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We propose an efficient semi-Lagrangian Characteristic Mapping (CM) method for solving the three-dimensional (3D) incompressible Euler equations. This method evolves advected quantities by discretizing the flow map associated with the…

Numerical Analysis · Mathematics 2023-02-21 Xi-Yuan Yin , Kai Schneider , Jean-Christophe Nave

Motivated by the manifold hypothesis, which states that data with a high extrinsic dimension may yet have a low intrinsic dimension, we develop refined statistical bounds for entropic optimal transport that are sensitive to the intrinsic…

Statistics Theory · Mathematics 2023-08-25 Austin J. Stromme

A formulation of the density functional theory is constructed on the foundations of entropic inference. The theory is introduced as an application of maximum entropy for inhomogeneous fluids in thermal equilibrium. It is shown that entropic…

Statistical Mechanics · Physics 2023-12-29 Ahmad Yousefi , Ariel Caticha

Optimal transport (OT) theory provides a principled framework for modeling mass movement in applications such as mobility, logistics, and economics. Classical formulations, however, generally ignore capacity limits that are intrinsic in…

Optimization and Control · Mathematics 2025-11-04 Anqi Dong , Karl Henrik Johansson , Johan Karlsson

The equation of the density field of an assembly of macroscopic particles advected by a hydrodynamic flow is derived from the microscopic description of the system. This equation allows to recognize the role and the relative importance of…

Chaotic Dynamics · Physics 2016-09-08 Cristobal Lopez , Andrea Puglisi

The existence of temperature gradients within eukaryotic cells has been postulated as a source of natural convection in the cytoplasm, i.e. bulk fluid motion as a result of temperature-difference-induced density gradients. Recent…

Fluid Dynamics · Physics 2024-07-22 Nikhil Desai , Weida Liao , Eric Lauga

The diffusive transport distance, a novel pseudo-metric between probability measures on the real line, is introduced. It generalizes Martingale optimal transport, and forms a hierarchy with the Hellinger and the Wasserstein metrics. We…

Analysis of PDEs · Mathematics 2025-01-27 Daniel Matthes , Eva-Maria Rott , André Schlichting

We describe an exact derivation of the total nondissipative transverse force acting on a quantized vortex moving in a uniform background. The derivation is valid for neutral boson or fermion superfluids, provided the order parameter is a…

Condensed Matter · Physics 2009-10-28 D. J. Thouless , P. Ao , Q. Niu

Hydrodynamic discontinuities in an external potential and incompressible flow are investigated. Using the reaction front as an example in a 2D stream, an overdetermined system of equations is obtained that describes its motion in terms of…

Fluid Dynamics · Physics 2024-04-10 Maxim Zaytsev , Vyacheslav Akkerman

Dense flow visualization is a popular visualization paradigm. Traditionally, the various models and methods in this area use a continuous formulation, resting upon the solid foundation of functional analysis. In this work, we examine a…

Graphics · Computer Science 2020-07-06 Daniel Preuß , Tino Weinkauf , Jens Krüger

We present a framework for modeling complex, high-dimensional distributions on convex polytopes by leveraging recent advances in discrete and continuous normalizing flows on Riemannian manifolds. We show that any full-dimensional polytope…

Machine Learning · Computer Science 2025-03-18 Tomek Diederen , Nicola Zamboni

We describe dimensional entropies introduced in a previous work list some of their properties and give some new proofs. These entropies allowed the definition of entropy-expanding maps. We introduce a new notion of entropy-hyperbolicity for…

Dynamical Systems · Mathematics 2011-02-04 Jerome Buzzi

Neural networks have dramatically increased our capacity to learn from large, high-dimensional datasets across innumerable disciplines. However, their decisions are not easily interpretable, their computational costs are high, and building…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Mackenzie J. Meni , Ryan T. White , Michael Mayo , Kevin Pilkiewicz

The Reynolds transport theorem occupies a central place in fluid dynamics, providing a generalized integral conservation equation for the transport of any conserved quantity within a fluid, and connected to its corresponding differential…

Fluid Dynamics · Physics 2023-02-01 Robert K. Niven

While machine learning (ML) architectures have evolved rapidly to account for complex data, loss functions like cross-entropy remain mostly structure-agnostic in many real-world applications. However, the `class-symmetric' nature of these…

Machine Learning · Computer Science 2026-05-28 Yasser Taha , Grégoire Montavon , Nils Körber

We consider possible generation of singularities of a vector field transported by diffeomorphisms with derivatives of uniformly bounded determinants. A particular case of volume preserving diffeomrphism is the most important, since it has…

Analysis of PDEs · Mathematics 2007-06-05 Dongho Chae

Large-eddy simulations are conducted to contrast momentum and passive scalar transport over large, three-dimensional roughness elements in a turbulent channel flow. Special attention is given to the dispersive fluxes, which are shown to be…

Fluid Dynamics · Physics 2019-10-09 Qi Li , Elie Bou-Zeid

We consider the gravity-driven flow of a perfect dielectric, viscous, thin liquid film, wetting a flat substrate inclined at a non-zero angle to the horizontal. The dynamics of the thin film is influenced by an electric field which is set…

Fluid Dynamics · Physics 2019-08-30 Ruben J Tomlin , Radu Cimpeanu , Demetrios T Papageorgiou

We define a class of divergences to measure differences between probability density functions in one-dimensional sample space. The construction is based on the convex function with the Jacobi operator of mapping function that pushforwards…

Statistics Theory · Mathematics 2025-04-24 Wuchen Li

Entropy is a central concept in physics, but can be challenging to calculate even for systems that are easily simulated. This is exacerbated out of equilibrium, where generally little is known about the distribution characterizing simulated…

Statistical Mechanics · Physics 2024-05-09 Samuel D. Gelman , Guy Cohen