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Related papers: A nonholonomic Moser theorem and optimal transport

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The geometric approach to optimal transport and information theory has triggered the interpretation of probability densities as an infinite-dimensional Riemannian manifold. The most studied Riemannian structures are Otto's metric, yielding…

Analysis of PDEs · Mathematics 2018-07-20 Martin Bauer , Sarang Joshi , Klas Modin

We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative and finite Radon measures in general topological spaces. They arise quite naturally by relaxing the marginal constraints typical of Optimal…

Optimization and Control · Mathematics 2018-10-16 Matthias Liero , Alexander Mielke , Giuseppe Savaré

Multi-marginal optimal transport enables one to compare multiple probability measures, which increasingly finds application in multi-task learning problems. One practical limitation of multi-marginal transport is computational scalability…

The Monge-Kantorovich problem for the infinite Wasserstein distance presents several peculiarities. Among them the lack of convexity and then of a direct duality. We study in dimension 1 the dual problem introduced by Barron, Bocea and…

Optimization and Control · Mathematics 2017-08-08 Luigi De Pascale , Jean Louet

We consider a one dimensional transport model with nonlocal velocity given by the Hilbert transform and develop a global well-posedness theory of probability measure solutions. Both the viscous and non-viscous cases are analyzed. Both in…

Analysis of PDEs · Mathematics 2011-11-01 J. A. Carrillo , L. C. F. Ferreira , J. C. Precioso

In this paper, we investigate the geodesic structure and the associated Kantorovich-type duality for a Benamou-Brenier-type transportation metric defined on the space of nonnegative measures over a finite reversible Markov chain. The metric…

Analysis of PDEs · Mathematics 2026-01-21 Qifan Mao , Xinyu Wang , Xiaoping Xue

We develop and study a theory of optimal transport for vector measures. We resolve in the negative a conjecture of Klartag, that given a vector measure on Euclidean space with total mass zero, the mass of any transport set is again zero. We…

Functional Analysis · Mathematics 2021-08-17 Krzysztof J. Ciosmak

We introduce a numerical method for extracting minimal geodesics along the group of volume preserving maps, equipped with the L2 metric, which as observed by Arnold solve Euler's equations of inviscid incompressible fluids. The method…

Numerical Analysis · Mathematics 2015-05-14 Quentin Mérigot , Jean-Marie Mirebeau

A Morse-Bott volume form on a manifold is a top-degree form which vanishes along a non-degenerate critical submanifold. We prove that two such forms are diffeomorphic (by a diffeomorphism fixed on the submanifold) provided that their…

Differential Geometry · Mathematics 2025-08-26 Luke Volk , Boris Khesin

We show that the Schroedinger equation is a lift of Newton's law of motion on the space of probability measures, where derivatives are taken w.r.t. the Wasserstein Riemannian metric. Here the potential is the sum of the total classical…

Mathematical Physics · Physics 2009-03-12 Max-K. von Renesse

We prove a theorem that generalizes Schmidt's Subspace Theorem in the context of metric diophantine approximation. To do so we reformulate the Subspace theorem in the framework of homogeneous dynamics by introducing and studying a slope…

Number Theory · Mathematics 2021-02-08 Emmanuel Breuillard , Nicolas de Saxcé

We generalize Einstein's probabilistic method for the Brownian motion to study compressible fluids in porous media. The multi-dimensional case is considered with general probability distribution functions. By relating the expected…

Analysis of PDEs · Mathematics 2025-03-06 Luan Hoang , Akif Ibragimov

This paper introduces a new nonlinear dictionary learning method for histograms in the probability simplex. The method leverages optimal transport theory, in the sense that our aim is to reconstruct histograms using so-called displacement…

The non-Markoffian transport equations for the systems of cold Bose atoms confined by a external potential both without and with a Bose-Einstein condensate are derived in the framework of nonequilibrium thermal filed theory (Thermo Field…

Quantum Gases · Physics 2010-07-13 Y. Nakamura , T. Sunaga , M. Mine , M. Okumura , Y. Yamanaka

This paper studies hamiltonization of nonholonomic systems using geometric tools. By making use of symmetries and suitable first integrals of the system, we explicitly define a global 2-form for which the gauge transformed nonholonomic…

Mathematical Physics · Physics 2019-04-02 Paula Balseiro , Luis P. Yapu

The most rigorous physical description of non-equilibrium gas dynamics is rooted in the numerical solution of the Boltzmann equation. Yet, the large number of degrees of freedom and the wide range of both spatial and temporal scales render…

Computational Physics · Physics 2024-10-25 Anthony Chang , Narendra Singh , Marco Panesi

In the variational principle leading to the Euler equation for a perfect fluid, we can use the method of undetermined multiplier for holonomic constraints representing mass conservation and adiabatic condition. For a dissipative fluid, the…

Fluid Dynamics · Physics 2012-06-03 Hiroki Fukagawa , Youhei Fujitani

We reconsider some fundamental aspects of the fluid mechanics model, and the derivation of continuum flow equations from gas kinetic theory. Two topologies for fluid representation are presented, and a set of macroscopic equations are…

Fluid Dynamics · Physics 2007-05-23 S. Kokou Dadzie , Jason M. Reese , Colin R. McInnes

In this paper, we establish the existence of periodic orbits of a twisted geodesic flow on all low energy levels and in all dimensions whenever the magnetic field form is symplectic and spherically rational. This is a consequence of a more…

Symplectic Geometry · Mathematics 2007-05-23 Viktor L. Ginzburg , Basak Z. Gurel

Non-negative matrix and tensor factorisations are a classical tool for finding low-dimensional representations of high-dimensional datasets. In applications such as imaging, datasets can be regarded as distributions supported on a space…

Machine Learning · Statistics 2021-07-16 Stephen Y. Zhang