{R}^d\rightarrow \mathbb{R}^d$ that can morph a probability measure onto another, on those that are the ``thriftiest'', i.e. such that the averaged cost $c(x, T(x))$ between…

Machine Learning · Statistics 2023-02-09 Marco Cuturi , Michal Klein , Pierre Ablin

We study the convergence of an $N$-particle Markovian controlled system to the solution of a family of stochastic McKean-Vlasov control problems, either with a finite horizon or Schr\"odinger type cost functional. Specifically, under…

Probability · Mathematics 2024-05-22 Francesco C. De Vecchi , Chiara Rigoni

We develop Brenier theorems on iterated Wasserstein spaces. For a separable Hilbert space $H$ and $N\geq 1$, we construct a full-support probability $\Lambda$ on $P_2^{N}(H)= P_2(... P_2(H)...)$ that is transport regular: for every $Q$ with…

Probability · Mathematics 2025-10-27 Mathias Beiglböck , Gudmund Pammer , Stefan Schrott

We consider a stochastic transportation problem between two prescribed probability distributions (a source and a target) over processes with general drift dependence and with free end times. First, and in order to establish a dual…

Optimization and Control · Mathematics 2019-09-12 Samer Dweik , Nassif Ghoussoub , Young-Heon Kim , Aaron Zeff Palmer
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