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Micromagnetics depends on high-fidelity numerical methods for magnetization dynamics. This work proposes a third-order temporal accuracy scheme for the Landau-Lifshitz-Gilbert equation, addressing accuracy-efficiency trade-offs in existing…

Mathematical Physics · Physics 2025-11-17 Changjian Xie , Cheng Wang

Explicit time advancement for continuous finite elements requires the inversion of a global mass matrix. For spectral element simulations on quadrilaterals and hexahedra, there is an accurate approximate mass matrix which is diagonal,…

Analysis of PDEs · Mathematics 2019-06-27 Jay Appleton , Brian Helenbrook

This paper presents a multi-field decomposed approach for hyper-reduced order modeling to overcome the limitations of traditional model reduction techniques for gradient-extended damage-plasticity simulations. The discrete empirical…

Computational Engineering, Finance, and Science · Computer Science 2026-01-07 Jannick Kehls , Stephan Ritzert , Lars Breuer , Qinghua Zhang , Stefanie Reese , Tim Brepols

Multipoint polynomial evaluation and interpolation are fundamental for modern symbolic and numerical computing. The known algorithms solve both problems over any field of constants in nearly linear arithmetic time, but the cost grows to…

Numerical Analysis · Mathematics 2017-04-19 Victor Y. Pan

In micromagnetic simulations, the demagnetization field is by far the computationally most expensive field component and often a limiting factor in large multilayer systems. We present an exact method to calculate the demagnetization field…

Computational Physics · Physics 2020-03-18 Paul Heistracher , Florian Bruckner , Claas Abert , Christoph Vogler , Dieter Suess

Functional iterations such as Newton's are a popular tool for polynomial root-finding. We consider realistic situation where some (e.g., better-conditioned) roots have already been approximated and where further computations is directed to…

Numerical Analysis · Mathematics 2019-07-09 Remi Imbach , Victor Y. Pan , Chee Yap , Ilias S. Kotsireas , Vitaly Zaderman

The matrix formation associated to high-order discretizations is known to be numerically demanding. Based on the existing procedure of interpolation and lookup, we design a multiscale assembly procedure to reduce the exorbitant assembly…

Numerical Analysis · Mathematics 2021-07-21 Thibaut Hirschler , Pablo Antolin , Annalisa Buffa

Polynomial approximations of functions are widely used in scientific computing. In certain applications, it is often desired to require the polynomial approximation to be non-negative (resp. non-positive), or bounded within a given range,…

Numerical Analysis · Mathematics 2024-11-12 Yuan Chen , Dongbin Xiu , Xiangxiong Zhang

An implementation of the fast multiple method (FMM) is performed for magnetic systems with long-ranged dipolar interactions. Expansion in spherical harmonics of the original FMM is replaced by expansion of polynomials in Cartesian…

Computational Physics · Physics 2015-05-13 Wen Zhang , Stephan Haas

To address the magnetization dynamics in ferromagnetic materials described by the Landau-Lifshitz-Gilbert equation under large damping parameters, a third-order accurate numerical scheme is developed by building upon a second-order method…

Numerical Analysis · Mathematics 2025-10-31 Changjian Xie , Cheng Wang

In the finite difference method which is commonly used in computational micromagnetics, the demagnetizing field is usually computed as a convolution of the magnetization vector field with the demagnetizing tensor that describes the…

Computational Physics · Physics 2015-06-04 Dmitri Chernyshenko , Hans Fangohr

In this paper we explore acceleration techniques for large scale nonconvex optimization problems with special focuses on deep neural networks. The extrapolation scheme is a classical approach for accelerating stochastic gradient descent for…

Machine Learning · Statistics 2018-05-18 Guangzeng Xie , Yitan Wang , Shuchang Zhou , Zhihua Zhang

Diffusion probabilistic models (DPMs), while effective in generating high-quality samples, often suffer from high computational costs due to their iterative sampling process. To address this, we propose an enhanced ODE-based sampling method…

Machine Learning · Computer Science 2025-04-03 Jinyoung Choi , Junoh Kang , Bohyung Han

This article presents a high-order accurate numerical method for the evaluation of singular volume integral operators, with attention focused on operators associated with the Poisson and Helmholtz equations in two dimensions. Following the…

Numerical Analysis · Mathematics 2024-05-24 Thomas G. Anderson , Marc Bonnet , Luiz M. Faria , Carlos Pérez-Arancibia

Provided a special function of one variable and some of its derivatives can be accurately computed over a finite range, a method is presented to build a series of polynomial approximations of the function with a defined relative error over…

Computational Physics · Physics 2007-05-23 C. Semay

A transient magneto-quasistatic vector potential formulation involving nonlinear material is spatially discretized using the finite element method of first and second polynomial order. By applying a generalized Schur complement the…

Computational Engineering, Finance, and Science · Computer Science 2020-11-09 Bernhard Kähne , Markus Clemens , Sebastian Schöps

Computational multi-scale methods capitalize on a large time-scale separation to efficiently simulate slow dynamics over long time intervals. For stochastic systems, one often aims at resolving the statistics of the slowest dynamics. This…

Numerical Analysis · Mathematics 2021-05-14 Kristian Debrabant , Giovanni Samaey , Przemysław Zieliński

In this paper, we propose and analyze the extrapolation method and asymptotically exact a posterior error estimate for eigenvalues of the Morley element. We establish an asymptotic expansion of eigenvalues, and prove an optimal result for…

Numerical Analysis · Mathematics 2022-05-10 Limin Ma , Shudan Tian

Gradient descent method, as one of the major methods in numerical optimization, is the key ingredient in many machine learning algorithms. As one of the most fundamental way to solve the optimization problems, it promises the function value…

Quantum Physics · Physics 2021-02-01 Keren Li , Shijie Wei , Feihao Zhang , Pan Gao , Zengrong Zhou , Tao Xin , Xiaoting Wang , Guilu Long

Nonnegative tensors arise very naturally in many applications that involve large and complex data flows. Due to the relatively small requirement in terms of memory storage and number of operations per step, the (shifted) higher-order power…

Numerical Analysis · Mathematics 2019-08-27 Stefano Cipolla , Michela Redivo-Zaglia , Francesco Tudisco