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We propose a new type of reduction for integrable systems of coupled matrix PDEs; this reduction equates one matrix variable with the transposition of another multiplied by an antisymmetric constant matrix. Via this reduction, we obtain a…

Exactly Solvable and Integrable Systems · Physics 2011-12-30 Takayuki Tsuchida

We consider the nonlinear Schr\"odinger equation with dispersion modulated by a (formal) derivative of a time-dependent function with fractional Sobolev regularity of class $W^{\alpha,2}$ for some $\alpha\in (0,1)$. Due to the loss of…

Numerical Analysis · Mathematics 2018-11-05 Martina Hofmanová , Marvin Knöller , Katharina Schratz

Randomized iterative methods, such as the randomized Kaczmarz method, have gained significant attention for solving large-scale linear systems due to their simplicity and efficiency. Meanwhile, Krylov subspace methods have emerged as a…

Numerical Analysis · Mathematics 2025-05-28 Yonghan Sun , Deren Han , Jiaxin Xie

In this paper, we consider the task of efficiently computing the numerical solution of evolutionary complex Ginzburg--Landau equations on Cartesian product domains with homogeneous Dirichlet/Neumann or periodic boundary conditions. To this…

Numerical Analysis · Mathematics 2024-06-19 Marco Caliari , Fabio Cassini

Structure-preserving linearly implicit exponential integrators are constructed for Hamiltonian partial differential equations with linear constant damping. Linearly implicit integrators are derived by polarizing the polynomial terms of the…

Numerical Analysis · Mathematics 2024-03-19 Murat Uzunca , Bülent Karasözen

This paper deals with the application of probabilistic time integration methods to semi-explicit partial differential-algebraic equations of parabolic type and its semi-discrete counterparts, namely semi-explicit differential-algebraic…

Numerical Analysis · Mathematics 2024-12-02 R. Altmann , A. Moradi

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

Optimization problems with constraints in the form of a partial differential equation arise frequently in the process of engineering design. The discretization of PDE-constrained optimization problems results in large-scale linear systems…

Numerical Analysis · Mathematics 2012-01-04 Jacek Gondzio , Pavel Zhlobich

Suitable discretizations through tensor product formulas of popular multidimensional operators (diffusion or diffusion--advection, for instance) lead to matrices with $d$-dimensional Kronecker sum structure. For evolutionary Partial…

Numerical Analysis · Mathematics 2024-06-18 Fabio Cassini

This paper surveys an important class of methods that combine iterative projection methods and variational regularization methods for large-scale inverse problems. Iterative methods such as Krylov subspace methods are invaluable in the…

Numerical Analysis · Mathematics 2021-08-23 Julianne Chung , Silvia Gazzola

We change a previous time-stepping algorithm for solving a multi-scale Vlasov-Poisson system within a Particle-In-Cell method, in order to do accurate long time simulations. As an exponential integrator, the new scheme allows to use large…

Numerical Analysis · Mathematics 2015-06-19 Emmanuel Frenod , Sever Hirstoaga , Mathieu Lutz

A linearly implicit conservative difference scheme is applied to discretize the attractive coupled nonlinear Schr\"odinger equations with fractional Laplacian. Complex symmetric linear systems can be obtained, and the system matrices are…

Numerical Analysis · Mathematics 2023-10-19 Yan Cheng , Xi Yang

Discretizing continuous-time linear systems typically requires numerical integration. This document presents a convenient method for discretizing the dynamics, input, and process noise state-space matrices of a continuous-time linear system…

Systems and Control · Electrical Eng. & Systems 2025-05-27 Steven Dahdah , James Richard Forbes

Krylov complexity provides a powerful framework for characterizing the dynamical evolution of quantum systems through the spreading of states in Krylov space. The motivation for this is rooted in the optimality of the Krylov basis for the…

Quantum Physics · Physics 2026-03-10 Saud Čindrak , Kathy Lüdge

Delay differential equations (DDEs) are infinite-dimensional systems, so even a scalar, unforced nonlinear DDE can exhibit chaos. Lyapunov exponents are indicators of chaos and can be computed by comparing the evolution of infinitesimally…

Computational Physics · Physics 2018-10-04 Anwar Sadath , Thomas K. Uchida , C. P. Vyasarayani

In this work, we propose a simple yet generic preconditioned Krylov subspace method for a large class of nonsymmetric block Toeplitz all-at-once systems arising from discretizing evolutionary partial differential equations. Namely, our main…

Numerical Analysis · Mathematics 2023-08-11 Sean Hon , Po Yin Fung , Jiamei Dong , Stefano Serra-Capizzano

A standard approach to reduced-order modeling of higher-order linear dynamical systems is to rewrite the system as an equivalent first-order system and then employ Krylov-subspace techniques for reduced-order modeling of first-order…

Numerical Analysis · Mathematics 2007-05-23 Roland W. Freund

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

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

An algorithm for constructing a $J$-orthogonal basis of the extended Krylov subspace $\mathcal{K}_{r,s}=\operatorname{range}\{u,Hu, H^2u,$ $ \ldots, $ $H^{2r-1}u, H^{-1}u, H^{-2}u, \ldots, H^{-2s}u\},$ where $H \in \mathbb{R}^{2n \times…

Numerical Analysis · Mathematics 2022-02-28 Peter Benner , Heike Faßbender , Michel-Niklas Senn