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We describe an efficient algorithm for computing the matrix vector products that appear in the numerical resolution of boundary integral equations in 2 space dimension. This work is an extension of the so-called Sparse Cardinal Sine…

Numerical Analysis · Mathematics 2017-11-22 Martin Averseng

Numerically solving ordinary differential equations (ODEs) is a naturally serial process and as a result the vast majority of ODE solver software are serial. In this manuscript we developed a set of parallelized ODE solvers using…

Numerical Analysis · Mathematics 2022-09-13 Utkarsh , Chris Elrod , Yingbo Ma , Christopher Rackauckas

Recent developments in high peak-power table-top laser systems reaching highly relativistic light intensities have led to significant advances in laser-driven particle acceleration schemes (mainly the laser wakefield acceleration, LWFA)…

Plasma Physics · Physics 2026-05-13 Szilárd Majorosi , Nasr A. M. Hafz , Zsolt Lécz

Quantum computing has attracted significant interest in the optimization community because it potentially can solve classes of optimization problems faster than conventional supercomputers. Several researchers proposed quantum computing…

Quantum Physics · Physics 2023-02-14 Mohammadhossein Mohammadisiahroudi , Ramin Fakhimi , Tamás Terlaky

A fast algorithm (linear in the degrees of freedom) for the solution of linear variable-coefficient rational-order fractional integral and differential equations is described. The approach is related to the ultraspherical method for…

Numerical Analysis · Mathematics 2017-12-04 Nicholas Hale , Sheehan Olver

A high-order convergent numerical method for solving linear and non-linear parabolic PDEs is presented. The time-stepping is done via an explicit, singly diagonally implicit Runge-Kutta (ESDIRK) method of order 4 or 5, and for the implicit…

Numerical Analysis · Mathematics 2018-11-13 Tracy Babb , Per-Gunnar Martinsson , Daniel Appelo

Semidefinite programming (SDP) is a fundamental class of convex optimization problems with diverse applications in mathematics, engineering, machine learning, and related disciplines. This paper investigates the application of the…

Optimization and Control · Mathematics 2025-10-15 Zilong Cui , Ran Gu

We propose an iterative solution method for the 3D high-frequency Helmholtz equation that exploits a contour integral formulation of spectral projectors. In this framework, the solution in certain invariant subspaces is approximated by…

Numerical Analysis · Mathematics 2018-11-30 Xiao Liu , Yuanzhe Xi , Yousef Saad , Maarten V. de Hoop

Recent advancements in quantum computing and quantum-inspired algorithms have sparked renewed interest in binary optimization. These hardware and software innovations promise to revolutionize solution times for complex problems. In this…

We developed fast direct solver for 3D Helmholtz and Maxwell equations in layered medium. The algorithm is based on the ideas of cyclic reduction for separable matrices. For the grids with major uniform part (within the survey domain in the…

Numerical Analysis · Mathematics 2019-09-04 Vladimir Druskin , Mikhail Zaslavsky

The diffuse-domain, or smoothed boundary, method is an attractive approach for solving partial differential equations in complex geometries because of its simplicity and flexibility. In this method the complex geometry is embedded into a…

Numerical Analysis · Mathematics 2019-12-02 Fei Yu , Zhenlin Guo , John Lowengrub

In this paper we generalize and improve a recently developed domain decomposition preconditioner for the iterative solution of discretized Helmholtz equations. We introduce an improved method for transmission at the internal boundaries…

Numerical Analysis · Mathematics 2016-07-12 Christiaan C. Stolk

The present work develops hybrid multigrid methods for high-order discontinuous Galerkin discretizations of elliptic problems. Fast matrix-free operator evaluation on tensor product elements is used to devise a computationally efficient PDE…

Computational Physics · Physics 2020-06-24 Niklas Fehn , Peter Munch , Wolfgang A. Wall , Martin Kronbichler

We introduce two new methods for deterministic convex optimization problems: QCC (Quadratic Cuts for Convex optimization) and QB (Quadratic Bundle method). We prove the complexity of these methods for composite optimization problems which…

Optimization and Control · Mathematics 2024-10-02 Vincent Guigues , Adriana Washington

We present direct logarithmically optimal in theory and fast in practice algorithms to implement the tensor product high order finite element method on multi-dimensional rectangular parallelepipeds for solving PDEs of the Poisson kind. They…

Numerical Analysis · Mathematics 2026-01-05 Alexander Zlotnik , Ilya Zlotnik

This paper introduces a novel geometric multigrid solver for unstructured curved surfaces. Multigrid methods are highly efficient iterative methods for solving systems of linear equations. Despite the success in solving problems defined on…

Graphics · Computer Science 2021-05-05 Hsueh-Ti Derek Liu , Jiayi Eris Zhang , Mirela Ben-Chen , Alec Jacobson

When modeling scientific and industrial problems, geometries are typically modeled by explicit boundary representations obtained from computer-aided design software. Unfitted (also known as embedded or immersed) finite element methods offer…

Computational Engineering, Finance, and Science · Computer Science 2024-05-24 Pere A. Martorell , Santiago Badia

In this paper the author introduces a new domain decomposition method for the solution of discretised integral equation eigenvalue problems. The new domain decomposition method is motivated by the so-called automated multi-level…

Numerical Analysis · Mathematics 2017-12-29 Peter Gerds

We present a fast spectral Galerkin scheme for the discretization of boundary integral equations arising from two-dimensional Helmholtz transmission problems in multi-layered periodic structures or gratings. Employing suitably parametrized…

Numerical Analysis · Mathematics 2020-11-06 José Pinto , Rubén Aylwin , Carlos Jerez-Hanckes

We introduce a cutting-plane framework for nonconvex quadratic programs (QPs) that progressively tightens convex relaxations. Our approach leverages the doubly nonnegative (DNN) relaxation to compute strong lower bounds and generate…

Optimization and Control · Mathematics 2025-10-06 Zheng Qu , Defeng Sun , Jintao Xu