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This study proposes and analyses a novel higher-order, structure preserving discretization method for inviscid barotropic flows from a Lagrangian perspective. The method is built on a multisymplectic variational principle discretized over a…

Numerical Analysis · Mathematics 2025-12-10 Mukthesh Mahadev , Marc Gerritsma

When applied to stiff, linear differential equations with time-dependent forcing, Runge-Kutta methods can exhibit convergence rates lower than predicted by the classical order condition theory. Commonly, this order reduction phenomenon is…

Numerical Analysis · Mathematics 2022-02-15 Steven Roberts , Adrian Sandu

In this work, a new algorithm for solving symmetric indefinite systems of linear equations is presented. It factorizes the matrix into the form LDLt using Jacobi rotations in order to increase the pivot's absolute value. Furthermore, Rook's…

Numerical Analysis · Mathematics 2025-01-30 Ibai Coria , Gorka Urkullu , Haritz Uriarte , Igor Fernández de Bustos

Krylov subspace methods in quantum dynamics identify the minimal subspace in which a process unfolds. To date, their use is restricted to time evolutions governed by time-independent generators. We introduce a generalization valid for…

Quantum Physics · Physics 2025-01-27 Kazutaka Takahashi , Adolfo del Campo

In this paper, Hamiltonian and energy preserving reduced-order models are developed for the rotating thermal shallow water equation (RTSWE) in the non-canonical Hamiltonian form with the state-dependent Poisson matrix. The high fidelity…

Numerical Analysis · Mathematics 2024-06-19 Suleyman Yildiz , Murat Uzunca , Bulent Karasozen

Among randomized numerical linear algebra strategies, so-called sketching procedures are emerging as effective reduction means to accelerate the computation of Krylov subspace methods for, e.g., the solution of linear systems, eigenvalue…

Numerical Analysis · Mathematics 2024-08-02 Davide Palitta , Marcel Schweitzer , Valeria Simoncini

In this work we introduce a memory-efficient method for computing the action of a Hermitian matrix function on a vector. Our method consists of a rational Lanczos algorithm combined with a basis compression procedure based on rational…

Numerical Analysis · Mathematics 2024-03-08 Angelo A. Casulli , Igor Simunec

We develop entropy dissipative higher order accurate local discontinuous Galerkin (LDG) discretizations coupled with Diagonally Implicit Runge-Kutta (DIRK) methods for nonlinear degenerate parabolic equations with a gradient flow structure.…

Numerical Analysis · Mathematics 2023-05-02 F. Yan , J. J . W. van der Vegt , Y. Xia , Y. Xu

This paper discusses model order reduction of large sparse second-order index-3 differential algebraic equations (DAEs) by applying Iterative Rational Krylov Algorithm (IRKA). In general, such DAEs arise in constraint mechanics, multibody…

Optimization and Control · Mathematics 2021-01-11 Xin Du , M. Monir Uddiny , A. Mostakim Fonyz , Md. Tanzim Hossainx , Md. Nazmul Islam Shuzan

During the past decade, Model Order Reduction (MOR) has become key enabler for the efficient simulation of large circuit models. MOR techniques based on moment-matching are well established due to their simplicity and computational…

Randomized block Krylov subspace methods form a powerful class of algorithms for computing the extreme eigenvalues of a symmetric matrix or the extreme singular values of a general matrix. The purpose of this paper is to develop new…

Numerical Analysis · Mathematics 2021-10-05 Joel A. Tropp

We consider the Cauchy problem for the 1D generalized Schr\"odinger equation on the whole axis. To solve it, any order finite element in space and the Crank-Nicolson in time method with the discrete transparent boundary conditions (TBCs)…

Numerical Analysis · Mathematics 2026-01-05 A. Zlotnik , I. Zlotnik

In this paper, we propose two discontinuous dynamical systems in continuous time with guaranteed prescribed finite-time local convergence to strict local minima of a given cost function. Our approach consists of exploiting a Lyapunov-based…

Optimization and Control · Mathematics 2019-12-19 Orlando Romero , Mouhacine Benosman

Time-dependent basis reduced order models (TDB ROMs) have successfully been used for approximating the solution to nonlinear stochastic partial differential equations (PDEs). For many practical problems of interest, discretizing these PDEs…

Numerical Analysis · Mathematics 2023-08-21 M. Donello , G. Palkar , M. H. Naderi , D. C. Del Rey Fernández , H. Babaee

A generalization of classical cubic B-spline functions with a parameter is used as basis in the collocation method. Some initial boundary value problems constructed on the nonlinear Klein-gordon equation are solved by the proposed method…

General Mathematics · Mathematics 2016-11-07 Alper Korkmaz , Ozlem Ersoy , Idiris Dag

We present a new efficient computational approach for time-dependent first-order Hamilton-Jacobi-Bellman PDEs. Since our method is based on a time-implicit Eulerian discretization, the numerical scheme is unconditionally stable, but…

Numerical Analysis · Mathematics 2013-06-18 Alexander Vladimirsky , Changxi Zheng

A classical reduced order model (ROM) for dynamical problems typically involves only the spatial reduction of a given problem. Recently, a novel space-time ROM for linear dynamical problems has been developed, which further reduces the…

Numerical Analysis · Mathematics 2025-11-06 Youngkyu Kim , Karen May Wang , Youngsoo Choi

This paper establishes and analyzes a second-order accurate numerical scheme for the nonlinear partial integrodifferential equation with a weakly singular kernel. In the time direction, we apply the Crank-Nicolson method for the time…

Numerical Analysis · Mathematics 2022-09-07 Wenlin Qiu , Xu Xiao , Kexin Li

We study linear parabolic initial-value problems in a space-time variational formulation based on fractional calculus. This formulation uses "time derivatives of order one half" on the bi-infinite time axis. We show that for linear,…

Numerical Analysis · Mathematics 2015-01-20 Stig Larsson , Christoph Schwab

Block Krylov subspace methods (KSMs) comprise building blocks in many state-of-the-art solvers for large-scale matrix equations as they arise, e.g., from the discretization of partial differential equations. While extended and rational…

Numerical Analysis · Mathematics 2020-02-06 Daniel Kressner , Kathryn Lund , Stefano Massei , Davide Palitta
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