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We introduce folded optimal transport, as a method to extend a cost or distance defined on the extreme boundary of a convex to the whole convex, related to convex extension. This construction broadens the framework of standard optimal…

Functional Analysis · Mathematics 2026-01-21 Thomas Borsoni

We introduce a new class of distances between nonnegative Radon measures in Euclidean spaces. They are modeled on the dynamical characterization of the Kantorovich-Rubinstein-Wasserstein distances proposed by Benamou-Brenier and provide a…

Functional Analysis · Mathematics 2014-09-16 Jean Dolbeault , Bruno Nazaret , Giuseppe Savare

In this paper we give a new proof of the (strong) displacement convexity of a class of integral functionals defined on a compact Riemannian manifold satisfying a lower Ricci curvature bound. Our approach does not rely on existence and…

Analysis of PDEs · Mathematics 2014-09-16 Sara Daneri , Giuseppe Savare

The paper proves transportation inequalities for probability measures on spheres for the Wasserstein metrics with respect to cost functions that are powers of the geodesic distance. Let $\mu$ be a probability measure on the sphere ${\bf…

Probability · Mathematics 2024-09-24 Gordon Blower

The paper considers the Euler system of PDE on a smooth compact Riemannian manifold of positive curvature without boundary, and the sphere ${\mathbb{S}}^2$ in particular. The paper interprets the Euler equations as a transport problem for…

Analysis of PDEs · Mathematics 2020-11-24 Gordon Blower

A version of the Uncertainty Principle says: There does not exist a non zero function in $L_p(\mathbb{R}^d)$ if its Fourier transform is supported by a set of finite $\alpha$-Hausdorff measure with $\alpha<2d/p$. This UP does not hold at…

Classical Analysis and ODEs · Mathematics 2026-04-30 Nikita Dobronravov

We consider Monge-Kantorovich optimal transport problems on $\mathbb{R}^d$, $d\ge 1$, with a convex cost function given by the cumulant generating function of a probability measure. Examples include the Wasserstein-2 transport whose cost…

Probability · Mathematics 2017-08-29 Soumik Pal

We discuss the classical problem of measuring the regularity of distribution of sets of $N$ points in $\mathbb{T}^d$. A recent line of investigation is to study the cost ($=$ mass $\times$ distance) necessary to move Dirac measures placed…

Classical Analysis and ODEs · Mathematics 2020-09-29 Louis Brown , Stefan Steinerberger

In this paper we consider the mass transport problem in the case of a relativistic cost; we can establish the continuity of the total cost, together with a general estimate about the directions in which the mass can actually move, under…

Optimization and Control · Mathematics 2016-12-20 Jean Louet , Aldo Pratelli , Florian Zeisler

We approach uncertainty principles of Cowling-Price-Heis-\\enberg-type as a variational principle on modulation spaces. In our discussion we are naturally led to compact localization operators with symbols in modulation spaces. The optimal…

Functional Analysis · Mathematics 2023-03-21 Nuno Costa Dias , Franz Luef , João Nuno Prata

We propose a fundamental metric for measuring the distance between two distributions. This metric, referred to as the decision-focused (DF) divergence, is tailored to stochastic linear optimization problems in which the objective…

Statistics Theory · Mathematics 2026-02-04 Suhan Liu , Mo Liu

The stability of solutions to optimal transport problems under variation of the measures is fundamental from a mathematical viewpoint: it is closely related to the convergence of numerical approaches to solve optimal transport problems and…

Numerical Analysis · Mathematics 2022-07-25 Anatole Gallouët , Quentin Mérigot , Boris Thibert

We consider particles prepared by the von Neumann-L\"uders projection. For those particles the standard deviation of the momentum is discussed. We show that infinite standard deviations are not exceptions but rather typical. A necessary and…

Quantum Physics · Physics 2010-06-29 Thomas Schürmann , Ingo Hoffmann

The Heisenberg uncertainty principle is one of the fundamental pillars of quantum mechanics and quantum field theory. It is normally introduced by postulating the commutation relations $[\hat{x}^i, \hat{p}^j] = i\hbar \delta^{ij}$. However,…

High Energy Physics - Phenomenology · Physics 2026-01-29 Ezequiel Valero , Hector Gisbert , Victor Ilisie

The purpose of this short note is to exhibit a new connection between the Heisenberg Uncertainty Principle on the line and the Breitenberger Uncertainty Principle on the circle, by considering the commutator of the multiplication and…

Functional Analysis · Mathematics 2013-07-19 Nils Byrial Andersen

The inverse optimal transport problem is to find the underlying cost function from the knowledge of optimal transport plans. While this amounts to solving a linear inverse problem, in this work we will be concerned with the nonlinear…

Optimization and Control · Mathematics 2025-09-03 Alberto González-Sanz , Michel Groppe , Axel Munk

We revisit the uncertainty principle from the point of view suggested by A. Wigderson and Y. Wigderson. This approach is based on a primary uncertainty principle from which one can derive several inequalities expressing the impossibility of…

Functional Analysis · Mathematics 2025-04-30 Nuno Costa Dias , Franz Luef , João Nuno Prata

Extending a recent result by Frank and Lieb, we show an entropic uncertainty principle for mixed states in a Hilbert space relatively to pairs of positive operator valued measures that are independent in some sense. This yields…

Functional Analysis · Mathematics 2012-05-29 Michel Rumin

Inverse transport theory concerns the reconstruction of the absorption and scattering coefficients in a transport equation from knowledge of the albedo operator, which models all possible boundary measurements. Uniqueness and stability…

Analysis of PDEs · Mathematics 2017-03-03 Guillaume Bal , Alexandre Jollivet

Let $L=\DD+Z$ for a $C^1$ vector field $Z$ on a complete Riemannian manifold possibly with a boundary. By using the uniform distance, a number of transportation-cost inequalities on the path space for the (reflecting) $L$-diffusion process…

Probability · Mathematics 2009-08-21 Feng-Yu Wang