An eigenvector of an operator is a vector such that the action of the operator is the same as multiplication by a constant, called the eigenvalue. The eigensystem of an operator is the set of all such eigenvectors and their associated eigenvalues.

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How to impose boundary conditions on eigenfunction problems?

I am trying to solve for the eigenfunctions of a (1D) differential operator using finite differences: $$A \, f(x) = \lambda f(x)$$ Here is an example in Python where $A = \partial_x^4$: ...
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52 views

Parallel Monte Carlo simulation using PETSc

I am trying to do Monte Carlo simulation for a large problem which requires eigensolution of a matrix for each sample. The matrix itself is quite large so much so that I want the eigensolution itself ...
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36 views

Computing eigenpairs of singular matrix with ZGEEV?

I've never run into a singular matrix before, so bear with me. I have a complex non-symmetric matrix (about 1000 x 1000) that I know has a couple zero eigenvalues. It isn't guaranteed to be ...
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diagonalization of matrix - omitting small matrix elements

I was wondering whether there is some theorem that allows me to put an upper bound on the error introduced by omitting small matrix elements from a matrix before diagonalization. Let's assume we ...
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1answer
59 views

Numerical eigenbasis for a unitary matrix

Do you know what numerical software computes an eigenvector basis for a unitary matrix? Say I have a unitary matrix $U$. If its eigenvalues are simple (no multiplicities), then for instance Matlab ...
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153 views

calculating eigenvector components of a given vector

I have some vector $V$ which can be decomposed into the eigenspace of the hermitian sparse operator $M$: $V = \sum_i v_i \hat{m}_i$ Is there a way to find the $\hat{m}_i$ (the eigenvector itself) ...
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27 views

roots of polynomials of high degree: LinAlgError: Eigenvalues did not converge

I wrote a simple script to generate random polynoimals $\displaystyle f(z)= \sum_{k=0}^N a_k \frac{z^k}{\sqrt{k!}} $ of high degree and find their roots. For more discussion on random polyomials see ...
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35 views

LAPACK DGGEVX: BALANC option

I'm using DGGEVX routine from LAPACKE with BALANC option as shown below, but to my surprise changing BALANC option from 'N' to ...
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69 views

I am looking for a complex sparse matrix EigenVector solver for GPGPU; preferably CUDA

So far the closest I've found is ViennaCL, which has a Lanczos implementation for Eigenvalues. It is not clear that EigenVectors are produced by this library. Does anyone here know whether ViennaCL ...
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67 views

Eigen vector property: MATLAB 'chol' (LAPACK DSYGV) & MATLAB 'qz' (LAPACK DGGEVX)

Two Eigen algorithms return Eigen vectors with different properties: 1st algorithm, LAPACK DSYGV (the same as MATLAB eig with ...
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2answers
189 views

Eigenvectors: MATLAB vs LAPACK DGGEV or DGGEVX

If we call LAPACK DGGEV or DGGEVX routines for two badly-conditioned matrices in a C++ code, will we get the same eigen-values ...
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1answer
57 views

Fortran 2003 ARPACK wrapper

I wrote a Fortran 2003 wrapper for the ARPACK routine znaupd, basically translating the the example driver routine zndrv1 into modern Fortran 2003 language with automatic arrays. I initialize every ...
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272 views

Most efficient library to diagonalize exactly large hermitian or unitary matrices

I am working on a physics problem which requires obtaining the exact eigenvalues and eigenvectors of Hermitian and Unitary matrices numerically. Naturally I would like to ask the experts what are the ...
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199 views

Comparing Eigenvectors, Mathematica vs. Matlab

I am trying to create the same out puts in Mathmatica and Matlab, however I am running into trouble aligning the eigenvectors with the eigenvalues, I think the Matlab is doing something slighly more ...
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116 views

Sparse smallest eigenvalue problem on a linear subspace?

I am interested in methods for solving the optimization problem $$ \begin{array}{rl} \arg\min_x & x^T A x \\ \mathrm{s.t.} & x^T x = 1 \\ & Bx = 0 \end{array} $$ where $A$ is symmetric ...
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1answer
78 views

Finding Interior eigenvalues using Davidson algorithm

Is it possible to find interior eigenvalues closer to some lambda using Davidson method. I was searching online but found that most people use Jacobi-Davidson method for that. Thanks
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1answer
75 views

Computing eigendecomposition of a Hermitian matrix that is almost unitary

I have a dense Hermitian matrix that is approximately unitary, so it has eigenvalues that are $\sim \pm1$. I would like to compute all the eigenvectors corresponding to the $+1$ eigenvalue (not ...
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3answers
167 views

How to find the smallest positive eigenvalue of a large general system if they are all in +/- pairs of real eigenvalues

I used MKL Lapack SBGVX because it can solve for "selected" eigenvalues/modes (both positive and negative), thinking it would be efficient, but it is extremely slow when compared with Bathe's subspace ...
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52 views

last column of SPD matrix given it's spectral decomposition

I'm working on this application where I get the spectral decomposition (O,D) of a matrix A for free (A is of full rank) but not A itself, and I need to only recover the last column of A. I was ...
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27 views

eigenvalues of graph $\mathbb{Z}_m \times \mathbb{Z}_n$

I am trying to find the eigenvalues of the Laplacian for the product of two cyclic graphs $\mathbb{Z}_L \times \mathbb{Z}_M$. I took a naive approch and coded the matrix by hand: ...
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Dominant contributions of a quadratic form

Let $\Sigma$ be a covariance matrix (e.g. symmetric positive definite). For arbitrary vectors $\epsilon$, I need to compute $\chi^2 \equiv \epsilon^\top\Sigma^{-1}\epsilon$, which I do using a ...
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77 views

Locally conservative method for differential generalized eigenvalue problem

I have to approximate the smallest eigenvalue of the following generalized eigenvalue problem $$ - \nabla \cdot D(x) \nabla p(x) + \alpha(x) p(x) = \lambda \beta(x) p(x) $$ over a domain like ...
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Is there guaranteed global solver for such an eigenvalue problem?

The original nonlinear optimization problem I have is as follows: For constant symmetric matrices $A=A^T, B_i=B_i^T(\forall i\in\mathbb{N}) \in \mathbb{R}^{n\times n}, \text{rank}(A)=n,$ ...
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161 views

Algorithm for directly finding the leading eigenvector of an irreducible matrix

According to the Perron-Frobenius theorem, a real matrix with only positive entries (or one with non-negative entries with a property called irreducibility) will have a unique eigenvector that ...
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Are the eigenvalues of the product matrix of two real symmetric square matrices also real values?

Suppose $A,B \in \mathbb{R}^{n\times n}; A=A^T, B=B^T$, let $C = AB, D =BA$, If we have all the real eigenvalues of $A$ and $B$, e.g. the eigenvalue decomposition of them: $A=P\Lambda_1 P^T$, ...
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Sorting eigenvalues by the dominant contribution

[Edited to simplify the question] I am trying to associate the eigenvalues $E$ of a matrix $H$ to the original rows of the matrix. Moreover, it would be trivial to sort the eigenvalues in ascending ...
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137 views

Algorithm for Eigenvalue Problem of a Real Symmetric nxn Matrix

I have a nxn covariance matrix (so, real, symmetric, dense, nxn... I mean positive semi-definite). 'n' may be very very very big! I'd like to solve partial (3 largest) eigenvalue (+eigenvectors) ...
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209 views

Algorithm for Complete Eigenvalue Problem of a Real Symmetric nxn Matrix

I have a nxn covariance matrix (so, real, symmetric, dense, nxn). 'n' may be very very very big! I'd like to solve complete eigenvalue (+eigenvectors) problem for this matrix. Could somebody tell me ...
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Implementation of Jacobi-Davidson method for cubic eigenvalue problem

I have a large cubic eigenvalue problem: $$\left(\mathbf{A}_0 + \lambda\mathbf{A}_1 + \lambda^2\mathbf{A}_2 + \lambda^3\mathbf{A}_3\right)\mathbf{x} = 0.$$ I could solve this by converting to a ...
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135 views

How to implement the spectral decomposition of a symmetric dense matrix via Eigen C++

Spectral decomposition of symmetric matrix $A_{n\times n}$, specifically, $n=3$ find the orthogonal matrix $Q$ and diagonal matrix $\Lambda$ such that: $A=Q\Lambda Q^T$ How to implement such ...
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About Subspace Iteration for Eigenvalues

I heard that subspace iteration plus Ritz acceleration could improve the performance a lot for solving clustered eigenvalues, for the eigenvalues and eigenvectors could converge linearly with ratio ...
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How to use Lanczos method to compute eigenvalues and eigenvectors

I have a sparse and symmetric matrix A(n x n). The method Lanczos tranforms matrix A into tridiagonal and symmetric matrix T and the Lanczos vectors in matrix V. From there how do I compute k ...
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Solver for eigensystem of vectors?

I'm trying to solve a multipole system. It involves a matrix of 3x3 tensors $A_{ij}$ and a vector of 3-tuples $\mathbf v_i$. $$\left(\begin{matrix} A_{11} & A_{12} & \cdots & A_{1n}\\ ...
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Size reduction of matrices in dispersion curve calculation

I have an energy dispersion curve resulted from eigen values of E(k) = eig(T exp(ik) + T' exp(-ik) + H0). Where H0 and T are NxN square matrices and T' is transpose of T and k is wave-vector. So there ...
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What is the added cost of generalizing an eigensystem?

Problem Let's say I can write a model as the Hermitian eigensystem: $$ A x = \lambda x $$ where $A \in \mathbb{C}^{n\times n}$ is Hermitian, or as the generalized Hermitian eigensystem: $$ \tilde A ...
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Does Lanczos have trouble with large matrix elements?

I have a large, yet very sparse, matrix that I'd like to diagonalize. Both my own Lanczos implementation and the ARPACK that's built in with scipy fail to converge properly, though. I know that my ...
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228 views

how to use lanczos code from netlib for large sparse symmetric matrix?

I want to use lanczos method to calculate the few lowest eigenvalue and eigen-vector of a large sparse symmetric matrix(~50k x ~50k). In http://www.netlib.org/lanczos/index.html I found the codes ...
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Preconditioner for finding the smallest eigenpairs of a large, but structured, matrix

I'm trying to find the eigenvector corresponding to the second smallest eigenvalue of a large $(4,000,000 \times 4,000,000)$ matrix $L$. $L$ is a graph Laplacian, with the following structure: $L = D ...
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Preconditioner for large size hermitian eigenvalue problems

Basically I try to compute several smallest eigenvalues of some sparse 50k*50k eigenvalue problems using matlab. $$Ax = \lambda Bx$$ With matlab eigs, it's not as fast as I expected. So I tried some ...
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Continuity of eigenvectors of parametric matrix

I have $n$-dimensional matrices $\mathrm{\hat{H}}(\vec{k})$ depending on vector parameter $\vec{k}$. Now, eigenvalue routines return eigenvalues in no particular order (they are usually sorted), but ...
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how can I numerically calculate all eigenvectors of a $n \times n$ complex tridiagonal matrix?

I have tried matlab eig command, it results true eigenvalues but wrong eigenvectors. I also tried direct iteration with rayleigh qotient which is better but doesn't give all eigenvectors also I have ...
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336 views

Solving a large non-hermitian generalised eigenvalue problem from a linear stability analysis using SLEPc

I have a generalised matrix problem: $A x = \lambda B x$ from a spectral method on a linear stability analysis problem. My matrix B is diagonal and positive semi-definite. A is non-hermitian and ...
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239 views

find a set of linearly independent columns in a $m\times n$ matrix

my question is between mathematics, physics and informatics. Suppose i have an Hamiltonian (hermitian matrix) that i can diagonalize. The matrix that allows this transformation is a unitary matrix ...
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Algorithm for Principal Eigenvector of a Real Symmetric 3x3 Matrix

I have a 3x3 covariance matrix (so, real, symmetric, dense, 3x3), I would like it's principal eigenvector, and speed is a concern. Is there a fast algorithm for this specific problem? I've seen ...
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What is the fastest way to compute all eigenvalues of a very big and sparse adjacency matrix in python?

I'm trying to figure out if there is a faster way to compute all the eigenvalues and eigenvectors of a very big and sparse adjacency matrix than using scipy.sparse.linalg.eigsh As far as I know, this ...
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617 views

generalized eigenvalue problem

I need to solve a real generalized eigenvalue problem $Ax= \lambda Bx(*)$ A and B are calculated from equations below: $$A=\sum_{i,j=1}^{N}W_{ij}(K_{i}-K_{j})\beta\beta^{T}(K_{i}-K_{j})^{T}$$ ...
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Ground state eigenvector different for different eigen solvers (differs by negative sign in the elements). Does it matter?

Here is some code that hopefully clearly illustrates what I'm doing: ...
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509 views

computing the determinant of a dense nonsymmetric 100x100 matrix having very big and very small eigenvalues

The motivation for my question is the following: in one of Project Euler questions there is a need to count the spanning trees of a rectangular grid graph of dimension 100x500. By the Matrix-Tree ...
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Specialized methods for symmetric tridiagonal generalized eigenvalue problems

I have to solve generalized eigenvalue problems $Ax = \lambda Bx$ where $A$ and $B$ are both tridiagonal, $B$ is symmetric positive definite and real, but $A$ is only complex symmetric (not definite ...
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1answer
169 views

Numerical Methods for minimizing a Non-Differentiable Convex Function of Several Variables

I have a multi-variable convex continuous function which is not differentiable. I am interested to know about different numerical techniques, possibly also references to them, used for this. Read ...