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This paper investigates, a new class of fractional order Runge-Kutta (FORK) methods for numerical approximation to the solution of fractional differential equations (FDEs). By using the Caputo generalizedTaylor formula and the total…

Numerical Analysis · Mathematics 2023-03-06 F. Ghoreishi , R. Ghaffari

We present a stationary iteration based upon a block splitting for a class of indefinite least squares problem. Convergence of the proposed method is investigated and optimal value of the involving parameter is used. The induced…

Numerical Analysis · Mathematics 2025-12-15 Davod Khojasteh Salkuyeh

This paper introduces a novel Transformed Primal-Dual with variable-metric/preconditioner (TPDv) algorithm, designed to efficiently solve affine constrained optimization problems common in nonlinear partial differential equations (PDEs).…

Numerical Analysis · Mathematics 2023-12-20 Long Chen , Ruchi Guo , Jingrong Wei

We propose a new method to solve the relativistic hydrodynamic equations based on implicit Runge-Kutta methods with a locally optimized fixed-point iterative solver. For numerical demonstration, we implement our idea for ideal hydrodynamics…

Nuclear Theory · Physics 2024-04-16 Nathan Touroux , Masakiyo Kitazawa , Koichi Murase , Marlene Nahrgang

Efficient high order numerical methods for evolving the solution of an ordinary differential equation are widely used. The popular Runge--Kutta methods, linear multi-step methods, and more broadly general linear methods, all have a global…

Numerical Analysis · Mathematics 2020-03-16 Adi Ditkowski , Sigal Gottlieb , Zachary J. Grant

Incomplete factorization is a powerful preconditioner for Krylov subspace methods for solving large-scale sparse linear systems. Existing incomplete factorization techniques, including incomplete Cholesky and incomplete LU factorizations,…

Numerical Analysis · Mathematics 2024-12-20 Aditi Ghai , Xiangmin Jiao

We present a modified version of the PRESB preconditioner for two-by-two block system of linear equations with the coefficient matrix $$\textbf{A}=\left(\begin{array}{cc} F & -G^* G & F \end{array}\right),$$ where $F\in\mathbb{C}^{n\times…

Numerical Analysis · Mathematics 2024-05-15 Owe Axelsson , Dovod Khojasteh Slakuyeh

We develop a preconditioner for the linear system arising from a finite element discretization of the Phase Field Crystal (PFC) equation. The PFC model serves as an atomic description of crystalline materials on diffusive time scales and…

Computational Physics · Physics 2015-08-27 Simon Praetorius , Axel Voigt

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

We devise 3-field and 4-field finite element approximations of a system describing the steady state of an incompressible heat-conducting fluid with implicit non-Newtonian rheology. We prove that the sequence of numerical approximations…

Numerical Analysis · Mathematics 2021-10-18 Patrick Farrell , Pablo Alexei Gazca Orozco , Endre Süli

In this work, we propose a novel diagonalization-based preconditioner for the all-at-once linear system arising from the optimal control problem of parabolic equations. The proposed preconditioner is constructed based on an…

Numerical Analysis · Mathematics 2025-07-01 Sean Y. Hon , Po Yin Fung , Xue-lei Lin

Splitting the exponential-like $\varphi$ functions, which typically appear in exponential integrators, is attractive in many situations since it can dramatically reduce the computational cost of the procedure. However, depending on the…

Numerical Analysis · Mathematics 2025-03-21 Marco Caliari , Fabio Cassini , Lukas Einkemmer , Alexander Ostermann

The ILU-based preconditioning methods in previous work have their own parameters to improve their performances. Although the parameters may degrade the performance, their determination is left to users. Thus, these previous methods are not…

Numerical Analysis · Computer Science 2013-06-21 Yuichiro Miki , Teruyoshi Washizawa

This paper presents a class of Crank-Nicolson (CN) type schemes enhanced by radial basis function (RBF) interpolation for the time integration of linear parabolic partial differential equations (PDEs). The resulting RBF-CN schemes preserve…

Numerical Analysis · Mathematics 2025-09-09 Subhankar Nandi , Satyajit Pramanik

The existing discrete variational derivative method is only second-order accurate and fully implicit. In this paper, we propose a framework to construct an arbitrary high-order implicit (original) energy stable scheme and a second-order…

Numerical Analysis · Mathematics 2022-10-24 Jizu Huang

This paper deals with solving a class of three-by-three block saddle point problems. The systems are solved by preconditioning techniques. Based on an iterative method, we construct a block upper triangular preconditioner. The convergence…

Numerical Analysis · Mathematics 2022-01-28 Hamed Aslani , Davod Khojasteh Salkuyeh

We study the convergence of a class of Runge-Kutta type schemes for backward stochastic differential equations (BSDEs) in a Markovian framework. The schemes belonging to the class under consideration benefit from a certain stability…

Probability · Mathematics 2014-03-24 Jean-François Chassagneux , Dan Crisan

Runge-Kutta methods have an irreplaceable position among numerical methods designed to solve ordinary differential equations. Especially, implicit ones are suitable for approximating solutions of stiff initial value problems. We propose a…

Numerical Analysis · Mathematics 2024-12-13 Hana Mizerová , Katarína Tvrdá

Topology optimization problems generally support multiple local minima, and real-world applications are typically three-dimensional. In previous work [I. P. A. Papadopoulos, P. E. Farrell, and T. M. Surowiec, Computing multiple solutions of…

Numerical Analysis · Mathematics 2022-11-23 Ioannis P. A. Papadopoulos , Patrick E. Farrell

We derive a new parallel-in-time approach for solving large-scale optimization problems constrained by time-dependent partial differential equations arising from fluid dynamics. The solver involves the use of a block circulant approximation…

Numerical Analysis · Mathematics 2024-05-30 Bernhard Heinzelreiter , John W. Pearson