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This paper considers spectral-difference methods of a high-order of accuracy for solving the one-way wave equation using the Laguerre integral transform with respect to time as the base. In order to provide a high spatial accuracy and…

Numerical Analysis · Mathematics 2018-05-10 Andrew V. Terekhov

In this paper a technique is given to recover the classical order of the method when explicit exponential Runge-Kutta methods integrate reaction-diffusion problems. Although methods of high stiff order for problems with vanishing boundary…

Numerical Analysis · Mathematics 2022-11-22 Begoña Cano , Marí a Jesús Moreta

Purely dispersive partial differential equations as the Korteweg-de Vries equation, the nonlinear Schr\"odinger equation and higher dimensional generalizations thereof can have solutions which develop a zone of rapid modulated oscillations…

Numerical Analysis · Mathematics 2015-03-19 C. Klein , K. Roidot

We propose a kernel compression method for solving Distributed-Order (DO) Fractional Partial Differential Equations (DOFPDEs) at the cost of solving corresponding local-in-time PDEs. The key concepts are (1) discretization of the integral…

Numerical Analysis · Mathematics 2025-08-20 Jonas Beddrich , Barbara Wohlmuth

Explicit Runge-Kutta methods are classical and widespread techniques in the numerical solution of ordinary differential equations (ODEs). Considering partial differential equations, spatial semidiscretisations can be used to obtain systems…

Numerical Analysis · Mathematics 2020-04-08 Hendrik Ranocha

Multirate time integration methods apply different step sizes to resolve different components of the system based on the local activity levels. This local selection of step sizes allows increased computational efficiency while achieving the…

Numerical Analysis · Computer Science 2021-12-22 Arash Sarshar , Steven Roberts , Adrian Sandu

A single-step high-order implicit time integration scheme with controllable numerical dissipation at high frequencies is presented for the transient analysis of structural dynamic problems. The amount of numerical dissipation is controlled…

Numerical Analysis · Mathematics 2023-09-29 Chongmin Song , Xiaoran Zhang , Sascha Eisenträger , Ankit Ankit

A new method for the numerical solution of ODEs is presented. This approach is based on an approximate formulation of the Taylor methods that has a much easier implementation than the original Taylor methods, since only the functions in the…

Numerical Analysis · Mathematics 2025-01-30 Antonio Baeza , Sebastiano Boscarino , Pep Mulet , Giovanni Russo , David Zorío

We consider the numerical integration of non-autonomous separable parabolic equations using high order splitting methods with complex coefficients (methods with real coefficients of order greater than two necessarily have negative…

Numerical Analysis · Mathematics 2014-05-20 Muaz Seydaoğlu , Sergio Blanes

This work considers multirate generalized-structure additively partitioned Runge-Kutta (MrGARK) methods for solving stiff systems of ordinary differential equations (ODEs) with multiple time scales. These methods treat different partitions…

Numerical Analysis · Mathematics 2022-01-19 Steven Roberts , John Loffeld , Arash Sarshar , Carol S. Woodward , Adrian Sandu

Splitting methods constitute a well-established class of numerical schemes for the time integration of partial differential equations. Their main advantages over more traditional schemes are computational efficiency and superior geometric…

Numerical Analysis · Mathematics 2017-01-06 Lukas Einkemmer , Alexander Ostermann

In order to treat the multiple time scales of ocean dynamics in an efficient manner, the baroclinic-barotropic splitting technique has been widely used for solving the primitive equations for ocean modeling. Based on the framework of strong…

Numerical Analysis · Mathematics 2022-03-14 Rihui Lan , Lili Ju , Zhu Wang , Max Gunzburger , Philip Jones

In many applications, the governing PDE to be solved numerically contains a stiff component. When this component is linear, an implicit time stepping method that is unencumbered by stability restrictions is often preferred. On the other…

Numerical Analysis · Mathematics 2021-04-27 Kevin Chow , Steven J. Ruuth

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

Exponential Runge--Kutta methods have shown to be competitive for the time integration of stiff semilinear parabolic PDEs. The current construction of stiffly accurate exponential Runge--Kutta methods, however, relies on a convergence…

Numerical Analysis · Mathematics 2020-09-29 Vu Thai Luan

Many time-dependent differential equations are equipped with invariants. Preserving such invariants under discretization can be important, e.g., to improve the qualitative and quantitative properties of numerical solutions. Recently,…

Numerical Analysis · Mathematics 2023-11-27 Sebastian Bleecke , Hendrik Ranocha

In the present work, a high order finite element type residual distribution scheme is designed in the framework of multidimensional compressible Euler equations of gas dynamics. The strengths of the proposed approximation rely on the…

Numerical Analysis · Mathematics 2023-01-16 Remi Abgrall , Paola Bacigaluppi , Tokareva Svetlana

We discuss the numerical solution methods available when solving for the steady-state density matrix of a time-independent open quantum optical system, where the system operators are expressed in a suitable basis representation as sparse…

Quantum Physics · Physics 2015-04-28 P. D. Nation

In this paper, we present error estimates of the integral deferred correction method constructed with stiffly accurate implicit Runge-Kutta methods with a nonsingular matrix $A$ in its Butcher table representation, when applied to stiff…

Numerical Analysis · Mathematics 2015-10-15 Sebastiano Boscarino , Jing-Mei Qiu

Solving partial differential equations (PDEs) within the framework of probabilistic numerics offers a principled approach to quantifying epistemic uncertainty arising from discretization. By leveraging Gaussian process regression and…

Machine Learning · Statistics 2025-08-18 Akshay Thakur , Sawan Kumar , Matthew Zahr , Souvik Chakraborty
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