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Machine-learning methods are gradually being adopted in a wide variety of social, economic, and scientific contexts, yet they are notorious for struggling with exact mathematics. A typical example is computer algebra, which includes tasks…

Machine Learning · Computer Science 2024-11-06 Lennart Dabelow , Masahito Ueda

The a posteriori error analysis of the classical Argyris finite element methods dates back to 1996, while the optimal convergence rates of associated adaptive finite element schemes are established only very recently in 2021. It took a long…

Numerical Analysis · Mathematics 2024-03-20 Carsten Carstensen , Benedikt Gräßle

We consider a space-time fractional parabolic problem. Combining a sinc-quadrature based method for discretizing the Riesz-Dunford integral with $hp$-FEM in space yields an exponentially convergent scheme for the initial boundary value…

Numerical Analysis · Mathematics 2024-07-25 Jens Markus Melenk , Alexander Rieder

We study the seismic inverse problem for the recovery of subsurface properties in acoustic media. In order to reduce the ill-posedness of the problem, the heterogeneous wave speed parameter to be recovered is represented using a limited…

Analysis of PDEs · Mathematics 2020-09-10 Florian Faucher , Otmar Scherzer , Hélène Barucq

Eigensolvers involving complex moments can determine all the eigenvalues in a given region in the complex plane and the corresponding eigenvectors of a regular linear matrix pencil. The complex moment acts as a filter for extracting…

Numerical Analysis · Mathematics 2021-09-22 Keiichi Morikuni

Building on the blueprint from Goemans and Williamson (1995) for the Max-Cut problem, we construct a polynomial-time approximation algorithm for orthogonally constrained quadratic optimization problems. First, we derive a semidefinite…

Optimization and Control · Mathematics 2026-03-17 Ryan Cory-Wright , Jean Pauphilet

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou

We describe a new method of proving a priori bounds for positive supersolutions and solutions of superlinear elliptic PDE, based on global weak Harnack inequalities and a quantitative Hopf lemma. Novel results based on the method include:…

Analysis of PDEs · Mathematics 2019-04-16 Boyan Sirakov

In a common formulation of semi-infinite programs, the infinite constraint set is a requirement that a function parametrized by the decision variables is nonnegative over an interval. If this function is sufficiently closely approximable by…

Optimization and Control · Mathematics 2017-03-24 Dávid Papp

We develop a numerical method for solving shape optimization of functionals involving Steklov eigenvalues and apply it to the problem of maximization of the $k$-th Steklov eigenvalue, under volume constraint. A similar study in the planar…

Optimization and Control · Mathematics 2021-09-07 Pedro R. S. Antunes

We find out a method for symbolic estimation of a minimal (maximal) distance between eigenvalues of a Hermitian matrix (or roots of a polynomial with real (maybe degenerated) roots), using Hankel matrices formalism. The range of location of…

Classical Analysis and ODEs · Mathematics 2016-08-18 Ilia Lomidze , Natela Chachava

In this article we derive a priori error estimates for the $hp$-version of the mortar finite element method for parabolic initial-boundary value problems. Both semidiscrete and fully discrete methods are analysed in $L^2$- and $H^1$-norms.…

Analysis of PDEs · Mathematics 2018-07-24 Sanjib Kumar Acharya , Ajit Patel , Talal Rahman

We consider the inverse problem of determining the highly oscillatory coefficient $a^\epsilon$ in partial differential equations of the form $-\nabla\cdot (a^\epsilon\nabla u^\epsilon)+bu^\epsilon = f$ from given measurements of the…

Numerical Analysis · Mathematics 2016-10-26 Christina Frederick , Bjorn Engquist

The aim of this article is to provide a simple and unified way to obtain the sharp upper bounds of nodal sets of eigenfunctions for different types of eigenvalue problems on real analytic domains. The examples include biharmonic Steklov…

Analysis of PDEs · Mathematics 2020-10-08 Fanghua Lin , Jiuyi Zhu

This paper introduces and develops the algebraic framework of moment polynomials, which are polynomial expressions in commuting variables and their formal mixed moments. Their positivity and optimization over probability measures supported…

Functional Analysis · Mathematics 2024-05-14 Igor Klep , Victor Magron , Jurij Volčič

We propose a novel a posteriori error estimator for conforming finite element discretizations of two- and three-dimensional Helmholtz problems. The estimator is based on an equilibrated flux that is computed by solving patchwise mixed…

Numerical Analysis · Mathematics 2021-05-05 T. Chaumont-Frelet , A. Ern , M. Vohralík

It is well known that the real and imaginary parts of any holomorphic function are harmonic functions of two variables. In this paper we generalize this property to finite-dimensional commutative algebras. We prove that if some basis of a…

Analysis of PDEs · Mathematics 2008-11-18 Anatoliy A. Pogorui

This paper demonstrates that extremal ideals can be used to great effect to compute integral closures of powers and symbolic powers of square-free monomial ideals. We show that the generators of these powers are images of the generators of…

Commutative Algebra · Mathematics 2026-02-06 Trung Chau , Art Duval , Sara Faridi , Thiago Holleben , Susan Morey , Liana Şega

In this paper we discuss three symbolic approaches for the generation of a finite difference scheme of a partial differential equation (PDE). We prove, that for a linear PDE with constant coefficients these three approaches are equivalent…

Mathematical Physics · Physics 2019-03-06 Viktor Levandovskyy , Bernd Martin

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian…

Machine Learning · Statistics 2014-02-13 Philipp Hennig , Søren Hauberg
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