Skip to main content

All Questions

Filter by
Sorted by
Tagged with
22 votes
0 answers
445 views

Why does the random shift in the QR eigenvalue algorithm work in the non-symmetric case over the complex field

I tried to implement the QR algorithm for non-symmetric matrices with complex entries to show to my students. The main part of the implementation was standard: the Householder reduction to the ...
fedja's user avatar
  • 61.9k
0 votes
1 answer
91 views

Matrix quantization and effect on singular values

Let $A$ and $B$ be an $N\times n$ matrix with $n\le N$, and let $\sigma_1(X),\dots \sigma_n(X)$ denote the singular values of $X\in \{A,B\}$. Do we have upper and lower bounds for $$ \| \sigma_i(A)-\...
ABIM's user avatar
  • 5,407
1 vote
0 answers
183 views

Connection of eigenspace of finite Hilbert matrix and its continuous operator counterpart

I am trying to understand the connection between the eigenspace of the continuous operator $$ H(x,y) = \frac{1}{x+y} $$ which is nothing but the square of the Laplace operator, and its discrete ...
knuth's user avatar
  • 33
0 votes
0 answers
99 views

Efficient method to determine minimum eigenvalue of $2 \times 2$ block diagonal matrix

Suppose $H$ is a $2 \times 2$ block-diagonal symmetric matrix in $\mathbb{R}^{2^N \times 2^N} $. That is $$ H = \begin{pmatrix} A_1 & 0 & \cdots & 0\\ 0 & A_2 & \cdots & 0 \\ ...
KAJ226's user avatar
  • 131
1 vote
0 answers
179 views

QR algorithm for eigenvalues and eigenvectors of large symmetric matrices

I am trying to write a QR algorithm in Python for eigenvectors and eigenvalues finding for large symmetric matrices, My initial thought was to use Householder transformation with a Wilkinson shift ...
Daniel Belaish's user avatar
1 vote
0 answers
138 views

Generalized eigenvalues of block matrix

Let $A, D \in \mathbb{R}^{n\times n}$ be symmetric matrices and consider the following matrix pencil $$ \begin{pmatrix} -I & A+\lambda I \\ A+\lambda I & -D \\ \end{pmatrix} $$ If we already ...
bernard's user avatar
  • 205
1 vote
1 answer
331 views

Eigenvalues of a circulant: DFT or Inverse DFT Convention?

Currently, most engineering texts (and webpages including Wikipedia) define forward discrete Fourier transform with a negative sign on the exponential. This is a convention and the inverse discrete ...
ACR's user avatar
  • 879
1 vote
0 answers
137 views

What are the eigenvalues/eigenvectors of the matrix $A=\Big(\frac{1}{\cos(k-l)\frac{\pi}{n}}\Big)_{k,l=1}^{\frac{n-1}{2}}$ when $n$ is odd?

Suppose that $n$ is odd. The eigen values/eigenvectors of the skew-circulant matrix $A=\Big(\frac{1}{\cos(k-l)\frac{\pi}{n}}\Big)_{k,l=1}^n$ are successfully computed in this post. Q. What are ...
ABB's user avatar
  • 4,058
3 votes
1 answer
370 views

The eigenvalues of the matrix $\Big(\frac{1}{\cos(k-l)\frac{\pi}{n}}\Big)_{k,l=1}^n$

What are the eigenvalues/eigenvectors of the matrix $A=\Big(\frac{1}{\cos(k-l)\frac{\pi}{n}}\Big)_{k,l=1}^n$ when $n$ is odd?
ABB's user avatar
  • 4,058
0 votes
0 answers
232 views

How to analyse the range of eigenvalues of a symmetric and indefinite matrix?

Let $G$ be a symmetric and indefinite matrix defined as follows $$ G := S - \begin{pmatrix} I_n & I_n \\ I_n & I_n \end{pmatrix},$$ where $S$ is a symmetric positive definite matrix of size $...
Nxy's user avatar
  • 1
1 vote
0 answers
272 views

Find the eigenvectors from the QR algorithm in the unsymmetric case

It is possible to find many references describing the QR Algorithm with more or less refinements to approximate the eigenvalues of a square matrix $A\in\mathbb{R}^{n\times n}$. I implemented a version ...
L.A. Reba's user avatar
1 vote
1 answer
223 views

Does Wilkinson's shift need to be discontinuous?

Given a symmetric Hessenberg matrix $A = \left[\begin{matrix}\ddots& \vdots & \vdots\\\dotsb & a & b\\\dotsb& b & c\end{matrix}\right]$, the Wilkinson shift $\mu$ employed in ...
wlad's user avatar
  • 4,943
3 votes
1 answer
439 views

Derivative of eigenvalues of a symmetric tridiagonal matrix built via the Lanczos-Arnoldi scheme

Suppose $\mathbf{A}(\mu)$ being a symmetric positive definite matrix of dimension $n$ where its elements depend parametrically on the real parameter $\mu$. Suppose now to build the orthonormal basis ...
wolfram's user avatar
  • 131
0 votes
1 answer
112 views

Is there a specific name for this optimization problem?

Let $A$ be an $n\times n$ symmetric positive definite matrix with eigenvalues and eigenvectors $\lambda_1\ge\lambda_2\ge\cdots\ge\lambda_n>0$ and $v_1,v_2,\cdots,v_n$ respectively. We know that the ...
bernard's user avatar
  • 205
1 vote
1 answer
323 views

How can I find minimum and maximum eigenvalue of non-positive define matrix [closed]

There is a power iteration method, but it only returns the greatest(in absolute value) eigenvalue of matrix. So when we have negative eigenvalues it'll give wrong results. Is there any method, which ...
Dima Shkad's user avatar
2 votes
0 answers
52 views

Large-scale projected minimum-eigenvalue computations

I am interested in efficient numerical procedures for solving large-scale instances of the following projected minimum-eigenvalue problem: $$\mu := \min_{v \in \mbox{ker}(A)} \frac{v^T H v}{\lVert v \...
David Rosen's user avatar
2 votes
1 answer
1k views

Is it faster to compute eigenvalues or coefficients of characteristic polynomials?

Given $A \in \mathsf{M}_n(\mathbb{C})$ (no special structure) is it (generally) faster to compute its eigenvalues or the coefficients of its characteristic polynomial? References/insights would be ...
Pietro Paparella's user avatar
0 votes
2 answers
556 views

Sparse dense matrix versus non-sparse dense matrix in eigenvalue computation

I have a matrix in the form of $2n\times 2n$ block matrix $$ A = \begin{pmatrix}O& W\\ J& D\end{pmatrix} $$ where, $O$ is an $n\times n$ zero-matrix; $W$ is a n-by-n diagonal matrix, $W = ...
Pascal's user avatar
  • 91
2 votes
1 answer
3k views

Eigenvalue and Eigenmatrix of a 3D Tensor - How to calculate it?

How to calculate easily the eigenmatrix of a 3D tensor. I try immersing the tensor in a big matrix, in my case, the tensor is of nxnxn and I can build an n^2 x n^2 matrix that contains all the "...
Alejandro Alvarez-Socorro's user avatar
2 votes
1 answer
3k views

Lanczos algorithm for finding $k$ smallest eigenvector

I am trying (and have been recommended) to use the Lanczos algorithm to find the $k$ smallest eigenvectors. However, all of the literature seems to talk about this algorithm as a way to estimate the $...
toblatp's user avatar
  • 21
0 votes
0 answers
232 views

Smallest eigenvalue of a sparse matrix (updated)

Let $D_{1}$ be $(m-1)n \times mn$ matrix (that is, $(m-1)n$ rows and $mn$ columns) and $D_{2}$ be $m(n-1) \times mn$ defined as $$\begin{cases} D_{1}[(m-1)(j-1)+i ; m(j-1)+i] & = -1 , \\ D_{1}[(m-...
JKay's user avatar
  • 133
7 votes
3 answers
1k views

Checking positive semi-definiteness of integer matrix

Key Problem : Is there any theorem about eigenvalues or positive semi-definiteness of small size matrices with small integer elements? I have to check positive semi-definiteness of many symmetric ...
SIM2's user avatar
  • 73
1 vote
0 answers
19 views

Empirical approaches to validate observational bounds on minimum gap between least eigenvalues of $n \times n$ correlation matrix and its submatrices

Let $\Sigma$ be an $n \times n$ correlation matrix whose least eigenvalue is denoted by $\lambda$. $\Sigma_i'$ be an $(n-1) \times (n-1)$ submatrix of $\Sigma$ obtained by eliminating the $i$-th row ...
Saurabh Agrawal's user avatar
5 votes
1 answer
1k views

In a large sparse matrix, how many eigenvalues/eigenvectors are “spurious”?

In a large (possibly above $5000\times 5000$) matrix, the problem of finding all the eigenvalues and eigenvectors can be solved using iterative methods (Arnoldi, Lanczos etc.). However, there seems to ...
user avatar
7 votes
0 answers
197 views

A special eigenvalue problem

For my research I need to solve a generalised eigenvalue problem $Ax=\lambda B x$, where $A$, $B$ are general matrices, and selectively find only eigen-pairs $\lambda, x$ such that $\lambda\in \mathbb{...
yarchik's user avatar
  • 492
4 votes
0 answers
2k views

What is the time complexity of the largest singular value and its vectors?

Full zero-error SVD on an $m \times n$ matrix $A$ would cost $O(\min(m^2n,mn^2))$. What is the time complexity if we need only the largest singular value and its corresponding vectors? I think it is $...
B. Arsic's user avatar
  • 123
2 votes
1 answer
1k views

How to retrieve eigenvectors from shifted QR algorithm?

I understand that the key to retrieve eigenvectors in the non-shifted QR algorithm is to accumulate the transformations at each steps in the following way: $Q = \Pi_i Q_i$ Can we accumulate the ...
Marc's user avatar
  • 23
15 votes
2 answers
6k views

Linearly constrained eigenvalue problem

Suppose I'd like to: \begin{align} \mathop{\text{min}}_\mathbf{x} && \mathbf{x}^T\mathbf{A}\mathbf{x} \\ \text{subject to:} && \mathbf{x}^T \mathbf{M} \mathbf{x} = 1\\ && \...
Alec Jacobson's user avatar
0 votes
1 answer
769 views

Proving that the eigenvalues of a certain matrix product are positive

Let $A$ be an $m \times n$ matrix, and define: \begin{align*} U &= {\rm diag} \{ \frac{1}{\beta_j} \}, \beta_j = \sum_{k=1}^m |a_{kj}|, j = 1 \dots n \\ V &= {\rm diag} \{ \frac{1}{\alpha_i} \}...
t_h's user avatar
  • 3
1 vote
2 answers
1k views

Eigenvalue computation using inverse iteration

I have a positive definite matrix $A$. I need to compute the max eigen value of $A$ using inverse iteration. The problem is that there are duplicate maximum eigen values and so inverse iteration ...
codepk's user avatar
  • 121
3 votes
0 answers
256 views

What would be a better method for numerical diagonalization of a certain Vandermonde-like matrix?

For the fractional iteration of the $\exp()$-function Hellmuth Kneser had 1942 proposed an analytic solution valid on the real numbers; there is a technical implementation for Pari/GP of this method ...
Gottfried Helms's user avatar
16 votes
2 answers
4k views

The singular values of the Hilbert matrix

The $n\times n$ Hilbert matrix $H$ is defined as follows $$H_{ij} = \frac{1}{i+j-1}, \qquad 1\leq i,j\leq n$$ What is known about the singular values $\sigma_1 \geq \cdots \geq \sigma_n$ of $H$? ...
alext87's user avatar
  • 3,217
5 votes
2 answers
6k views

Computing the largest eigenvalue of a very large sparse matrix

I am trying to compute the asymptotic growth-rate in a specific combinatorial problem depending on a parameter $w$, using the Transfer-Matrix method. This amounts to computing the largest eigenvalue ...
Gadi A's user avatar
  • 233