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This paper proposes a power method for computing the dominant eigenvalues of a non-Hermitian dual quaternion matrix (DQM). Although the algorithmic framework parallels the Hermitian case, the theoretical analysis is substantially more…

Numerical Analysis · Mathematics 2025-12-02 Hao Yang , Liqun Qi , Chunfeng Cui

This paper investigates the eigenvalue computation problem of the dual quaternion Hermitian matrix closely related to multi-agent group control. Recently, power method was proposed by Cui and Qi in Journal of Scientific Computing, 100…

Numerical Analysis · Mathematics 2025-05-22 Yongjun Chen , Liping Zhang

The power method is a basic method for computing the dominant eigenpair of a matrix. In this paper, we propose a structure-preserving power-like method for computing the dominant conjugate pair of purely imaginary eigenvalues and the…

Numerical Analysis · Mathematics 2024-09-10 Qingqing Zheng

The poses of $m$ robotics in $n$ time points may be represented by an $m \times n$ dual quaternion matrix. In this paper, we study the spectral theory of dual quaternion matrices. We introduce right and left eigenvalues for square dual…

Rings and Algebras · Mathematics 2021-12-01 Liqun Qi , Ziyan Luo

Several common dual quaternion functions, such as the power function, the magnitude function, the $2$-norm function and the $k$th largest eigenvalue of a dual quaternion Hermitian matrix, are standard dual quaternion functions, i.e., the…

Numerical Analysis · Mathematics 2022-08-09 Liqun Qi

We propose a supplement matrix method for computing eigenvalues of a dual Hermitian matrix, and discuss its application in multi-agent formation control. Suppose we have a ring, which can be the real field, the complex field, or the…

Numerical Analysis · Mathematics 2024-05-08 Liqun Qi , Chunfeng Cui

We present a new power method to obtain solutions of eigenvalue problems. The method can determine not only the dominant or lowest eigenvalues but also all eigenvalues without the need for a deflation procedure. The method uses a functional…

Numerical Analysis · Mathematics 2024-10-08 I Wayan Sudiarta , Hadi Susanto

The application of eigenvalue theory to dual quaternion Hermitian matrices holds significance in the realm of multi-agent formation control. In this paper, we study the Rayleigh quotient iteration (RQI) for solving the right eigenpairs of…

Numerical Analysis · Mathematics 2024-09-25 Shan-Qi Duan , Qing-Wen Wang , Xue-Feng Duan

Dual quaternion/complex matrices have important applications in brain science and multi-agent formation control. In this paper, we first study some basic properties of determinants of dual complex matrices, including Sturm theorem and…

Rings and Algebras · Mathematics 2024-05-01 Chen Ling , Liqun Qi

This paper introduces an efficient algorithm for finding the dominant generalized eigenvectors of a pair of symmetric matrices. Combining tools from approximation theory and convex optimization, we develop a simple scalable algorithm with…

Optimization and Control · Mathematics 2019-06-26 Vien V. Mai , Mikael Johansson

Dual quaternions and dual quaternion matrices are widely used in robotics research, particularly in simultaneous localization and mapping (SLAM) problem. Using dual quaternion theory and graph-based methods, SLAM can be reformulated as a…

Numerical Analysis · Mathematics 2025-10-07 Yongjun Chen , Liping Zhang

A majority of numerical scientific computation relies heavily on handling and manipulating matrices, such as solving linear equations, finding eigenvalues and eigenvectors, and so on. Many quantum algorithms have been developed to advance…

Quantum Physics · Physics 2023-11-10 Nhat A. Nghiem , Tzu-Chieh Wei

We propose two different strategies to find eigenvalues and eigenvectors of a given, not necessarily Hermitian, matrix $A$. Our methods apply also to the case of complex eigenvalues, making the strategies interesting for applications to…

Mathematical Physics · Physics 2020-06-24 Fabio Bagarello , Francesco Gargano

In this article, we propose two kinds of neural networks inspired by power method and inverse power method to solve linear eigenvalue problems. These neural networks share similar ideas with traditional methods, in which the differential…

Numerical Analysis · Mathematics 2023-07-18 Qihong Yang , Yangtao Deng , Yu Yang , Qiaolin He , Shiquan Zhang

We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix…

Strongly Correlated Electrons · Physics 2013-10-24 F. R. Petruzielo , A. A. Holmes , Hitesh J. Changlani , M. P. Nightingale , C. J. Umrigar

Many real-world problems rely on finding eigenvalues and eigenvectors of a matrix. The power iteration algorithm is a simple method for determining the largest eigenvalue and associated eigenvector of a general matrix. This algorithm relies…

Numerical Analysis · Mathematics 2021-09-23 Congzhou M Sha , Nikolay V Dokholyan

We explore the block nature of the matrix representation of multiplex networks, introducing a new formalism to deal with its spectral properties as a function of the inter-layer coupling parameter. This approach allows us to derive…

Physics and Society · Physics 2018-07-17 Guilherme Ferraz de Arruda , Emanuele Cozzo , Francisco A. Rodrigues , Yamir Moreno

This paper offers a review of numerical methods for computation of the eigenvalues of Hermitian matrices and the singular values of general and some classes of structured matrices. The focus is on the main principles behind the methods that…

Numerical Analysis · Mathematics 2020-06-05 Zlatko Drmač

In (relativistic) electronic structure methods, the quaternion matrix eigenvalue problem and the linear response (Bethe-Salpeter) eigenvalue problem for excitation energies are two frequently encountered structured eigenvalue problems.…

Chemical Physics · Physics 2021-12-01 Zhendong Li

The power method is one of the most fundamental tools for extracting top principal components from data through low-rank matrix approximation. Yet, when the target rank is large, the cost of matrix multiplication associated with this…

Numerical Analysis · Mathematics 2026-05-12 Shabarish Chenakkod , Michał Dereziński
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