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In this work, the problem of optimizing damper positions in vibrational systems is investigated. The objective is to determine the positions of external dampers in such a way that the influence of the input on the output is minimized. The…

Numerical Analysis · Mathematics 2025-06-26 Jennifer Przybilla , Matea Ugrica Vukojević , Ninolsav Truhar , Peter Benner

We develop randomized (block) coordinate descent (CD) methods for linearly constrained convex optimization. Unlike most CD methods, we do not assume the constraints to be separable, but let them be coupled linearly. To our knowledge, ours…

Optimization and Control · Mathematics 2015-06-11 Sashank Reddi , Ahmed Hefny , Carlton Downey , Avinava Dubey , Suvrit Sra

Deep-Learning-based Variational Monte Carlo (DL-VMC) has recently emerged as a highly accurate approach for finding approximate solutions to the many-electron Schr\"odinger equation. Despite its favorable scaling with the number of…

Computational Physics · Physics 2024-05-14 Leon Gerard , Michael Scherbela , Halvard Sutterud , Matthew Foulkes , Philipp Grohs

We consider spin systems on the integer lattice graph $\mathbb{Z}^d$ with nearest-neighbor interactions. We develop a combinatorial framework for establishing that exponential decay with distance of spin correlations, specifically the…

Discrete Mathematics · Computer Science 2017-08-09 Antonio Blanca , Pietro Caputo , Alistair Sinclair , Eric Vigoda

In this paper, we propose a class of matrix splitting-based fixed-point iteration (FPI) methods for solving the vertical nonlinear complementarity problem (VNCP). Under appropriate conditions, we present two convergence results obtained…

Optimization and Control · Mathematics 2025-01-15 Wang Yapeng , Mu Xuewen

This work extends our previous study from S. Shrestha et al. (2024) by introducing a new abstract framework for Variational Multiscale (VMS) methods at the discrete level. We introduce the concept of what we define as the optimal projector…

Numerical Analysis · Mathematics 2025-03-04 Suyash Shrestha , Marc Gerritsma , Gonzalo Rubio , Steven Hulshoff , Esteban Ferrer

A coarse grid correction (CGC) approach is proposed to enhance the efficiency of the matrix exponential and $\varphi$ matrix function evaluations. The approach is intended for iterative methods computing the matrix-vector products with…

Numerical Analysis · Mathematics 2024-04-23 Mike A. Botchev

Stochastic sampling methods are arguably the most direct and least intrusive means of incorporating parametric uncertainty into numerical simulations of partial differential equations with random inputs. However, to achieve an overall error…

Numerical Analysis · Mathematics 2014-04-09 Hans-Werner van Wyk

We show that a rectangular collocation method, equivalent to evaluating all matrix elements with a quadrature-like scheme and using more points than basis functions, is an effective approach for solving the electronic Schr\"odinger equation…

Computational Physics · Physics 2021-12-08 Sergei Manzhos , Tucker Carrington

Variational inequalities are a formalism that includes games, minimization, saddle point, and equilibrium problems as special cases. Methods for variational inequalities are therefore universal approaches for many applied tasks, including…

This work presents a non-linear extension of the high-order discretisation framework based on the Variational Multiscale (VMS) method previously introduced for steady linear problems. We build on the concept of an optimal projector defined…

Numerical Analysis · Mathematics 2025-12-22 Suyash Shrestha , Marc Gerritsma , Gonzalo Rubio , Steven Hulshoff , Esteban Ferrer

We present a strong form, meshless point collocation explicit solver for the numerical solution of the transient, incompressible, viscous Navier-Stokes (N-S) equations in two dimensions. We numerically solve the governing flow equations in…

We propose a collocation method based on multivariate polynomial splines over triangulation or tetrahedralization for the numerical solution of partial differential equations. We start with a detailed explanation of the method for the…

Numerical Analysis · Mathematics 2023-04-18 Ming-Jun Lai , Jinsil Lee

Multilevel techniques are efficient approaches for solving the large linear systems that arise from discretized partial differential equations and other problems. While geometric multigrid requires detailed knowledge about the underlying…

Numerical Analysis · Mathematics 2023-01-23 Tareq. U. Zaman , Scott P. MacLachlan , Luke N. Olson , Matt West

In this paper, we develop an EXCMG method to solve the three-dimensional Poisson equation on rectangular domains by using the compact finite difference (FD) method with unequal meshsizes in different coordinate directions. The resulting…

Numerical Analysis · Mathematics 2016-09-04 Kejia Pan , Dongdong He , Hongling Hu

This paper presents an efficient solution to 3D-LiDAR-based Monte Carlo localization (MCL). MCL robustly works if particles are exactly sampled around the ground truth. An inertial navigation system (INS) can be used for accurate sampling,…

Robotics · Computer Science 2023-03-03 Naoki Akai

The solution of saddle-point problems, such as the Stokes equations, is a challenging task, especially in large-scale problems. Multigrid methods are one of the most efficient solvers for such systems of equations and can achieve…

Numerical Analysis · Mathematics 2022-04-13 S. Saberi , G. Meschke , A. Vogel

Multigrid methods are popular iterative methods for solving large-scale sparse systems of linear equations. We present a mixed precision formulation of the multigrid V-cycle with general assumptions on the finite precision errors coming…

Numerical Analysis · Mathematics 2025-11-07 Petr Vacek , Hartwig Anzt , Erin Carson , Nils Kohl , Ulrich Rüde , Yu-Hsiang Tsai

Recently, the spatial modulation (SM) technique has been proposed for visible light communication (VLC). This paper investigates the average symbol error rate (SER) for the VLC using adaptive spatial modulation (ASM). In the system, the…

Information Theory · Computer Science 2018-07-27 Jin-Yuan Wang , Jian-Xia Zhu , Sheng-Hong Lin , Jun-Bo Wang

In this work we introduce and analyze a new multiscale method for strongly nonlinear monotone equations in the spirit of the Localized Orthogonal Decomposition. A problem-adapted multiscale space is constructed by solving linear local…

Numerical Analysis · Mathematics 2020-12-16 Barbara Verfürth