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We study the optimal transport problem in sub-Riemannian manifolds where the cost function is given by the square of the sub-Riemannian distance. Under appropriate assumptions, we generalize Brenier-McCann's Theorem proving existence and…

Optimization and Control · Mathematics 2009-10-15 Alessio Figalli , Ludovic Rifford

This paper defines a new transport metric over the space of non-negative measures. This metric interpolates between the quadratic Wasserstein and the Fisher-Rao metrics and generalizes optimal transport to measures with different masses. It…

Analysis of PDEs · Mathematics 2015-07-13 Lenaic Chizat , Bernhard Schmitzer , Gabriel Peyré , François-Xavier Vialard

We investigate the synthetic metric spacetime structure of the sub-Lorentzian Heisenberg group and we study the optimal transport problem in this space. The sub-Lorentzian version of Brenier's theorem is established in this setting.…

Metric Geometry · Mathematics 2025-04-07 Samuël Borza , Wilhelm Klingenberg , Patrick Wood

When approximating a function that depends on a parameter, one encounters many practical examples where linear interpolation or linear approximation with respect to the parameters prove ineffective. This is particularly true for responses…

Numerical Analysis · Mathematics 2018-12-27 Donsub Rim , Kyle T. Mandli

We analyze the behavior of the thermal conductivity in quasi-two dimensional superconductors with line nodes. Motivated by measurements of the anisotropy between the interplane and intraplane thermal transport in CeIrIn_5 we show that a…

Superconductivity · Physics 2013-05-29 I. Vekhter , A. Vorontsov

We establish both local and global well-posedness for the heat flow of polyharmonic maps from $R^n$ to a compact Riemannian manifold without boundary for initial data with small BMO norms.

Analysis of PDEs · Mathematics 2010-01-26 Tao Huang Changyou Wang

We study anomalous transport in a one-dimensional system with two conserved quantities in presence of thermal baths. In this system we derive exact expressions of the temperature profile and the two point correlations in steady state as…

Statistical Mechanics · Physics 2018-10-10 Priyanka , Aritra Kundu , Abhishek Dhar , Anupam Kundu

We consider the problem of optimizing heat transport through an incompressible fluid layer. Modeling passive scalar transport by advection-diffusion, we maximize the mean rate of total transport by a divergence-free velocity field. Subject…

Analysis of PDEs · Mathematics 2019-09-18 Charles R. Doering , Ian Tobasco

In this work, we develop a new framework for dynamic network flow problems based on optimal transport theory. We show that the dynamic multi-commodity minimum-cost network flow problem can be formulated as a multi-marginal optimal transport…

Optimization and Control · Mathematics 2021-06-29 Isabel Haasler , Axel Ringh , Yongxin Chen , Johan Karlsson

In this paper, we focus on the different traffic flow models that exist in literature. Due to our frequently encountered confusion among traffic engineers and policy makers, this paper goes into more detail about transportation planning…

Physics and Society · Physics 2009-09-29 Sven Maerivoet , Bart De Moor

Tunneling metal-insulator-metal (MIM) junctions can exhibit an open-circuit photovoltage (OCPV) response under illumination that may be useful for photodetection. One mechanism for photovoltage generation is hot carrier tunneling, in which…

Mesoscale and Nanoscale Physics · Physics 2023-06-19 Mahdiyeh Abbasi , Shusen Liao , Yunxuan Zhu , Douglas Natelson

Monge-Kantorovich optimal mass transport (OMT) provides a blueprint for geometries in the space of positive densities -- it quantifies the cost of transporting a mass distribution into another. In particular, it provides natural options for…

Optimization and Control · Mathematics 2015-06-16 Yongxin Chen , Tryphon T. Georgiou , Michele Pavon

We investigate heat transport in various quantum spin chains, using the projector operator technique. We find that anomalous heat transport is linked not to the integrability of the Hamiltonian, but to whether it can be mapped to a model of…

Statistical Mechanics · Physics 2015-05-18 Jinshan Wu , Mona Berciu

We explore the geometry of the Bures-Wasserstein space for potentially degenerate Gaussian measures on a separable Hilbert space. In this general setting, the optimal transport map is formally the subgradient of a convex function that is…

Functional Analysis · Mathematics 2025-12-29 Ho Yun , Yoav Zemel

In the field of optimal transport, two prominent subfields face each other: (i) unregularized optimal transport, "\`a-la-Kantorovich", which leads to extremely sparse plans but with algorithms that scale poorly, and (ii)…

Machine Learning · Computer Science 2024-02-19 Ehsan Amid , Frank Nielsen , Richard Nock , Manfred K. Warmuth

This paper considers the construction of optimal designs due to Hoel and Levine and Guest. It focuses on the relation between the theory of the uniform approximation of functions and the optimality of the designs. Some application to…

Statistics Theory · Mathematics 2014-03-21 Michel Broniatowski , Giorgio Celant

In the Monge-Kantorovich transport problem, the transport cost is expressed in terms of transport maps or transport plans, which play crucial roles there. A variant of the Monge-Kantorovich problem is the ramified (branching) transport…

Analysis of PDEs · Mathematics 2023-10-09 Qinglan Xia , Haotian Sun

We give a characterization of optimal transport plans for a variant of the usual quadratic transport cost introduced in [33]. Optimal plans are composition of a deterministic transport given by the gradient of a continuously differentiable…

Probability · Mathematics 2019-09-18 Nathael Gozlan , Nicolas Juillet

We identify a novel connection between a recently introduced pseudo-Riemannian framework for optimal mass transport and the geometry of Monge-Amp\`ere equations. We show this correspondence by application to an example from geophysical…

Mathematical Physics · Physics 2023-02-21 Roberto D'Onofrio

Estimating optimal transport maps between two distributions from respective samples is an important element for many machine learning methods. To do so, rather than extending discrete transport maps, it has been shown that estimating the…

Statistics Theory · Mathematics 2025-02-04 Clément Lalanne , Franck Iutzeler , Jean-Michel Loubes , Julien Chhor