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Invariant sets are a key ingredient for verifying safety and other properties of cyber-physical systems that mix discrete and continuous dynamics. We adapt the elimination-theoretic Rosenfeld-Gr\"{o}bner algorithm to systematically obtain…

Symbolic Computation · Computer Science 2026-04-02 William Simmons , André Platzer

In this paper, we propose a method, that is based on equivariant moving frames, for development of high order accurate invariant compact finite difference schemes that preserve Lie symmetries of underlying partial differential equations. In…

Mathematical Physics · Physics 2020-02-19 Ersin Ozbenli , Prakash Vedula

High-dimensional PDEs have been a longstanding computational challenge. We propose to solve high-dimensional PDEs by approximating the solution with a deep neural network which is trained to satisfy the differential operator, initial…

Mathematical Finance · Quantitative Finance 2018-10-17 Justin Sirignano , Konstantinos Spiliopoulos

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

An algebraic approach to the maximum likelihood estimation problem is to solve a very structured parameterized polynomial system called likelihood equations that have finitely many complex (real or non-real) solutions. The only solutions…

Symbolic Computation · Computer Science 2016-06-13 Jose Israel Rodriguez , Xiaoxian Tang

A local weighted discontinuous Galerkin gradient discretization method for solving elliptic equations is introduced. The local scheme is based on a coarse grid and successively improves the solution solving a sequence of local elliptic…

Numerical Analysis · Mathematics 2018-07-30 Assyr Abdulle , Giacomo Rosilho de Souza

We develop an efficient $hp$-finite element method for piecewise-smooth differential equations with periodic boundary conditions, using orthogonal polynomials defined on circular arcs. The operators derived from this basis are banded and…

Numerical Analysis · Mathematics 2025-12-23 Daniel VandenHeuvel , Sheehan Olver

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

Symmetry preserving difference schemes approximating second and third order ordinary differential equations are presented. They have the same three or four-dimensional symmetry groups as the original differential equations. The new…

Mathematical Physics · Physics 2009-11-11 A. Bourlioux , C Cyr-Gagnon , P Winternitz

I analyse a generalised Burger's equation to develop an accurate finite difference approximation to its dynamics. The analysis is based upon centre manifold theory so we are assured that the finite difference model accurately models the…

chao-dyn · Physics 2007-05-23 A. J. Roberts

One of the biggest open problems in computational algebra is the design of efficient algorithms for Gr{\"o}bner basis computations that take into account the sparsity of the input polynomials. We can perform such computations in the case of…

Symbolic Computation · Computer Science 2018-06-22 Matías Bender , Jean-Charles Faugère , Elias Tsigaridas

A key consideration in the development of numerical schemes for time-dependent partial differential equations (PDEs) is the ability to preserve certain properties of the continuum solution, such as associated conservation laws or other…

Numerical Analysis · Mathematics 2023-06-21 James Jackaman , Scott MacLachlan

We develop a general framework for designing conservative numerical methods based on summation by parts operators and split forms in space, combined with relaxation Runge-Kutta methods in time. We apply this framework to create new classes…

Numerical Analysis · Mathematics 2021-03-09 Hendrik Ranocha , Dimitrios Mitsotakis , David I. Ketcheson

In this paper we generalize the involutive methods and algorithms devised for polynomial ideals to differential ones generated by a finite set of linear differential polynomials in the differential polynomial ring over a zero characteristic…

Analysis of PDEs · Mathematics 2025-10-20 Vladimir P. Gerdt

We introduce efficient differentially private (DP) algorithms for several linear algebraic tasks, including solving linear equalities over arbitrary fields, linear inequalities over the reals, and computing affine spans and convex hulls. As…

Data Structures and Algorithms · Computer Science 2024-11-06 Haim Kaplan , Yishay Mansour , Shay Moran , Uri Stemmer , Nitzan Tur

A direct method for the computation of polynomial conservation laws of polynomial systems of nonlinear partial differential equations (PDEs) in multi-dimensions is presented. The method avoids advanced differential-geometric tools. Instead,…

Exactly Solvable and Integrable Systems · Physics 2015-06-26 Willy Hereman

In this paper, we present how high-order accurate solutions to elliptic partial differential equations can be achieved in arbitrary spatial domains using radial basis function-generated finite differences (RBF-FD) on unfitted node sets…

Numerical Analysis · Mathematics 2024-07-23 Morten E. Nielsen , Bengt Fornberg

We establish sharp energy decay rates for a large class of nonlinearly first-order damped systems, and we design discretization schemes that inherit of the same energy decay rates, uniformly with respect to the space and/or time…

Analysis of PDEs · Mathematics 2015-12-17 Fatiha Alabau-Boussouira , Yannick Privat , Emmanuel Trélat

The fact that the first variation of a variational functional must vanish along an extremizer is the base of most effective solution schemes to solve problems of the calculus of variations. We generalize the method to variational problems…

Optimization and Control · Mathematics 2018-02-14 Shakoor Pooseh , Ricardo Almeida , Delfim F. M. Torres

In recent years, a significant amount of attention has been paid to solve partial differential equations (PDEs) by deep learning. For example, deep Galerkin method (DGM) uses the PDE residual in the least-squares sense as the loss function…

Numerical Analysis · Mathematics 2020-06-09 Liyao Lyu , Zhen Zhang , Minxin Chen , Jingrun Chen