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Many iterative parallel-in-time algorithms have been shown to be highly efficient for diffusion-dominated partial differential equations (PDEs), but are inefficient or even divergent when applied to advection-dominated PDEs. We consider the…

Numerical Analysis · Mathematics 2022-04-26 H. De Sterck , R. D. Falgout , O. A. Krzysik

Immersed boundary methods have attracted substantial interest in the last decades due to their potential for computations involving complex geometries. Often these cannot be efficiently discretized using boundary-fitted finite elements.…

Computational Engineering, Finance, and Science · Computer Science 2026-01-13 Tim Bürchner , Lars Radtke , Philipp Kopp , Stefan Kollmannsberger , Ernst Rank , Alexander Düster

High fidelity scientific simulations modeling physical phenomena typically require solving large linear systems of equations which result from discretization of a partial differential equation (PDE) by some numerical method. This step often…

Mathematical Software · Computer Science 2020-07-01 Mohammad Shafaet Islam , Qiqi Wang

Two types of second-order in time partial differential equations (PDEs), namely semilinear wave equations and semilinear beam equations are considered. To solve these equations with exponential integrators, we present an approach to compute…

Numerical Analysis · Mathematics 2022-10-13 Alexander Ostermann , Duy Phan

Preconditioning of a linear system obtained from spectral discretization of time-dependent PDEs often results in a full matrix which is expensive to compute and store specially when the problem size increases. A matrix-free implementation…

Statistics Theory · Mathematics 2016-06-09 A. Ghasemi , L. K. Taylor

Direct discretization of continuum kinetic equations, like the Vlasov equation, are under-utilized because the distribution function generally exists in a high-dimensional (>3D) space and computational cost increases geometrically with…

Mathematical Software · Computer Science 2015-06-04 J. A. F. Hittinger , J. W. Banks

The numerical solution of large-scale PDEs, such as those occurring in data-driven applications, unavoidably require powerful parallel computers and tailored parallel algorithms to make the best possible use of them. In fact, considerations…

Numerical Analysis · Mathematics 2017-05-11 Francisco Bernal , Gonçalo dos Reis , Greig Smith

We present a general and scalable framework for the automated discovery of optimal meta-solvers for the solution of time-dependent nonlinear partial differential equations after appropriate discretization. By integrating classical numerical…

Numerical Analysis · Mathematics 2025-07-02 Youngkyu Lee , Shanqing Liu , Jerome Darbon , George Em Karniadakis

Discrete variational methods show excellent performance in numerical simulations of different mechanical systems. In this paper, we introduce an iterative procedure for the solution of discrete variational equations for boundary value…

Optimization and Control · Mathematics 2022-06-22 Sebastián J. Ferraro , David Martín de Diego , Rodrigo Takuro Sato Martín de Almagro

Solving sparse linear systems from discretized PDEs is challenging. Direct solvers have in many cases quadratic complexity (depending on geometry), while iterative solvers require problem dependent preconditioners to be robust and…

Numerical Analysis · Mathematics 2017-03-14 Kai Yang , Hadi Pouransari , Eric Darve

The solution of partial differential equations (PDEs) plays a central role in numerous applications in science and engineering, particularly those involving multiphase flow in porous media. Complex, nonlinear systems govern these problems…

The solution for non-linear, complex partial differential Equations (PDEs) is achieved through numerical approximations, which yield a linear system of equations. This approach is prevalent in Computational Fluid Dynamics (CFD), but it…

Fluid Dynamics · Physics 2024-09-06 Ferdin Sagai Don Bosco , Dhamotharan S , Rut Lineswala , Abhishek Chopra

In this paper, we develop an ensemble-based time-stepping algorithm to efficiently find numerical solutions to a group of linear, second-order parabolic partial differential equations (PDEs). Particularly, the PDE models in the group could…

Numerical Analysis · Mathematics 2017-10-18 Yan Luo , Zhu Wang

Model predictive control (MPC) is a powerful framework for optimal control of dynamical systems. However, MPC solvers suffer from a high computational burden that restricts their application to systems with low sampling frequency. This…

Optimization and Control · Mathematics 2025-03-12 Casian Iacob , Hany Abdulsamad , Simo Särkkä

We introduce a time-integrator to sample with high order of accuracy the invariant distribution for a class of semilinear SPDEs driven by an additive space-time noise. Combined with a postprocessor, the new method is a modification with…

Numerical Analysis · Mathematics 2016-08-18 Charles-Edouard Bréhier , Gilles Vilmart

A novel compressed matrix format is proposed that combines an adaptive hierarchical partitioning of the matrix with low-rank approximation. One typical application is the approximation of discretized functions on rectangular domains; the…

Numerical Analysis · Mathematics 2021-11-05 Stefano Massei , Leonardo Robol , Daniel Kressner

We present and analyze a parallel implementation of a parallel-in-time collocation method based on $\alpha$-circulant preconditioned Richardson iterations. While many papers explore this family of single-level, time-parallel "all-at-once"…

Numerical Analysis · Mathematics 2023-02-16 Gayatri Caklovic , Robert Speck , Martin Frank

In this paper, we propose high order numerical methods to solve a 2D advection diffusion equation, in the highly oscillatory regime. We use an integrator strategy that allows the construction of arbitrary high-order schemes {leading} to an…

Numerical Analysis · Mathematics 2024-11-11 Clarissa Astuto

This manuscript presents an efficient solver for the linear system that arises from the Hierarchical Poincar\'e-Steklov (HPS) discretization of three dimensional variable coefficient Helmholtz problems. Previous work on the HPS method has…

Numerical Analysis · Mathematics 2023-01-18 José Pablo Lucero Lorca , Natalie Beams , Damien Beecroft , Adrianna Gillman

Within this paper, we introduce partially and fully decoupled time stepping schemes for linear thermo-poroelasticity. This means that the mechanics, heat, and flow equations can be solved sequentially. We provide sufficient conditions on…

Numerical Analysis · Mathematics 2026-03-17 R. Altmann , R. Maier , J. Schmeck
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