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Differential algebra approaches to structural identifiability analysis of a dynamic system model in many instances heavily depend upon Ritt's pseudodivision at an early step in analysis. The pseudodivision algorithm is used to find the…

Algebraic Geometry · Mathematics 2012-03-21 Nicolette Meshkat , Chris Anderson , Joseph J. DiStefano

Gr{\"o}bner bases is one the most powerful tools in algorithmic non-linear algebra. Their computation is an intrinsically hard problem with a complexity at least single exponential in the number of variables. However, in most of the cases,…

Symbolic Computation · Computer Science 2019-02-04 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

In the process of constructing invariant difference schemes which approximate partial differential equations we write down a procedure for discretizing an arbitrary partial differential equation on an arbitrary lattice. An open problem is…

Mathematical Physics · Physics 2016-04-27 Decio Levi , Miguel A. Rodriguez

An exact discretization method is being developed for solving linear systems of ordinary fractional-derivative differential equations with constant matrix coefficients (LSOFDDECMC). It is shown that the obtained linear discrete system in…

Dynamical Systems · Mathematics 2019-03-18 Fikret A. Aliev , N. A. Aliev , N. I. Velieva , K. G. Gasimova , Y. V Mamedova

For a wide class of polynomially nonlinear systems of partial differential equations we suggest an algorithmic approach to the s(trong)-consistency analysis of their finite difference approximations on Cartesian grids. First we apply the…

Symbolic Computation · Computer Science 2019-05-01 Vladimir P. Gerdt , Daniel Robertz

We consider ideals involving the maximal minors of a polynomial matrix. For example, those arising in the computation of the critical values of a polynomial restricted to a variety for polynomial optimisation. Gr\"obner bases are a…

Commutative Algebra · Mathematics 2022-03-21 Alin Bostan , Jérémy Berthomieu , Andrew Ferguson , Mohab Safey El Din

The Galerkin difference (GD) basis is a set of continuous, piecewise polynomials defined using a finite difference like grid of degrees of freedom. The one dimensional GD basis functions are naturally extended to multiple dimensions using…

Numerical Analysis · Mathematics 2021-06-03 Jeremy E. Kozdon , Lucas C. Wilcox , Thomas Hagstrom , Jeffrey W. Banks

A generalization of the Gr\"{u}nwald difference approximation for fractional derivatives in terms of a real sequence and its generating function is presented. Properties of the generating function are derived for consistency and order of…

Numerical Analysis · Mathematics 2018-03-06 H. M. Nasir , K. Nafa

We propose an Exponential DG approach for numerically solving partial differential equations (PDEs). The idea is to decompose the governing PDE operators into linear (fast dynamics extracted by linearization) and nonlinear (the remaining…

Numerical Analysis · Mathematics 2021-08-11 Shinhoo Kang , Tan Bui-Thanh

We propose a novel algorithmic method for constructing invariant variational schemes of systems of ordinary differential equations that are the Euler-Lagrange equations of a variational principle. The method is based on the invariantization…

Numerical Analysis · Mathematics 2021-09-28 Alex Bihlo , James Jackaman , Francis Valiquette

We present a new line-based discontinuous Galerkin (DG) discretization scheme for first- and second-order systems of partial differential equations. The scheme is based on fully unstructured meshes of quadrilateral or hexahedral elements,…

Numerical Analysis · Mathematics 2015-06-04 Per-Olof Persson

Sparse polynomial interpolation, sparse linear system solving or modular rational reconstruction are fundamental problems in Computer Algebra. They come down to computing linear recurrence relations of a sequence with the Berlekamp-Massey…

Symbolic Computation · Computer Science 2021-07-07 Jérémy Berthomieu , Jean-Charles Faugère

This paper develops and analyzes a class of semi-discrete and fully discrete weak Galerkin finite element methods for unsteady incompressible convective Brinkman-Forchheimer equations. For the spatial discretization, the methods adopt the…

Numerical Analysis · Mathematics 2024-10-30 Xiaojuan Wang , Jihong Xiao , Xiaoping Xie , Shiquan Zhang

In this paper we present a new methodology for solving multiobjective integer linear programs using tools from algebraic geometry. We introduce the concept of partial Gr\"obner basis for a family of multiobjective programs where the…

Optimization and Control · Mathematics 2008-06-19 Victor Blanco , Justo Puerto

We adapt the Gradient Discretisation Method (GDM), originally designed for elliptic and parabolic partial differential equations, to the case of a linear scalar hyperbolic equations. This enables the simultaneous design and convergence…

Numerical Analysis · Mathematics 2019-10-28 Jérôme Droniou , Robert Eymard , T. Gallouët , R. Herbin

Many differential equations with physical backgrounds are described as gradient systems, which are evolution equations driven by the gradient of some functionals, and such problems have energy conservation or dissipation properties. For…

Numerical Analysis · Mathematics 2023-08-07 Tomoya Kemmochi

In this paper, a linearized semi-implicit finite difference scheme is proposed for solving the two-dimensional (2D) space fractional nonlinear Schr\"{o}dinger equation (SFNSE).The scheme has the property of mass and energy conservation on…

Numerical Analysis · Mathematics 2021-07-27 Hongling Hu , Xianlin Jin , Dongdong He , Kejia Pan , Qifeng Zhang

We consider structure-preserving methods for conservative systems, which rigorously replicate the conservation property yielding better numerical solutions. There, corresponding to the skew-symmetry of the differential operator, that of…

Numerical Analysis · Mathematics 2016-07-19 Daisuke Furihata , Shun Sato , Takayasu Matsuo

In this paper, we focus on constructing numerical schemes preserving the averaged energy evolution law for nonlinear stochastic wave equations driven by multiplicative noise. We first apply the compact finite difference method and the…

Numerical Analysis · Mathematics 2022-01-26 Jialin Hong , Baohui Hou , Liying Sun

We present an algorithm for marginalising changepoints in time-series models that assume a fixed number of unknown changepoints. Our algorithm is differentiable with respect to its inputs, which are the values of latent random variables…

Machine Learning · Computer Science 2019-11-25 Hyoungjin Lim , Gwonsoo Che , Wonyeol Lee , Hongseok Yang