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A computationally efficient method for solving three-dimensional, viscous, incompressible flows on unbounded domains is presented. The method formally discretizes the incompressible Navier-Stokes equations on an unbounded staggered…

Fluid Dynamics · Physics 2016-05-25 Sebastian Liska , Tim Colonius

Analogous to the bowl soliton of mean curvature flow, we construct rotationally symmetric translating solutions to a very large class of extrinsic curvature flows, namely those whose speeds are $\alpha$-homogeneous ($\alpha>0$), elliptic…

Differential Geometry · Mathematics 2021-09-23 Sathyanarayanan Rengaswami

Sampling from Flow Matching generative models requires solving an ordinary differential equation (ODE) whose computational cost is dominated by neural network forward passes. We derive four classical ODE solvers -- Euler, Explicit Midpoint,…

Machine Learning · Computer Science 2026-05-05 Hao Xiao

It is well-known that the flows generated by two smooth vector fields commute, if the Lie bracket of these vector fields vanishes. This assertion is known to extend to Lipschitz continuous vector fields, up to interpreting the vanishing of…

Functional Analysis · Mathematics 2020-11-17 Chiara Rigoni , Eugene Stepanov , Dario Trevisan

A word-to-word function is rational if it can be realized by a non-deterministic one-way transducer. Over finite words, it is a classical result that any rational function is regular, i.e. it can be computed by a deterministic two-way…

Formal Languages and Automata Theory · Computer Science 2022-11-04 Olivier Carton , Gaëtan Douéneau-Tabot

We investigate a set of functional equations defining a projection in the noncommutative 2-torus algebra $A_{\theta}$. The exact solutions of these provide various generalisations of the Powers-Rieffel projection. By identifying the…

K-Theory and Homology · Mathematics 2014-03-25 Michał Eckstein

Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn produce a single softened solution and collapse under ambiguity. We present PermFlow, a…

Machine Learning · Computer Science 2026-05-19 Yimeng Min , Carla P. Gomes

Normalizing flows (NF) recently gained attention as a way to construct generative networks with exact likelihood calculation out of composable layers. However, NF is restricted to dimension-preserving transformations. Surjection VAE…

Machine Learning · Computer Science 2023-11-28 Paul M. Baggenstoss , Felix Govaers

We study $2$-dimensional unit vector flows on graphs, that is, nowhere-zero flows that assign to each oriented edge a unit vector in $\mathbb R^{3}$. We give a new geometric characterization of $\mathbb S^{2}$-flows on cubic graphs. We also…

Combinatorics · Mathematics 2026-02-26 Hussein Houdrouge , Bobby Miraftab , Pat Morin

We present an epistemic action theory for tractable epistemic reasoning as an extension to the h-approximation (HPX) theory. In contrast to existing tractable approaches, the theory supports functional fluents and postdictive reasoning with…

Artificial Intelligence · Computer Science 2020-11-26 Manfred Eppe

The main result of this paper is a convexity estimate for translating solitons of extrinsic geometric flows which evolve under a $1$-homogeneous concave function in the principal curvatures. In addition, we show examples of these…

Differential Geometry · Mathematics 2021-09-28 Jose Torres Santaella

The mean resolvent operator predicts, in the frequency domain, the mean linear response to forcing. As such, it provides the optimal linear time-invariant approximation of the input-output dynamics of time-varying flows in the statistically…

Fluid Dynamics · Physics 2025-10-16 Alessandro Bongarzone , Cédric Content , Denis Sipp , Colin Leclercq

We present the derivation of a new unidirectional model for We present the derivation of a new unidirectional model for unsteady mixed flows in non uniform closed water pipes. We introduce a local reference frame to take into account the…

Analysis of PDEs · Mathematics 2010-06-02 Christian Bourdarias , Mehmet Ersoy , Stéphane Gerbi

In our previous paper we associated to each non-constant elliptic function $f$ on a torus $T$ a dynamical system, the elliptic Newton flow corresponding to $f$. We characterized the functions for which these flows are structurally stable…

Dynamical Systems · Mathematics 2016-09-07 G. F. Helminck , F. Twilt

We give complete classification of C^2-regular and non-degenerate projectively Anosov flows on three dimensional manifolds. More precisely, we prove that such a flow on a connected manifold must be either an Anosov flow or represented as a…

Dynamical Systems · Mathematics 2011-09-12 Masayuki Asaoka

Normalizing flows are a promising tool for modeling probability distributions in physical systems. While state-of-the-art flows accurately approximate distributions and energies, applications in physics additionally require smooth energies…

Machine Learning · Statistics 2021-12-01 Jonas Köhler , Andreas Krämer , Frank Noé

Recently, two of these authors construct dissipative continuous (weak) solutions to the incompressible Euler equations on the three-dimensional torus $\mathbb T^3$. The building blocks in their proof are Beltrami flows, which are inherently…

Analysis of PDEs · Mathematics 2012-05-08 Antoine Choffrut , Camillo De Lellis , László Székelyhidi

A normal projective complex surface is called a rational homology projective plane if it has the same Betti numbers with the complex projective plane $\mathbb{C}\mathbb{P}^2$. It is known that a rational homology projective plane with…

Algebraic Geometry · Mathematics 2008-10-12 Dongseon Hwang , JongHae Keum

We investigate a one dimensional flow described with the non-compressible coupled Euler and non-compressible Navier-Stokes equations in Cartesian coordinate systems. We couple the two fluids through the continuity equation where different…

Fluid Dynamics · Physics 2021-09-28 I. F. Barna , Mátyás László

Normalizing flows are a powerful technique for obtaining reparameterizable samples from complex multimodal distributions. Unfortunately current approaches fall short when the underlying space has a non trivial topology, and are only…

Machine Learning · Statistics 2020-06-12 Luca Falorsi , Patrick Forré