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Dynamical low-rank approximation has become a valuable tool to perform an on-the-fly model order reduction for prohibitively large matrix differential equations. A core ingredient is the construction of integrators that are robust to the…

Numerical Analysis · Mathematics 2024-02-14 Gianluca Ceruti , Lukas Einkemmer , Jonas Kusch , Christian Lubich

This work introduces a parallel and rank-adaptive matrix integrator for dynamical low-rank approximation. The method is related to the previously proposed rank-adaptive basis update & Galerkin (BUG) integrator but differs significantly in…

Numerical Analysis · Mathematics 2023-04-13 Gianluca Ceruti , Jonas Kusch , Christian Lubich

Numerical simulations of kinetic problems can become prohibitively expensive due to their large memory requirements and computational costs. A method that has proven to successfully reduce these costs is the dynamical low-rank approximation…

Numerical Analysis · Mathematics 2025-06-17 Lukas Einkemmer , Jonas Kusch , Steffen Schotthöfer

The Runge--Kutta (RK) discontinuous Galerkin (DG) method is a mainstream numerical algorithm for solving hyperbolic equations. In this paper, we use the linear advection equation in one and two dimensions as a model problem to prove the…

Numerical Analysis · Mathematics 2024-10-02 Zheng Sun

This work proposes and analyzes a new class of numerical integrators for computing low-rank approximations to solutions of matrix differential equation. We combine an explicit Runge-Kutta method with repeated randomized low-rank…

Numerical Analysis · Mathematics 2024-09-11 Hei Yin Lam , Gianluca Ceruti , Daniel Kressner

We reconsider the variational derivation of symplectic partitioned Runge-Kutta schemes. Such type of variational integrators are of great importance since they integrate mechanical systems with high order accuracy while preserving the…

Numerical Analysis · Mathematics 2015-05-08 Cédric M. Campos

In this work, we develop implicit rank-adaptive schemes for time-dependent matrix differential equations. The dynamic low rank approximation (DLRA) is a well-known technique to capture the dynamic low rank structure based on Dirac-Frenkel…

Numerical Analysis · Mathematics 2025-01-27 Daniel Appelö , Yingda Cheng

Isospectral Runge-Kutta methods are well-suited for the numerical solution of isospectral systems such as the rigid body and the Toda lattice. More recently, these integrators have been applied to geophysical fluid models, where their…

Numerical Analysis · Mathematics 2025-06-10 Clauson Carvalho da Silva , Christian Lessig , Carlos Tomei

A rank-adaptive integrator for the dynamical low-rank approximation of matrix and tensor differential equations is presented. The fixed-rank integrator recently proposed by two of the authors is extended to allow for an adaptive choice of…

Numerical Analysis · Mathematics 2021-04-13 Gianluca Ceruti , Jonas Kusch , Christian Lubich

We note a fact that stiff systems or differential equations that have highly oscillatory solutions cannot be solved efficiently using conventional methods. In this paper, we study two new classes of exponential Runge-Kutta (ERK) integrators…

Numerical Analysis · Mathematics 2023-12-06 Bin Wang , Xianfa Hu , Xinyuan Wu

A new approach for the construction of high order A-stable explicit integrators for ordinary differential equations (ODEs) is theoretically studied. Basically, the integrators are obtained by splitting, at each time step, the solution of…

Numerical Analysis · Mathematics 2012-08-24 H. de la Cruz , R. J. Biscay , J. C. Jimenez , F. Carbonell

We introduce a low-rank algorithm inspired by the Basis-Update and Galerkin (BUG) integrator to efficiently approximate solutions to Sylvester-type equations. The algorithm can exploit both the low-rank structure of the solution as well as…

Numerical Analysis · Mathematics 2025-11-04 Georgios Vretinaris

This paper investigates the performance of a subclass of exponential integrators, specifically explicit exponential Runge--Kutta methods. It is well known that third-order methods can suffer from order reduction when applied to linearized…

Numerical Analysis · Mathematics 2024-12-30 Thi Tam Dang , Trung Hau Hoang

This work focuses on the development of a new class of high-order accurate methods for multirate time integration of systems of ordinary differential equations. The proposed methods are based on a specific subset of explicit one-step…

Numerical Analysis · Mathematics 2019-04-16 Vu Thai Luan , Rujeko Chinomona , Daniel R. Reynolds

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

We prove that Runge-Kutta (RK) methods for numerical integration of arbitrarily large systems of Ordinary Differential Equations are linearly stable. Standard stability arguments -- based on spectral analysis, resolvent condition or strong…

Numerical Analysis · Mathematics 2023-12-27 Eitan Tadmor

In this paper, two novel classes of implicit exponential Runge-Kutta (ERK) methods are studied for solving highly oscillatory systems. First of all, we analyze the symplectic conditions of two kinds of exponential integrators, and present a…

Numerical Analysis · Mathematics 2023-12-05 Xianfa Hu , Wansheng Wang , Bin Wang , Yonglei Fang

Explicit Runge--Kutta (RK) methods are susceptible to a reduction in the observed order of convergence when applied to initial-boundary value problem with time-dependent boundary conditions. We study conditions on explicit RK methods that…

Numerical Analysis · Mathematics 2026-02-11 Abhijit Biswas , David I. Ketcheson , Steven Roberts , Benjamin Seibold , David Shirokoff

The work deals with two major topics concerning the numerical analysis of Runge-Kutta-like (RK-like) methods, namely their stability and order of convergence. RK-like methods differ from additive RK methods in that their coefficients are…

Numerical Analysis · Mathematics 2025-06-26 Thomas Izgin

Dynamic systems have a fundamental relevance in the description of physical phenomena. The search for more accurate and faster numerical integration methods for the resolution of such systems is, therefore, an important topic of research.…

Computational Physics · Physics 2025-10-10 J. Avellar , L. G. S. Duarte , L. A. C. P. da Mota , L. O. Pereira
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