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Related papers: Flat Norm Decomposition of Integral Currents

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Deep learning is emerging as a new paradigm for solving inverse imaging problems. However, the deep learning methods often lack the assurance of traditional physics-based methods due to the lack of physical information considerations in…

Image and Video Processing · Electrical Eng. & Systems 2020-07-20 Dongdong Chen , Mike E. Davies

In the analysis of High-Energy Physics data, it is frequently desired to separate resonant signals from a smooth, non-resonant background. This paper introduces a new technique - functional decomposition (FD) - to accomplish this task. It…

Data Analysis, Statistics and Probability · Physics 2018-05-15 Ryan Edgar , Dante Amidei , Christopher Grud , Karishma Sekhon

Non-stationary blind super-resolution is an extension of the traditional super-resolution problem, which deals with the problem of recovering fine details from coarse measurements. The non-stationary blind super-resolution problem appears…

Information Theory · Computer Science 2019-10-09 Shuang Li , Michael B. Wakin , Gongguo Tang

The aim of this paper is to investigate the sufficient condition for the invariance of a normal curve on a smooth immersed surface under isometry. We also find the the deviations of the tangential and normal components of the curve with…

General Mathematics · Mathematics 2019-06-13 Absos Ali Shaikh , Mohamd Saleem Lone , Pinaki Ranjan Ghosh

We extract local current distributions from interatomic currents calculated using a fully relativistic quantum mechanical scattering formalism by interpolation onto a three-dimensional grid. The method is illustrated with calculations for…

Mesoscale and Nanoscale Physics · Physics 2021-05-06 Rohit S. Nair , Paul J. Kelly

In this paper, we generalize the minimum flow decomposition problem (MFD) to incorporate uncertain edge capacities and tackle it from the perspective of robust optimization. In the classical flow decomposition problem, a network flow is…

Optimization and Control · Mathematics 2025-10-17 Moritz Stinzendörfer , Philine Schiewe , Fabricio Oliveira

Herein we present open problems and survey examples and theorems concerning sequences of Riemannian manifolds with uniform lower bounds on scalar curvature and their limit spaces. Examples of Gromov and of Ilmanen which naturally ought to…

Metric Geometry · Mathematics 2017-12-01 Christina Sormani

Direct numerical simulations are performed for the steady flow normal to a circular disk at the Reynolds number of 1000. Numerical simulations are conducted with different levels of simplification procedure by reducing the azimuthal…

Fluid Dynamics · Physics 2019-06-26 Xinliang Tian

The most general version of a renormalizable $d=4$ theory corresponding to a dimensionless higher-derivative scalar field model in curved spacetime is explored. The classical action of the theory contains $12$ independent functions, which…

High Energy Physics - Theory · Physics 2010-04-06 E. Elizalde , A. G. Jacksenaev , S. D. Odintsov , I. L. Shapiro

Inspired by the Gromov-Hausdorff distance, we define the intrinsic flat distance between oriented $m$ dimensional Riemannian manifolds with boundary by isometrically embedding the manifolds into a common metric space, measuring the flat…

Differential Geometry · Mathematics 2011-05-25 C. Sormani , S. Wenger

The immersed interface method (IIM) for fluid-structure interaction imposes discontinuities in the fluid stress along immersed boundaries that are generated by forces concentrated along those boundaries. For a viscous incompressible fluid,…

Numerical Analysis · Mathematics 2026-03-10 Michael J. Facci , Qi Sun , Boyce E. Griffith

The scaling properties of quantum gravity are discussed by employing a class of proper-time regulators in the functional flow equation for the conformal factor within the formalism of the background field method. Renormalization group…

High Energy Physics - Theory · Physics 2013-12-10 Alfio Bonanno , Filippo Guarnieri

Many approaches have been proposed to estimate camera poses by directly minimizing photometric error. However, due to the non-convex property of direct alignment, proper initialization is still required for these methods. Many robust norms…

Robotics · Computer Science 2019-10-17 Ke Wang , Kaixuan Wang , Shaojie Shen

A proof of convergence is given for semi- and full discretizations of mean curvature flow of closed two-dimensional surfaces. The numerical method proposed and studied here combines evolving finite elements, whose nodes determine the…

Numerical Analysis · Mathematics 2019-06-27 Balázs Kovács , Buyang Li , Christian Lubich

The infinite reduction of couplings is a tool to consistently renormalize a wide class of non-renormalizable theories with a reduced, eventually finite, set of independent couplings, and classify the non-renormalizable interactions. Several…

High Energy Physics - Theory · Physics 2009-11-11 Damiano Anselmi , Milenko Halat

Compositional simulation is challenging, because of highly nonlinear couplings between multi-component flow in porous media with thermodynamic phase behavior. The coupled nonlinear system is commonly solved by the fully-implicit scheme.…

Computational Physics · Physics 2020-10-13 Jiamin Jiang , Xian-Huan Wen

Surface-subsurface flow models for hydrological applications solve a coupled multiphysics problem. This usually consists of some form of the Richards and shallow water equations. A typical setup couples these two nonlinear partial…

Numerical Analysis · Mathematics 2025-04-25 Valentina Schüller , Philipp Birken , Andreas Dedner

An ideal triangulation of a singular flat surface is a geodesic triangulation such that its vertex set is equal to the set of singular points of the surface. Using the fact that each pair of points in a surface has a finite number of…

Metric Geometry · Mathematics 2020-12-01 İsmail Sağlam

The paper is devoted to discretization of integral norms of functions from a given finite dimensional subspace. This problem is very important in applications but there is no systematic study of it. We present here a new technique, which…

Numerical Analysis · Mathematics 2017-03-13 V. N. Temlyakov

Phase unwrapping is the process of recovering a continuous phase signal from an original signal wrapped in the ($-\pi$,$\pi$] interval. It is a critical step of coherent signal processing, with applications such as synthetic aperture radar,…

Signal Processing · Electrical Eng. & Systems 2019-06-03 Ian Herszterg , Marcus Poggi , Thibaut Vidal