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A symbolic computational algorithm which detects " linear "` solutions of nonlinear polynomial differential equations of single functions, is developed throughout this paper.

Dynamical Systems · Mathematics 2007-05-23 Stelios Kotsios

We propose a novel iterative algorithm for solving a large sparse linear system. The method is based on the EM algorithm. If the system has a unique solution, the algorithm guarantees convergence with a geometric rate. Otherwise,…

Numerical Analysis · Mathematics 2018-08-03 Minwoo Chae , Stephen G. Walker

This paper offers a matrix-free first-order numerical method to solve large-scale conic optimization problems. Solving systems of linear equations pose the most computationally challenging part in both first-order and second-order numerical…

Optimization and Control · Mathematics 2022-03-11 Muhammad Adil , Ramtin Madani , Sasan Tavakkol , Ali Davoudi

A generalized eigenvalue algorithm for tridiagonal matrix pencils is presented. The algorithm appears as the time evolution equation of a nonautonomous discrete integrable system associated with a polynomial sequence which has some…

Numerical Analysis · Mathematics 2016-01-19 Kazuki Maeda , Satoshi Tsujimoto

A simple iteration methodology for the solution of a set of a linear algebraic equations is presented. The explanation of this method is based on a pure geometrical interpretation and pictorial representation. Convergence using this method…

Computational Physics · Physics 2010-12-30 Avas V. Khugaev , Renat A. Sultanov , D. Guster

A novel orthogonalization-free method together with two specific algorithms are proposed to solve extreme eigenvalue problems. On top of gradient-based algorithms, the proposed algorithms modify the multi-column gradient such that earlier…

Numerical Analysis · Mathematics 2021-10-15 Weiguo Gao , Yingzhou Li , Bichen Lu

Modern advances in general-purpose computer algebra systems offer solutions to a variety of problems, which in the past required substantial time investments by trained mathematicians. An excellent example of such development are the…

Rings and Algebras · Mathematics 2023-05-18 Dimiter Prodanov

This paper introduces a fast and numerically stable algorithm for the solution of fourth-order linear boundary value problems on an interval. This type of equation arises in a variety of settings in physics and signal processing. Our method…

Numerical Analysis · Computer Science 2020-01-13 William Leeb , Vladimir Rokhlin

We present two new algorithms for the computation of the q-integer linear decomposition of a multivariate polynomial. Such a decomposition is essential for the treatment of q-hypergeometric symbolic summation via creative telescoping and…

Symbolic Computation · Computer Science 2021-02-15 Mark Giesbrecht , Hui Huang , George Labahn , Eugene Zima

We provide algorithms for symbolic integration of hyperlogarithms multiplied by rational functions, which also include multiple polylogarithms when their arguments are rational functions. These algorithms are implemented in Maple and we…

High Energy Physics - Theory · Physics 2015-01-06 Erik Panzer

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

Nonlinear least-squares problems are a special class of unconstrained optimization problems in which their gradient and Hessian have special structures. In this paper, we exploit these structures and proposed a matrix-free algorithm with a…

Optimization and Control · Mathematics 2020-02-06 Aliyu Muhammed Awwal , Poom Kumam , Hassan Mohammad

We propose and implement an algorithm for solving an overdetermined system of partial differential equations in one unknown. Our approach relies on Bour-Mayer method to determine compatibility conditions via Jacobi-Mayer brackets. We solve…

Symbolic Computation · Computer Science 2017-03-07 Célestin Wafo Soh

We consider the identification of spatially distributed parameters under $H^1$ regularization. Solving the associated minimization problem by Gauss-Newton iteration results in linearized problems to be solved in each step that can be cast…

Numerical Analysis · Mathematics 2023-08-23 Jan Blechta , Oliver G. Ernst

In this paper we consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore…

Numerical Analysis · Mathematics 2016-05-30 Oliver J. D. Barrowclough , Tor Dokken

In this article, we present a family of numerical approaches to solve high-dimensional linear non-symmetric problems. The principle of these methods is to approximate a function which depends on a large number of variates by a sum of tensor…

Functional Analysis · Mathematics 2012-10-26 Eric Cances , Virginie Ehrlacher , Tony Lelievre

Three loop ladder and $V$-topology diagrams contributing to the massive operator matrix element $A_{Qg}$ are calculated. The corresponding objects can all be expressed in terms of nested sums and recurrences depending on the Mellin variable…

High Energy Physics - Phenomenology · Physics 2016-04-20 J. Ablinger , A. Behring , J. Blümlein , A. De Freitas , A. von Manteuffel , C. Schneider

This paper proposes a matrix-free residual evaluation technique for the hybridizable discontinuous Galerkin method requiring a number of operations scaling only linearly with the number of degrees of freedom. The method results from…

Numerical Analysis · Mathematics 2020-07-24 Immo Huismann , Jörg Stiller , Jochen Fröhlich

This paper presents some algorithms in linear algebraic groups. These algorithms solve the word problem and compute the spinor norm for orthogonal groups. This gives us an algorithmic definition of the spinor norm. We compute the double…

Group Theory · Mathematics 2020-05-19 Sushil Bhunia , Ayan Mahalanobis , Pralhad Shinde , Anupam Singh

Solving systems of ordinary differential equations (ODEs) is essential when it comes to understanding the behavior of dynamical systems. Yet, automated solving remains challenging, in particular for nonlinear systems. Computer algebra…

Machine Learning · Computer Science 2025-06-25 Paul Kahlmeyer , Niklas Merk , Joachim Giesen