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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

A preconditioning framework for the coupled problem of frictional contact mechanics and fluid flow in the fracture network is presented. The porous medium is discretized using low-order continuous finite elements, with cell-centered…

Numerical Analysis · Mathematics 2022-05-25 Andrea Franceschini , Laura Gazzola , Massimiliano Ferronato

We describe a new technique for computing lower-bounds on the minimum energy configuration of a planar Markov Random Field (MRF). Our method successively adds large numbers of constraints and enforces consistency over binary projections of…

Machine Learning · Computer Science 2012-02-20 Julian Yarkony , Ragib Morshed , Alexander T. Ihler , Charless C. Fowlkes

The superior ability of nanostructures to manipulate light has propelled extensive applications in nano-electromagnetic components and devices. Computational electromagnetics plays a critical role in characterizing and optimizing the…

Computational Physics · Physics 2025-01-24 Chengnian Huang , Wei E. I. Sha

Unless special conditions apply, the attempt to solve ill-conditioned systems of linear equations with standard numerical methods leads to uncontrollably high numerical error. Often, such systems arise from the discretization of operator…

Numerical Analysis · Mathematics 2021-05-18 Stephan Mohr , Yuji Nakatsukasa , Carolina Urzúa-Torres

Quantum linear system solvers like the Quantum Singular Value Transformation (QSVT) require a block encoding of the system matrix $A$ within a unitary operator $U_A$. Unfortunately, block encoding often results in significant…

Quantum Physics · Physics 2025-10-28 Leigh Lapworth , Christoph Sünderhauf

Preconditioning is a key component of MCMC algorithms that improves sampling efficiency by facilitating exploration of geometrically complex target distributions through an invertible map. While linear preconditioners are often sufficient…

Machine Learning · Computer Science 2025-11-05 David Nabergoj , Erik Štrumbelj

Circulant preconditioners are commonly used to accelerate the rate of convergence of iterative methods when solving linear systems of equations with a Toeplitz matrix. Block extensions that can be applied when the system has a block…

Numerical Analysis · Mathematics 2016-09-06 L. Dykes , S. Noschese , L. Reichel

We introduce a relaxed inertial forward-backward-forward (RIFBF) splitting algorithm for approaching the set of zeros of the sum of a maximally monotone operator and a single-valued monotone and Lipschitz continuous operator. This work aims…

Optimization and Control · Mathematics 2020-03-24 Radu Ioan Bot , Michael Sedlmayer , Phan Tu Vuong

The convergence of the conjugate gradient method for solving large-scale and sparse linear equation systems depends on the spectral properties of the system matrix, which can be improved by preconditioning. In this paper, we develop a…

Optimization and Control · Mathematics 2024-10-25 Paul Häusner , Ozan Öktem , Jens Sjölund

Simulation of multiphase poromechanics involves solving a multi-physics problem in which multiphase flow and transport are tightly coupled with the porous medium deformation. To capture this dynamic interplay, fully implicit methods, also…

Numerical Analysis · Mathematics 2021-01-08 Quan M. Bui , Daniel Osei-Kuffuor , Nicola Castelletto , Joshua A. White

Most of the FFT methods available for homogenization of the mechanical response use the strain/deformation gradient as unknown, imposing their compatibility using Green's functions or projection operators. This implies the allocation of…

Computational Engineering, Finance, and Science · Computer Science 2019-08-27 Sergio Lucarini , Javier Segurado

Random Feature Methods (RFMs) and their variants such as extreme learning machine finite-basis physics-informed neural networks (ELM-FBPINNs) offer a scalable approach for solving partial differential equations (PDEs) by using localized,…

Numerical Analysis · Mathematics 2025-09-03 Jan Willem van Beek , Victorita Dolean , Ben Moseley

In this work, we consider fracture propagation in nearly incompressible and (fully) incompressible materials using a phase-field formulation. We use a mixed form of the elasticity equation to overcome volume locking effects and develop a…

Numerical Analysis · Mathematics 2022-02-10 Timo Heister , Katrin Mang , Thomas Wick

Nonnegative matrix factorization (NMF) under the separability assumption can provably be solved efficiently, even in the presence of noise, and has been shown to be a powerful technique in document classification and hyperspectral unmixing.…

Machine Learning · Statistics 2015-04-02 Nicolas Gillis , Stephen A. Vavasis

The eXtended Finite Element Method (XFEM) is an approach for solving problems with non-smooth solutions. In the XFEM, the approximate solution is locally enriched to capture discontinuities without requiring a mesh which conforms to the…

Numerical Analysis · Mathematics 2013-12-23 Christapher Lang , David Makhija , Alireza Doostan , Kurt Maute

Robust Principal Component Analysis (RPCA) and its associated non-convex relaxation methods constitute a significant component of matrix completion problems, wherein matrix factorization strategies effectively reduce dimensionality and…

Optimization and Control · Mathematics 2024-03-28 Zhenzhi Qin , Liping Zhang

We aim to solve the incompressible Navier-Stokes equations within the complex microstructure of a porous material. Discretizing the equations on a fine grid using a staggered (e.g., marker-and-cell, mixed FEM) scheme results in a nonlinear…

Numerical Analysis · Mathematics 2025-10-28 Kangan Li , Yashar Mehmani

We consider iterative methods for solving the linearised Navier-Stokes equations arising from two-phase flow problems and the efficient preconditioning of such systems when using mixed finite element methods. Our target application is…

Numerical Analysis · Mathematics 2020-05-18 Niall Bootland , Alistair Bentley , Christopher Kees , Andrew Wathen

This paper focuses on the AC Optimal Power Flow (OPF) problem for multi-phase systems. Particular emphasis is given to systems with high integration of renewables, where adjustments of the real and reactive output powers from renewable…

Optimization and Control · Mathematics 2016-12-22 Ahmed S. Zamzam , Nicholas D. Sidiropoulos , Emiliano Dall'Anese