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A general procedure for constructing conservative numerical integrators for time dependent partial differential equations is presented. In particular, linearly implicit methods preserving a time discretised version of the invariant is…

Numerical Analysis · Mathematics 2011-05-05 Morten Dahlby , Brynjulf Owren

We describe a method for discretizing planar C2-regular domains immersed in non-conforming triangulations. The method consists in constructing mappings from triangles in a background mesh to curvilinear ones that conform exactly to the…

Numerical Analysis · Mathematics 2012-01-25 Ramsharan Rangarajan , Adrian J. Lew

We develop an efficient numerical scheme for the 3D mean-field spherical dynamo equation. The scheme is based on a semi-implicit discretization in time and a spectral method in space based on the divergence-free spherical harmonic…

Numerical Analysis · Mathematics 2019-10-04 Ting cheng , Lina Ma , Jie Shen

Problems with localized nonhomogeneous material properties present well-known challenges for numerical simulations. In particular, such problems may feature large differences in length scales, causing difficulties with meshing and…

Numerical Analysis · Mathematics 2021-11-23 Alex Viguerie , Silvia Bertoluzza , Alessandro Veneziani , Ferdinando Auricchio

Non divergence-free discretisations for the incompressible Stokes problem may suffer from a lack of pressure-robustness characterised by large discretisations errors due to irrotational forces in the momentum balance. This paper argues that…

Numerical Analysis · Mathematics 2020-02-06 Derk Frerichs , Christian Merdon

The invariant subspace method is refined to present more unity and more diversity of exact solutions to evolution equations. The key idea is to take subspaces of solutions to linear ordinary differential equations as invariant subspaces…

Exactly Solvable and Integrable Systems · Physics 2015-06-04 Wen-Xiu Ma

We study a nonlinear system of partial differential equations which describe rotating shallow water with an arbitrary constant polytropic index $\gamma $ for the fluid. In our analysis we apply the theory of symmetries for differential…

Mathematical Physics · Physics 2019-10-23 Andronikos Paliathanasis

This book deals with functions allowing to express the dissimilarity (discrepancy) between two data fields or ''divergence functions'' with the aim of applications to linear inverse problems. Most of the divergences found in the litterature…

Optimization and Control · Mathematics 2020-03-04 Henri Lantéri

We introduce a lattice random walk discretisation scheme for stochastic differential equations (SDEs) that samples binary or ternary increments at each step, suppressing complex drift and diffusion computations to simple 1 or 2 bit random…

Numerical Analysis · Mathematics 2026-02-18 Samuel Duffield , Maxwell Aifer , Denis Melanson , Zach Belateche , Patrick J. Coles

The aim of this work is to develop general optimization methods for finite difference schemes used to approximate linear differential equations. The specific case of the transport equation is exposed. In particular, the minimization of the…

Analysis of PDEs · Mathematics 2007-05-23 Claire David , Pierre Sagaut

Alignment between non-rigid stretchable structures is one of the most challenging tasks in computer vision, as the invariant properties are hard to define, and there is no labeled data for real datasets. We present unsupervised neural…

Computer Vision and Pattern Recognition · Computer Science 2022-08-30 Idan Pazi , Dvir Ginzburg , Dan Raviv

The theory of slow invariant manifolds (SIMs) is the foundation of various model-order reduction techniques for dissipative dynamical systems with multiple time-scales, e.g. in chemical kinetic models. The construction of SIMs and many…

Dynamical Systems · Mathematics 2022-01-19 Johannes Poppe , Dirk Lebiedz

We propose a geometric numerical analysis of SDEs admitting Lie symmetries which allows us to individuate a symmetry adapted coordinates system where the given SDE has notable invariant properties. An approximation scheme preserving the…

Probability · Mathematics 2020-08-04 Francesco C. De Vecchi , Andrea Romano , Stefania Ugolini

Invariant manifolds are fundamental tools for describing and understanding nonlinear dynamics. In this paper, we present a theory of stable and unstable manifolds for infinite dimensional random dynamical systems generated by a class of…

Dynamical Systems · Mathematics 2019-08-15 Jinqiao Duan , Kening Lu , Bjorn Schmalfuss

Shape calculus concerns the calculation of directional derivatives of some quantity of interest, typically expressed as an integral. This article introduces a type of shape calculus based on localized dilation of boundary faces through…

Numerical Analysis · Mathematics 2023-05-29 Martin Berggren

Nonlinear dynamic models are widely used for characterizing functional forms of processes that govern complex biological pathway systems. Over the past decade, validation and further development of these models became possible due to data…

Methodology · Statistics 2019-08-13 Itai Dattner , Shota Gugushvili , Harold Ship , Eberhard O. Voit

This paper is devoted to the analysis of a numerical scheme for the coagulation and fragmentation equation with diffusion in space. A finite volume scheme is developed, based on a conservative formulation of the space nonhomogeneous…

Numerical Analysis · Mathematics 2009-11-13 Francis Filbet

Various versions of the Dynamical Systems Method (DSM) are proposed for solving linear ill-posed problems with bounded and unbounded operators. Convergence of the proposed methods is proved. Some new results concerning discrepancy principle…

Numerical Analysis · Mathematics 2007-05-23 A. G. Ramm

Given a stochastic differential equation (SDE) in $\mathbb{R}^n$ whose solution is constrained to lie in some manifold $M \subset \mathbb{R}^n$, we propose a class of numerical schemes for the SDE whose iterates remain close to $M$ to high…

Numerical Analysis · Mathematics 2020-09-24 John Armstrong , Tim King

The invariant is one of central topics in science, technology and engineering. The differential invariant is essential in understanding or describing some important phenomena or procedures in mathematics, physics, chemistry, biology or…

Computer Vision and Pattern Recognition · Computer Science 2017-05-26 Erbo Li , Hua Li
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