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Cylindrical algebraic decomposition (CAD) is an important tool for the investigation of semi-algebraic sets, with applications in algebraic geometry and beyond. We have previously reported on an implementation of CAD in Maple which offers…

Symbolic Computation · Computer Science 2015-03-24 Matthew England , David Wilson

In this paper, we describe a reliable symbolic computational algorithm for inverting general cyclic heptadiagonal matrices by using parallel computing along with recursion. The algorithm is implementable to the Computer Algebra System(CAS)…

Symbolic Computation · Computer Science 2015-03-17 A. A. Karawia

This paper proposes an original Riemmanian geometry for low-rank structured elliptical models, i.e., when samples are elliptically distributed with a covariance matrix that has a low-rank plus identity structure. The considered geometry is…

Differential Geometry · Mathematics 2020-01-07 Florent Bouchard , Arnaud Breloy , Guillaume Ginolhac , Alexandre Renaux , Frédéric Pascal

To every subspace arrangement X we will associate symmetric functions P[X] and H[X]. These symmetric functions encode the Hilbert series and the minimal projective resolution of the product ideal associated to the subspace arrangement. They…

Combinatorics · Mathematics 2008-01-30 Harm Derksen

The set theory relations \in, \backslash, \Delta, \cap, and \cup have corollaries in subspace relations. Geometric Algebra is introduced as the ideal framework to explore these subspace operations. The relations \in, \backslash, and \Delta…

Rings and Algebras · Mathematics 2007-05-23 T. A. Bouma , L. Dorst , H. G. J. Pijls

We present a MATLAB toolbox for five different classes of exponential integrators for solving (mildly) stiff ordinary differential equations or time-dependent partial differential equations. For the efficiency of such exponential…

Numerical Analysis · Mathematics 2014-04-18 Georg Jansing

We present an algorithm for decomposing a symmetric tensor, of dimension n and order d as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the…

Symbolic Computation · Computer Science 2010-11-29 Jerome Brachat , Pierre Comon , Bernard Mourrain , Elias Tsigaridas

The conjugate gradient method is a widely used algorithm for the numerical solution of a system of linear equations. It is particularly attractive because it allows one to take advantage of sparse matrices and produces (in case of infinite…

Numerical Analysis · Mathematics 2017-11-27 Sergey Voronin , Christophe Zaroli , Naresh P. Cuntoor

This article introduces a general purpose framework and software to approximate partial differential equations (PDEs). The sparsity patterns of finite element discretized operators is identified automatically using the tools from…

Numerical Analysis · Mathematics 2024-10-17 Kiefer Green , Harbir Antil

The algorithms given in Karney, J. Geodesy 87, 43-55 (2013), to compute geodesics on terrestrial ellipsoids are extended to apply to ellipsoids of revolution with arbitrary eccentricity. For the direct and inverse geodesic problems, this…

Geophysics · Physics 2025-10-28 Charles F. F. Karney

We develop \emph{geometric optimisation} on the manifold of Hermitian positive definite (HPD) matrices. In particular, we consider optimising two types of cost functions: (i) geodesically convex (g-convex); and (ii) log-nonexpansive (LN).…

Functional Analysis · Mathematics 2018-06-04 Suvrit Sra , Reshad Hosseini

We present a MATLAB package called the Pha-sorArray Toolbox that has been developed to make harmonic analysis and control methods both practical and user-friendly. The toolbox adopts an object-oriented architecture that enables intuitive…

Systems and Control · Electrical Eng. & Systems 2025-10-27 Maxime Grosso , Pierre Riedinger , Jamal Daafouz

Several Riemannian metrics and families of Riemannian metrics were defined on the manifold of Symmetric Positive Definite (SPD) matrices. Firstly, we formalize a common general process to define families of metrics: the principle of…

Differential Geometry · Mathematics 2021-11-05 Yann Thanwerdas , Xavier Pennec

Solving dual quaternion equations is an important issue in many fields such as scientific computing and engineering applications. In this paper, we first introduce a new metric function for dual quaternion matrices. Then, we reformulate…

Optimization and Control · Mathematics 2024-11-11 Chen Ling , Chenjian Pan , Liqun Qi

Numerical integral operators of convolution type form the basis of most wave-equation-based methods for processing and imaging of seismic data. As several of these methods require the solution of an inverse problem, multiple forward and…

Geophysics · Physics 2020-11-24 Matteo Ravasi , Ivan Vasconcelos

This paper is a self-contained presentation of certain aspects of the theory of weighted Sobolev spaces and elliptic operators on non-compact Riemannian manifolds. Specifically, we discuss (i) the standard and weighted Sobolev Embedding…

Differential Geometry · Mathematics 2010-05-20 Tommaso Pacini

A new generalized cyclic symmetric structure in the factor matrices of polyadic decompositions of matrix multiplication tensors for non-square matrix multiplication is proposed to reduce the number of variables in the optimization problem…

Numerical Analysis · Mathematics 2025-03-19 Charlotte Vermeylen , Marc Van Barel

We describe algorithms to compute elliptic functions and their relatives (Jacobi theta functions, modular forms, elliptic integrals, and the arithmetic-geometric mean) numerically to arbitrary precision with rigorous error bounds for…

Numerical Analysis · Computer Science 2018-06-19 Fredrik Johansson

In this article, we describe a new algorithm for the expansion of hypergeometric functions about half-integer parameters. The implementation of this algorithm for certain classes of hypergeometric functions in the already existing…

High Energy Physics - Phenomenology · Physics 2008-11-26 T. Huber , D. Maître

We present a novel nonparametric algorithm for symmetry-based disentangling of data manifolds, the Geometric Manifold Component Estimator (GEOMANCER). GEOMANCER provides a partial answer to the question posed by Higgins et al. (2018): is it…

Machine Learning · Statistics 2020-11-19 David Pfau , Irina Higgins , Aleksandar Botev , Sébastien Racanière
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