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We propose a new iterative algorithm for generating a subset of eigenvalues and eigenvectors of large matrices which generalizes the method of optimal relaxations. We also give convergence criteria for the iterative process, investigate its…

General Physics · Physics 2009-11-07 F. Andreozzi , A. Porrino , N. Lo Iudice

Eigenvectors of matrices on a network have been used for understanding spectral clustering and influence of a vertex. For matrices with small geodesic-width, we propose a distributed iterative algorithm in this letter to find eigenvectors…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-11-24 Nazar Emirov , Cheng Cheng , Qiyu Sun , Zhihua Qu

We report on the implementation of an algorithm for computing the set of all regular triangulations of finitely many points in Euclidean space. This algorithm, which we call down-flip reverse search, can be restricted, e.g., to computing…

Combinatorics · Mathematics 2018-10-30 Charles Jordan , Michael Joswig , Lars Kastner

An algorithm is presented for the efficient and accurate computation of the coefficients of the characteristic polynomial of a general square matrix. The algorithm is especially suited for the evaluation of canonical traces in determinant…

Numerical Analysis · Mathematics 2025-10-20 S. Rombouts , K. Heyde

A method is presented for fast diagonalization of a 2x2 or 3x3 real symmetric matrix, that is determination of its eigenvalues and eigenvectors. The Euler angles of the eigenvectors are computed. A small computer algebra program is used to…

Numerical Analysis · Mathematics 2015-02-17 M. J. Kronenburg

A new inverse iteration algorithm that can be used to compute all the eigenvectors of a real symmetric tri-diagonal matrix on parallel computers is developed. The modified Gram-Schmidt orthogonalization is used in the classical inverse…

Numerical Analysis · Computer Science 2012-09-11 Hiroyuki Ishigami , Kinji Kimura , Yoshimasa Nakamura

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

Some skew-symmetrizable integer exchange matrices are associated to ideal (tagged) triangulations of marked bordered surfaces. These exchange matrices admits unfoldings to skew-symmetric matrices. We develop an combinatorial algorithm that…

Combinatorics · Mathematics 2012-02-07 Weiwen Gu

In this paper, we present a generalized Cuppen's divide-and-conquer algorithm for the symmetric tridiagonal eigenproblem. We extend the Cuppen's work to the rank two modifications of the form $A =T +\beta_1\bw_1\bw_1^T +…

Numerical Analysis · Mathematics 2015-06-30 Do Young Kwak , Jaeyeon Kim

We provide a remarkably simple algorithm to compute all (at most four) common tangents of two disjoint simple polygons. Given each polygon as a read-only array of its corners in cyclic order, the algorithm runs in linear time and constant…

Computational Geometry · Computer Science 2018-12-11 Mikkel Abrahamsen , Bartosz Walczak

We compute the joint distributions of arbitrary numbers of eigenvectors of real and complex symmetric random tensors by the quantum field theoretical methods which were previously used to compute the mean distributions. We obtain the random…

High Energy Physics - Theory · Physics 2026-05-12 Naoki Sasakura

In this paper, we introduce novel fast matrix inversion algorithms that leverage triangular decomposition and recurrent formalism, incorporating Strassen's fast matrix multiplication. Our research places particular emphasis on triangular…

Numerical Analysis · Mathematics 2026-02-05 Mohamed Kamel Riahi

We describe algorithms for computing eigenpairs (eigenvalue--eigenvector) of a complex $n\times n$ matrix $A$. These algorithms are numerically stable, strongly accurate, and theoretically efficient (i.e., polynomial-time). We do not…

Numerical Analysis · Mathematics 2014-10-02 Peter Bürgisser , Felipe Cucker

In this paper we present an efficient algorithm to compute the eigen decomposition of a matrix that is a weighted sum of the self outer products of vectors such as a covariance matrix of data. A well known algorithm to compute the eigen…

Numerical Analysis · Computer Science 2017-06-08 Youhei Akimoto

Eigenvectors of tensors, as studied recently in numerical multilinear algebra, correspond to fixed points of self-maps of a projective space. We determine the number of eigenvectors and eigenvalues of a generic tensor, and we show that the…

Numerical Analysis · Mathematics 2018-06-18 Dustin Cartwright , Bernd Sturmfels

Let $\mathcal{A}=(A_{1},...,A_{n},...)$ be a finite or infinite sequence of $2\times2$ matrices with entries in an integral domain. We show that, except for a very special case, $\mathcal{A}$ is (simultaneously) triangularizable if and only…

Rings and Algebras · Mathematics 2021-10-19 Carlos A. A. Florentino

We present a matrix version of a known method of constructing common eigenvectors of two diagonalizable commuting matrices, thus enabling their simultaneous diagonalization. The matrices may have simple eigenvalues of multiplicity greater…

General Mathematics · Mathematics 2020-07-01 Ronald P. Nordgren

Recently, three numerical methods for the computation of eigenvalues of singular matrix pencils, based on a rank-completing perturbation, a rank-projection, or an augmentation were developed. We show that all three approaches can be…

Numerical Analysis · Mathematics 2025-02-21 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak

The existence and construction of common invariant cones for families of real matrices is considered. The complete results are obtained for 2x2 matrices (with no additional restrictions) and for families of simultaneously diagonalizable…

Rings and Algebras · Mathematics 2009-03-04 Leiba Rodman , Hakan Seyalioglu , Ilya M. Spitkovsky

The history of research on eigenvalue problems is rich with many outstanding contributions. Nonetheless, the rapidly increasing size of data sets requires new algorithms for old problems in the context of extremely large matrix dimensions.…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-17 Hesam T. Dashti , Alireza F. Siahpirani , Liya Wang , Mary Kloc , Amir H. Assadi