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Related papers: Wasserstein Hamiltonian flows

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Elementary sub-Riemannian geometry on the Heisenberg group H(n) provides a compact picture of symplectic geometry. Any Hamiltonian diffeomorphism on $R^{2n}$ lifts to a volume preserving bi-Lipschitz homeomorphisms of H(n), with the use of…

Symplectic Geometry · Mathematics 2007-05-23 Marius Buliga

The Hamiltonian formulation of superfluids based on noncanonical Poisson brackets is studied in detail. The assumption that the momentum density is proportional to the flow of the conserved energy is shown to lead to the covariant…

High Energy Physics - Phenomenology · Physics 2008-11-26 Manuel A. Valle

An ideal compressible fluid is considered, with an equilibrium density being a given function of coordinates due to presence of some static external forces. The slow flows in such system, which do not disturb the density, are investigated…

Fluid Dynamics · Physics 2009-11-06 V. P. Ruban

We study the Wasserstein natural gradient in parametric statistical models with continuous sample spaces. Our approach is to pull back the $L^2$-Wasserstein metric tensor in the probability density space to a parameter space, equipping the…

Optimization and Control · Mathematics 2024-08-20 Yifan Chen , Wuchen Li

Consider a homogenous fluid membrane described by the Helfrich-Canham energy, quadratic in the mean curvature of the membrane surface. The shape equation that determines equilibrium configurations is fourth order in derivatives and cubic in…

Soft Condensed Matter · Physics 2009-11-11 Riccardo Capovilla , Jemal Guven , Efrain Rojas

We propose a general framework to extend Flow Matching to homogeneous spaces, i.e. quotients of Lie groups. Our approach reformulates the problem as a flow matching task on the underlying Lie group by lifting the data distributions. This…

Machine Learning · Computer Science 2026-03-27 Francesco Ruscelli

In this article we study generalization of the classical Talagrand transport-entropy inequality in which the Wasserstein distance is replaced by the entropic transportation cost. This class of inequalities has been introduced in the recent…

Probability · Mathematics 2019-07-02 Giovanni Conforti , Luigia Ripani

A fully coupled system of two second-order parabolic degenerate equations arising as a thin film approximation to the Muskat problem is interpreted as a gradient flow for the 2-Wasserstein distance in the space of probability measures with…

Analysis of PDEs · Mathematics 2013-08-29 Philippe Laurencot , Bogdan-Vasile Matioc

We derive the dynamics of several rigid bodies of arbitrary shape in a 2-dimensional inviscid and incompressible fluid, whose vorticity field is given by point vortices. We adopt the idea of Vankerschaver et al. (2009) to derive the…

Fluid Dynamics · Physics 2014-02-27 Steffen Weissmann

We study a natural Wasserstein gradient flow on manifolds of probability distributions with discrete sample spaces. We derive the Riemannian structure for the probability simplex from the dynamical formulation of the Wasserstein distance on…

Optimization and Control · Mathematics 2021-04-19 Wuchen Li , Guido Montufar

Let K be an irreducible and reversible Markov kernel on a finite set X. We construct a metric W on the set of probability measures on X and show that with respect to this metric, the law of the continuous time Markov chain evolves as the…

Probability · Mathematics 2011-06-17 Jan Maas

We consider the problem of density estimation on Riemannian manifolds. Density estimation on manifolds has many applications in fluid-mechanics, optics and plasma physics and it appears often when dealing with angular variables (such as…

Machine Learning · Statistics 2016-11-10 Mevlana C. Gemici , Danilo Rezende , Shakir Mohamed

By a semi-Lagrangian change of coordinates, the hydrostatic Euler equations describing free-surface sheared flows is rewritten as a system of quasilinear equations, where stability conditions can be determined by the analysis of its…

It is well-known that the LIE(Locally Induction Equation) admit soliton-type solutions and same soliton solutions arise from different and apparently irrelevant physical models. By comparing the solitons of LIE and Killing magnetic…

Differential Geometry · Mathematics 2015-06-12 Chong Song , Xiaowei Sun , Youde Wang

Superconformal extensions of the perfect fluid equations, which realize $N=1,2$ Schrodinger superalgebra, are constructed within the Hamiltonian formalism. They are built by introducing real (for $N=1$) or complex (for $N=2$) anticommuting…

High Energy Physics - Theory · Physics 2025-12-02 Timofei Snegirev

We reformulate the relativistic perfect fluid system on curved space-time. Using standard variables, the velocity field $u$,energy density $\rho$ and pressure $p$, the covariant Euler-Lagrange equation is obtained from variational…

General Relativity and Quantum Cosmology · Physics 2016-12-07 Takayoshi Ootsuka , Muneyuki Ishida , Erico Tanaka , Ryoko Yahagi

Kinetic theory describes a dilute monatomic gas using a distribution function $f(q,p,t)$, the expected phase-space density of particles. The distribution function evolves according to the collisionless Boltzmann equation in the high Knudsen…

Mathematical Physics · Physics 2022-03-02 Ching Lok Chong

This paper investigates the dynamics of time-periodic Euler flows in multi-connected, planar fluid regions which are ``stirred'' by the moving boundaries. The classical Helmholtz theorem on the transport of vorticity implies that if the…

Dynamical Systems · Mathematics 2007-05-23 Philip Boyland

In this paper we bring together some of the key ideas and methods of two disparate fields of mathematical research, frame theory and optimal transport, using the methods of the second to answer questions posed in the first. In particular,…

Functional Analysis · Mathematics 2022-12-01 Clare Wickman , Kasso Okoudjou

Many problems in machine learning can be formulated as solving entropy-regularized optimal transport on the space of probability measures. The canonical approach involves the Sinkhorn iterates, renowned for their rich mathematical…

Machine Learning · Computer Science 2023-11-29 Mohammad Reza Karimi , Ya-Ping Hsieh , Andreas Krause