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In this paper, we propose a certified reduced basis (RB) method for quasilinear parabolic problems. The method is based on a space-time variational formulation. We provide a residual-based a-posteriori error bound on a space-time level and…

Numerical Analysis · Mathematics 2020-12-21 Michael Hinze , Denis Korolev

Model Order Reduction (MOR) can significantly reduce the computational cost of vibroacoustic simulations. While most MOR research focuses on single-domain systems (e.g., structural dynamics or computational fluid mechanics), this work…

Applied Physics · Physics 2026-02-05 Sander Metting van Rijn , Linus Taenzer , Paolo Tiso , Bart Van Damme

The randomized Arnoldi process has been used in large-scale scientific computing because it produces a well-conditioned basis for the Krylov subspace more quickly than the standard Arnoldi process. However, the resulting Hessenberg matrix…

Numerical Analysis · Mathematics 2026-01-16 Laura Grigori , Daniel Kressner , Nian Shao , Igor Simunec

This paper focuses on the efficient numerical algorithms of a three-field Biot's consolidation model. The approach begins with the introduction of innovative monolithic and global-in-time iterative decoupled algorithms, which incorporate…

Numerical Analysis · Mathematics 2025-08-07 Huipeng Gu , Francesco Ballarin , Mingchao Cai , Jingzhi Li

The Golub-Kahan-Tikhonov method is a popular solution technique for large linear discrete ill-posed problems. This method first applies partial Golub-Kahan bidiagonalization to reduce the size of the given problem and then uses Tikhonov…

Numerical Analysis · Mathematics 2026-03-10 Davide Bianchi , Marco Donatelli , Davide Furchì , Lothar Reichel

Our work is about energy conserving fourth-order time discretizations of a three-field formulation of Maxwell's equations in conjunction with a spatial discretization using higher-order and compatible de Rham finite element spaces. Toward…

Numerical Analysis · Mathematics 2026-01-21 Archana Arya , Kaushik Kalyanaraman

Bilevel optimization, with broad applications in machine learning, has an intricate hierarchical structure. Gradient-based methods have emerged as a common approach to large-scale bilevel problems. However, the computation of the…

Optimization and Control · Mathematics 2025-02-27 Yan Yang , Bin Gao , Ya-xiang Yuan

Hybrid high-order (HHO) methods are numerical methods characterized by several interesting properties such as local conservativity, geometric flexibility and high-order accuracy. Here, HHO schemes are studied for the space…

Numerical Analysis · Mathematics 2025-10-06 Romain Mottier , Alexandre Ern , Laurent Guillot

In this study, we develop an extended implicit moment method, namely, a coupled high-order low-order (HOLO) method and apply it to the electromagnetic Vlasov-Darwin model. The high-order (HO) system evolves particles in a manner that…

Plasma Physics · Physics 2025-08-13 Derek A. Kuldinow , William T. Taitano , Kentaro Hara

We use the alternating direction method to simulate implicit dynamics. ur spatial discretization uses isogeometric analysis. Namely, we simulate a (hyperbolic) wave propagation problem in which we use tensor-product B-splines in space and…

Numerical Analysis · Mathematics 2019-11-20 Marcin Los , Pouria Behnoudfar , Maciej Paszynski , Victor Manuel Calo

The overlap operator in lattice QCD requires the computation of the sign function of a matrix, which is non-Hermitian in the presence of a quark chemical potential. In previous work we introduced an Arnoldi-based Krylov subspace…

High Energy Physics - Lattice · Physics 2014-11-20 Jacques C. R. Bloch , Tobias Breu , Andreas Frommer , Simon Heybrock , Katrin Schäfer , Tilo Wettig

Quantum Krylov algorithms have emerged as a promising approach for ground-state energy estimation in the near-term quantum computing era. A major challenge, however, lies in their inherently substantial sampling cost, primarily due to the…

To integrate large systems of nonlinear differential equations in time, we consider a variant of nonlinear waveform relaxation (also known as dynamic iteration or Picard-Lindel\"of iteration), where at each iteration a linear inhomogeneous…

Numerical Analysis · Mathematics 2024-04-23 Mike A. Botchev

In this paper, we focus on the finite difference approximation of nonlinear degenerate parabolic equations, a special class of parabolic equations where the viscous term vanishes in certain regions. This vanishing gives rise to additional…

Numerical Analysis · Mathematics 2024-06-11 Ziyao Xu , Yong-Tao Zhang

We present a new short-recurrence reaidual-optimal Krylov subspace recycling method for sequences of Hermitian systems of linear equations with a fixed system matrix and changing right-hand sides. Such sequences of linear systems occur…

Numerical Analysis · Mathematics 2016-04-15 Martin Peter Neuenhofen , Sven Groß

In this paper we develop a novel two-stage fourth order time-accurate discretization for time-dependent flow problems, particularly for hyperbolic conservation laws. Different from the classical Runge-Kutta (R-K) temporal discretization for…

Numerical Analysis · Mathematics 2015-12-14 Jiequan Li , Zhifang Du

This paper is concerned with developing and analyzing two novel implicit temporal discretization methods for the stochastic semilinear wave equations with multiplicative noise. The proposed methods are natural extensions of well-known…

Numerical Analysis · Mathematics 2024-08-26 Xiaobing Feng , Yukun Li , Liet Vo

The purpose of this work is the development of space-time discretization schemes for phase-field optimal control problems. First, a time discretization of the forward problem is derived using a discontinuous Galerkin formulation. Here, a…

Optimization and Control · Mathematics 2022-03-24 Denis Khimin , Marc C. Steinbach , Thomas Wick

This paper presents a novel space-time topology optimisation framework for time-dependent thermal conduction problems, aiming to significantly reduce the time-to-solution. By treating time as an additional spatial dimension, we discretise…

Computational Engineering, Finance, and Science · Computer Science 2025-08-14 Joe Alexandersen , Magnus Appel

With the recent realization of exascale performace by Oak Ridge National Laboratory's Frontier supercomputer, reducing communication in kernels like QR factorization has become even more imperative. Low-synchronization Gram-Schmidt methods,…

Numerical Analysis · Mathematics 2023-02-21 Kathryn Lund