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Linear systems with a tensor product structure arise naturally when considering the discretization of Laplace type differential equations or, more generally, multidimensional operators with separable coefficients. In this work, we focus on…

Numerical Analysis · Mathematics 2023-11-03 Stefano Massei , Leonardo Robol

The first order by time partial differential equations are used as models in applications such as fluid flow, heat transfer, solid deformation, electromagnetic waves, and others. In this paper we propose the new numerical method to solve a…

Numerical Analysis · Mathematics 2008-01-14 Ivan Kazachkov

A characteristic matrix function captures the spectral information of a bounded linear operator in a matrix-valued function. In this article, we consider a delay differential equation with one discrete time delay and assume this equation is…

Dynamical Systems · Mathematics 2022-01-31 Babette de Wolff

We study generalized solutions of an evolutionary equation related to some densely defined skew-symmetric operator in a real Hilbert space. We establish existence of a contractive semigroup, which provides generalized solutions, and suggest…

Analysis of PDEs · Mathematics 2025-04-24 Evgeny Yu. Panov

To approximate solutions of a linear differential equation, we project, via trigonometric interpolation, its solution space onto a finite-dimensional space of trigonometric polynomials and construct a matrix representation of the…

Numerical Analysis · Mathematics 2011-08-30 Oksana Bihun , Austin Bren , Michael Dyrud , Kristin Heysse

We develop a general framework for construction and analysis of discrete extension operators with application to unfitted finite element approximation of partial differential equations. In unfitted methods so called cut elements intersected…

Numerical Analysis · Mathematics 2021-01-26 Erik Burman , Peter Hansbo , Mats G. Larson

This article explores some geometric and algebraic properties of the dynamical system which is represented by matrix differential equations arising from inertial navigation problems, such as the symplecticity and the orthogonality.…

Dynamical Systems · Mathematics 2020-02-12 Xin-Long Luo , Geng Sun

This work establishes new results on spectral theory and time evolution for matrix-valued discrete Schr\"odinger operators on the space of square-summable matrix sequences. The matrix-valued formalism is employed to streamline notation,…

Functional Analysis · Mathematics 2026-04-03 Ballesteros Miguel , Franco Córdova Gerardo , Gil Jonathan , Ivan Naumkin

We propose a preconditioner to accelerate the convergence of the GMRES iterative method for solving the system of linear equations obtained from discretize-then-optimize approach applied to optimal control problems constrained by a partial…

Numerical Analysis · Mathematics 2019-11-15 Hamid Mirchi , Davod Khojasteh Salkuyeh

In this work, we construct novel discretizations for the unsteady convection-diffusion equation. Our discretization relies on multiderivative time integrators together with a novel discretization that reduces the total number of unknowns…

Numerical Analysis · Mathematics 2017-02-10 Jochen Schütz , David C. Seal , Alexander Jaust

Efficient and stable solution of partial differential equations (PDEs) is central to scientific and engineering applications, yet existing numerical solvers rely heavily on matrix based discretizations, while learning based methods require…

Machine Learning · Computer Science 2026-04-30 Yi Bing , Zheng Ran , Fu Jinyang , Liu Long , Peng Xiang

Learning underlying dynamics from data is important and challenging in many real-world scenarios. Incorporating differential equations (DEs) to design continuous networks has drawn much attention recently, however, most prior works make…

Machine Learning · Computer Science 2023-02-03 Yesom Park , Jaemoo Choi , Changyeon Yoon , Chang hoon Song , Myungjoo Kang

For many linear and nonlinear systems that arise from the discretization of partial differential equations the construction of an efficient multigrid solver is a challenging task. Here we present a novel approach for the optimization of…

Numerical Analysis · Mathematics 2019-10-09 Jonas Schmitt , Sebastian Kuckuk , Harald Köstler

We present the partial evolutionary tensor neural networks (pETNNs), a novel framework for solving time-dependent partial differential equations with high accuracy and capable of handling high-dimensional problems. Our architecture…

Numerical Analysis · Mathematics 2025-12-08 Tunan Kao , He Zhang , Lei Zhang , Jin Zhao

Multi-material design optimization problems can, after discretization, be solved by the iterative solution of simpler sub-problems which approximate the original problem at an expansion point to first order. In particular, models…

Numerical Analysis · Mathematics 2026-04-01 Peter Gangl , Nico Nees , Michael Stingl

In this paper, we develop an efficient numerical solver for unsteady diffusion-type partial differential equations with random coefficients. A major computational challenge in such problems lies in repeatedly handling large-scale linear…

Numerical Analysis · Mathematics 2026-01-19 Yujun Zhu , Min Li , Yulan Ning , Ju Ming

We prove stability and convergence of a full discretization for a class of stochastic evolution equations with super-linearly growing operators appearing in the drift term. This is done using the recently developed tamed Euler method, which…

Probability · Mathematics 2015-08-14 István Gyöngy , Sotirios Sabanis , David Šiška

In this paper, we consider a new approach for semi-discretization in time and spatial discretization of a class of semi-linear stochastic partial differential equations (SPDEs) with multiplicative noise. The drift term of the SPDEs is only…

Numerical Analysis · Mathematics 2023-07-10 Yukun Li , Liet Vo , Guanqian Wang

The tracer equations are part of the primitive equations used in ocean modeling and describe the transport of tracers, such as temperature, salinity or chemicals, in the ocean. Depending on the number of tracers considered, several…

Numerical Analysis · Mathematics 2020-04-22 Sara Calandrini , Konstantin Pieper , Max Gunzburger

We discuss a new optimization strategy, which considerably improves the effectivity of evolutionary algorithms applied to a certain class of optimization problems. The basic principle is to solve first a simpler related problem, which is…

Disordered Systems and Neural Networks · Physics 2007-05-23 Volkhard Buchholtz , Thorsten Poeschel