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The paper presents a two-dimensional geometrically nonlinear formulation of a beam element that can accommodate arbitrarily large rotations of cross sections. The formulation is based on the integrated form of equilibrium equations, which…

Numerical Analysis · Mathematics 2021-04-20 Milan Jirásek , Emma La Malfa Ribolla , Martin Horák

In this paper, we develop fast procedures for solving linear systems arising from discretization of ordinary and partial differential equations with Caputo fractional derivative w.r.t time variable. First, we consider a finite difference…

Analysis of PDEs · Mathematics 2018-02-01 Zhengguang Liu , Aijie Cheng , Xiaoli Li , Hong Wang

Fast Fourier transform algorithms are an arsenal of effective tools for solving various problems of analysis and high-speed processing of signals of various natures. Almost all of these algorithms are designed to process sequences of…

Data Structures and Algorithms · Computer Science 2025-04-11 Aleksandr Cariow

Multivariate partial fractioning is a powerful tool for simplifying rational function coefficients in scattering amplitude computations. Since current research problems lead to large sets of complicated rational functions, performance of…

High Energy Physics - Phenomenology · Physics 2022-12-19 Dominik Bendle , Janko Boehm , Murray Heymann , Rourou Ma , Mirko Rahn , Lukas Ristau , Marcel Wittmann , Zihao Wu , Yang Zhang

We introduce a high-order numerical scheme for fractional ordinary differential equations with the Caputo derivative. The method is developed by dividing the domain into a number of subintervals, and applying the quadratic interpolation on…

Numerical Analysis · Mathematics 2020-02-25 Junying Cao , Zhenning Cai

A Radial Basis Function Generated Finite-Differences (RBF-FD) inspired technique for evaluating definite integrals over the volume of the ball in three dimensions is described. Such methods are necessary in many areas of Applied…

Numerical Analysis · Mathematics 2020-06-11 Jonah A. Reeger

Data-driven discovery of "hidden physics" -- i.e., machine learning of differential equation models underlying observed data -- has recently been approached by embedding the discovery problem into a Gaussian Process regression of spatial…

Machine Learning · Computer Science 2019-08-05 Mamikon Gulian , Maziar Raissi , Paris Perdikaris , George Karniadakis

Integral-equation-based fast direct solvers for electromagnetic scattering can substantially reduce computational costs, especially in the presence of multiple excitations. We recently proposed a new high-frequency fast direct solver…

Numerical Analysis · Mathematics 2026-03-05 V. Giunzioni , C. Henry , A. Merlini , F. P. Andriulli

Diffusive representations of fractional derivatives have proven to be useful tools in the construction of fast and memory efficient numerical methods for solving fractional differential equations. A common challenge in many of the known…

Numerical Analysis · Mathematics 2022-04-11 Kai Diethelm

Linear differential equations of arbitrary order with polynomial coefficients are considered. Specifically, necessary and sufficient conditions for the existence of polynomial solutions of a given degree are obtained for these equations. An…

Mathematical Physics · Physics 2011-09-27 H. Azad , A. Laradji , M. T. Mustafa

We look for differential equations satisfied by the generalized Jacobi polynomials which are orthogonal on the interval [-1,1] with respect to the classical weight function for the Jacobi polynomials together with point masses at both…

Classical Analysis and ODEs · Mathematics 2007-05-23 Roelof Koekoek

Quantum algorithms have been developed for efficiently solving linear algebra tasks. However, they generally require deep circuits and hence universal fault-tolerant quantum computers. In this work, we propose variational algorithms for…

Quantum Physics · Physics 2021-12-28 Xiaosi Xu , Jinzhao Sun , Suguru Endo , Ying Li , Simon C. Benjamin , Xiao Yuan

In this article, we present an $O(N \log N)$ rapidly convergent algorithm for the numerical approximation of the convolution integral with radially symmetric weakly singular kernels and compactly supported densities. To achieve the reduced…

Numerical Analysis · Mathematics 2021-07-09 Awanish Kumar Tiwari , Ambuj Pandey , Jagabandhu Paul , Akash Anand

In this paper, we develop a numerical scheme for the space-time fractional parabolic equation, i.e., an equation involving a fractional time derivative and a fractional spatial operator. Both the initial value problem and the…

Numerical Analysis · Mathematics 2017-08-18 Andrea Bonito , Wenyu Lei , Joseph E. Pasciak

The finite element method is used to approximately solve boundary value problems for differential equations. The method discretises the parameter space and finds an approximate solution by solving a large system of linear equations. Here we…

Quantum Physics · Physics 2016-03-23 Ashley Montanaro , Sam Pallister

This paper presents an algorithmic framework for the minimization of strictly convex quadratic functions. The framework is flexible and generic. At every iteration the search direction is a linear combination of the negative gradient, as…

Optimization and Control · Mathematics 2025-05-08 Liam MacDonald , Rua Murray , Rachael Tappenden

In this paper, we propose and analyze a fast two-point gradient algorithm for solving nonlinear ill-posed problems, which is based on the sequential subspace optimization method. A complete convergence analysis is provided under the…

Analysis of PDEs · Mathematics 2019-11-06 Guangyu Gao , Bo Han , Shanshan Tong

In this paper, a nonlinear system of fractional ordinary differential equations with multiple scales in time is investigated. We are interested in the effective long-term computation of the solution. The main challenge is how to obtain the…

Numerical Analysis · Mathematics 2022-01-07 Zhaoyang Wang , Ping Lin

This study reexamines diffusive representations for fractional integrals with the goal of pioneering new variants of such representations. These variants aim to offer highly efficient numerical algorithms for the approximate computation of…

Numerical Analysis · Mathematics 2025-07-08 Renu Chaudhary , Kai Diethelm

Linear algebraic primitives are at the core of many modern algorithms in engineering, science, and machine learning. Hence, accelerating these primitives with novel computing hardware would have tremendous economic impact. Quantum computing…

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