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This paper presents sufficient graph-theoretic conditions for injectivity of collections of differentiable functions on rectangular subsets of R^n. The results have implications for the possibility of multiple fixed points of maps and…

Functional Analysis · Mathematics 2010-04-30 Murad Banaji

We propose Riemannian Flow Matching (RFM), a simple yet powerful framework for training continuous normalizing flows on manifolds. Existing methods for generative modeling on manifolds either require expensive simulation, are inherently…

Machine Learning · Computer Science 2024-02-27 Ricky T. Q. Chen , Yaron Lipman

By using the degree theory and the $\tau-$topology of Kryszewski and Szulkin, we establish a version of the Fountain Theorem for strongly indefinite functionals. The abstract result will be applied for studying the existence of infinitely…

Analysis of PDEs · Mathematics 2013-06-18 Cyril J. Batkam , Fabrice Colin

In this paper, we introduce a class of new logarithmic curvature flow. The flows are designed to embrace the monotonicity of the related functional, and the convergence of this flow would tackle the solvability of the weighted…

Analysis of PDEs · Mathematics 2023-06-16 Jinrong Hu , Qiongfang Mao

Using the convex functions in Grassmannian manifolds we can carry out interior estimates for mean curvature flow of higher codimension. In this way some of the results of Ecker-Huisken can be generalized to higher codimension

Differential Geometry · Mathematics 2008-07-10 Y. L. Xin , Ling Yang

Algorithms based on normalizing flows are emerging as promising machine learning approaches to sampling complicated probability distributions in a way that can be made asymptotically exact. In the context of lattice field theory,…

The exact 1+3 covariant dynamical fluid equations for a multi-component plasma, together with Maxwell's equations are presented in such a way as to make them suitable for a gauge-invariant analysis of linear density and velocity…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Mattias Marklund , Peter K. S. Dunsby , Gerold Betschart , Martin Servin , Christos Tsagas

Iterative Gaussianization is a fixed-point iteration procedure that can transform any continuous random vector into a Gaussian one. Based on iterative Gaussianization, we propose a new type of normalizing flow model that enables both…

Machine Learning · Computer Science 2020-03-05 Chenlin Meng , Yang Song , Jiaming Song , Stefano Ermon

Many-body perturbation theory provides a powerful framework to study the ground state and thermodynamic properties of nuclear matter as well as associated single-particle potentials and response functions within a systematic order-by-order…

Nuclear Theory · Physics 2024-12-30 Pengsheng Wen , Jeremy W. Holt , Albany Blackburn

We introduce the mean curvature flow of curves in the Minkowski plane $\mathbf R^{1,1}$ and give a classification of all the self-similar solutions. In addition, we describe five other exact solutions to the flow.

Differential Geometry · Mathematics 2013-05-14 Hoeskuldur P. Halldorsson

Particulate Stokesian flows describe the hydrodynamics of rigid or deformable particles in Stokes flows. Due to highly nonlinear fluid-structure interaction dynamics, moving interfaces, and multiple scales, numerical simulations of such…

Computational Physics · Physics 2019-07-03 Gokberk Kabacaoglu , George Biros

We present an approach to construct appropriate and efficient emulators for Hamiltonian flow maps. Intended future applications are long-term tracing of fast charged particles in accelerators and magnetic plasma confinement configurations.…

Computational Physics · Physics 2021-06-02 Katharina Rath , Christopher G. Albert , Bernd Bischl , Udo von Toussaint

In this thesis, we investigate various integral submodels and generalize them. In part I, we study the submodel of the nonlinear $\mathbf{C}P^1$-model and the related submodels in $(1+2)$ dimensions. In part II, we construct integrable…

High Energy Physics - Theory · Physics 2007-05-23 Tatsuo Suzuki

Multi-phase flows encountered in nature or in industry, exhibit non trivial rheological properties, that can be understood better thanks to model materials and appropriate rheometers. Here, we use model unsaturated granular materials:…

Soft Condensed Matter · Physics 2021-06-24 Stephanie Deboeuf , Abdoulaye Fall

To model the dynamics of polymers formed through nucleation, elongated by polymerisation, shortened by depolymerisation and subject to aggregation reactions, we study a nonlinear integro-differential equation. Growth and shrinkage are…

Analysis of PDEs · Mathematics 2026-03-11 Julia Delacour , Marie Doumic , Carmela Moschella , Christian Schmeiser

This notebook tutorial demonstrates a method for sampling Boltzmann distributions of lattice field theories using a class of machine learning models known as normalizing flows. The ideas and approaches proposed in arXiv:1904.12072,…

To acquire the ability to numerically study the rheology of particulate two-phase flows that lack scale separation, we present a general method to average or coarse-grain the equations of motion of a mixture of a continuous fluid of…

Fluid Dynamics · Physics 2026-01-22 Thomas Pähtz , Yulan Chen , Rui Zhu , Katharina Tholen , Zhiguo He

We consider the approach to self-similarity (or dynamical scaling) in Smoluchowski's equations of coagulation for the solvable kernels $K(x,y)=2$, $x+y$ and $xy$. In addition to the known self-similar solutions with exponential tails, there…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Govind Menon , Robert L. Pego

Granular flows are ubiquitous in nature and industrial applications, yet a complete continuum theory remains a long-standing challenge. The leading empirical approach, {\mu}(I) rheology, lacks microscopic foundations and becomes multivalued…

We show how solutions to a large class of partial differential equations with nonlocal Riccati-type nonlinearities can be generated from the corresponding linearized equations, from arbitrary initial data. It is well known that evolutionary…

Analysis of PDEs · Mathematics 2018-01-31 Margaret Beck , Anastasia Doikou , Simon J. A. Malham , Ioannis Stylianidis