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This work constructs and analyzes new efficient high-order two-derivative diagonally implicit Runge--Kutta (TDDIRK) schemes with optimized phase errors. Specifically, we present a convergence result for TDDIRK methods and investigate their…

Numerical Analysis · Mathematics 2025-12-18 Julius Ehigie , Vu Thai Luan

Most research on preconditioners for time-dependent PDEs has focused on implicit multi-step or diagonally-implicit multi-stage temporal discretizations. In this paper, we consider monolithic multigrid preconditioners for fully-implicit…

Numerical Analysis · Mathematics 2023-02-28 Razan Abu-Labdeh , Scott MacLachlan , Patrick E. Farrell

In this note we discuss the construction of high order asymptotic preserving numerical schemes for the Boltzmann equation. The methods are based on the use of Implicit-Explicit (IMEX) Runge-Kutta methods combined with a penalization…

Numerical Analysis · Mathematics 2012-02-24 Giacomo Dimarco , Lorenzo Pareschi

We propose a technique for investigating stability properties like positivity and forward invariance of an interval for method-of-lines discretizations, and apply the technique to study positivity preservation for a class of TVD…

Numerical Analysis · Mathematics 2017-02-15 Imre Fekete , David I. Ketcheson , Lajos Lóczi

We present a parametric family of semi-implicit second order accurate numerical methods for non-conservative and conservative advection equation for which the numerical solutions can be obtained in a fixed number of forward and backward…

Numerical Analysis · Mathematics 2023-12-01 Peter Frolkovič , Svetlana Krišková , Michaela Rohová , Michal Žeravý

A wide range of physical phenomena exhibit auxiliary admissibility criteria, such as conservation of entropy or various energies, which arise implicitly under the exact solution of their governing PDEs. However, standard temporal schemes,…

Numerical Analysis · Mathematics 2024-01-29 Mohammad R. Najafian , Brian C. Vermeire

In this work we present a class of high order unconditionally strong stability preserving (SSP) implicit multi-derivative Runge--Kutta schemes, and SSP implicit-explicit (IMEX) multi-derivative Runge--Kutta schemes where the time-step…

Numerical Analysis · Mathematics 2021-08-10 Sigal Gottlieb , Zachary J. Grant , Jingwei Hu , Ruiwen Shu

In this work modified Patankar-Runge-Kutta (MPRK) schemes up to order four are considered and equipped with a dense output formula of appropriate accuracy. Since these time integrators are conservative and positivity preserving for any time…

Numerical Analysis · Mathematics 2025-01-24 Thomas Izgin

The framework of inner product norm preserving relaxation Runge-Kutta methods (David I. Ketcheson, \emph{Relaxation Runge-Kutta Methods: Conservation and Stability for Inner-Product Norms}, SIAM Journal on Numerical Analysis, 2019) is…

Numerical Analysis · Mathematics 2020-11-26 Hendrik Ranocha , Mohammed Sayyari , Lisandro Dalcin , Matteo Parsani , David I. Ketcheson

In this technical note a general procedure is described to construct internally consistent splitting methods for the numerical solution of differential equations, starting from matching pairs of explicit and diagonally implicit Runge-Kutta…

Numerical Analysis · Mathematics 2017-07-17 Willem Hundsdorfer

We propose second-order implicit-explicit (IMEX) time-stepping schemes for nonlinear fractional differential equations with fractional order $0<\beta<1$. From the known structure of the non-smooth solution and by introducing corresponding…

Numerical Analysis · Mathematics 2016-08-03 Wanrong Cao , Fanhai Zeng , Zhongqiang Zhang , George Em Karniadakis

A novel class of explicit high-order energy-preserving methods are proposed for general Hamiltonian partial differential equations with non-canonical structure matrix. When the energy is not quadratic, it is firstly done that the original…

Numerical Analysis · Mathematics 2020-06-02 Chaolong Jiang , Yushun Wang , Yuezheng Gong

In this paper we consider an approach to improve the performance of exponential Runge--Kutta integrators and Lawson schemes} in cases where the solution of a related, but usually much simpler, problem can be computed efficiently. While for…

Numerical Analysis · Mathematics 2023-10-20 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

A new Chebyshev-type family of stabilized explicit methods for solving mildly stiff ODEs is presented. Besides conventional conditions of order and stability we impose an additional restriction on the methods: their stability function must…

Numerical Analysis · Mathematics 2025-04-02 Boris Faleichik , Andrew Moisa

In this work we present explicit Adams-type multistep methods with extended stability interval, which are analogous to the stabilized Chebyshev Runge--Kutta methods. It is proved that for any $k\geq 1$ there exists an explicit $k$-step…

Numerical Analysis · Mathematics 2020-12-15 Vasily Repnikov , Boris Faleichik , Andrey Moysa

Nonlinear time fractional partial differential equations are widely used in modeling and simulations. In many applications, there are high contrast changes in media properties. For solving these problems, one often uses coarse spatial grid…

Numerical Analysis · Mathematics 2022-07-13 Wenyuan Li , Anatoly Alikhanov , Yalchin Efendiev , Wing Tat Leung

In this study, we propose high-order implicit and semi-implicit schemes for solving ordinary differential equations (ODEs) based on Taylor series expansion. These methods are designed to handle stiff and non-stiff components within a…

Numerical Analysis · Mathematics 2024-09-19 S. Boscarino , E. Macca

Fully implicit timestepping methods have several potential advantages for atmosphere/ocean simulation. First, being unconditionally stable, they degrade more gracefully as the Courant number increases, typically requiring more solver…

Numerical Analysis · Mathematics 2025-10-16 Werner Bauer , Colin J. Cotter

Neural PDE solvers offer a powerful tool for modeling complex dynamical systems, but often struggle with error accumulation over long time horizons and maintaining stability and physical consistency. We introduce a multiscale implicit…

Machine Learning · Computer Science 2025-06-06 Ruoxi Jiang , Xiao Zhang , Karan Jakhar , Peter Y. Lu , Pedram Hassanzadeh , Michael Maire , Rebecca Willett

For time-dependent problems with high-contrast multiscale coefficients, the time step size for explicit methods is affected by the magnitude of the coefficient parameter. With a suitable construction of multiscale space, one can achieve a…

Numerical Analysis · Mathematics 2022-04-01 Wing Tat Leung , Yating Wang
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