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Questions tagged [matrix]

Matrix is a rectangular array of elements (e.q. numbers, symbols, or expressions), arranged in columns and rows.

3
votes
2answers
122 views

Time-stable SO(n) matrix synthesis algorithm

Consider an equation $S(t)b(t) = a$, where $a, b(t) \in S^{n-1}$ are given and the vector $b(t)$ is continuous, i.e. its endpoint traces a continuous curve on the unit sphere. The task is to find ...
3
votes
1answer
821 views

Spectral decomposition with eigenvalue shift

Suppose a square, real and symmetric matrix $G\in\mathbb{R}^{n\times n}$ is given, and it is known to have one zero eigenvalue associated with all ones eigenvector, $1_n$. I'm aware that the (possibly)...
12
votes
3answers
2k views

What's the current state of the art regarding algorithms for the singular value decomposition?

I'm working on a header-only matrix library to provide some reasonable degree of linear algebra capability in as simple a package as possible, and I'm trying to survey what the current state of the ...
11
votes
1answer
2k views

weighted SVD problem?

Given two matrices $A$ and $B$, I'd like to find vectors $x$ and $y$, such that, $$ \min \sum_{ij} (A_{ij} - x_i y_j B_{ij})^2. $$ In matrix form, I'm trying to minimize the Frobenius norm of $A - \...
4
votes
2answers
4k views

Is there an MPI All Gather operation for matrices?

I have a distributed matrix, in block column format. I know that I can reshape the matrix into one long vector and use an all_gatherv operation. I just wanted to avoid the trouble of having to ...
9
votes
2answers
1k views

Safe application of iterative methods on diagonally dominant matrices

Suppose the following linear system is given $$Lx=c,\tag1$$ where $L$ is the weighted Laplacian known to be positive $semi-$definite with a one dimensional null space spanned by $1_n=(1,\dots,1)\in\...
4
votes
4answers
215 views

Determining the algorithmic complexity

A few of the iterative matrix algorithms (CG,GMRES etc.) I have authored are acting rather funny. They converge to the right answers but take abnormally long time to run. I am in the process of ...
7
votes
1answer
553 views

Jacobi iteration to reduce the quadratic function

Given certain function $f(X)$ which is quadratic in $X\in\mathbb{R}^{n\times d}$, $$\frac{1}{2}tr(X^TAX) - tr(Y^TBX)$$ for positive definite weighted Laplacian matrices $A, B\in\mathbb{R}^{n\times n}...
4
votes
3answers
217 views

Efficiently computing a few localized eigenvectors

Let $H = \triangle + V(x) : \mathbb{R}^2 \rightarrow \mathbb{R}^2$. I am interested in domain decomposition for an eigenproblem involving $H$. The lowest 1000 eigenfunctions of $H$, $ \psi_i $, can ...
2
votes
2answers
517 views

Unimodular Matrix calculation

I know for a given matrix $M$, there exists a matrix $U$ over the integers with determinant $+1$ or $-1$ such that $UM=E$. I know $E$, but $M$ is not a square matrix. Is there any easy way to get $...
4
votes
2answers
271 views

Is it possible to prove that the off-diagonal blocks of the Cauchy matrix have numerical rank $O(\log n)$?

Suppose we have a $n\times n$ Cauchy matrix of which the $ij$-th entry is given by: $$ A_{ij} = \frac{1}{a_i - b_j} $$ the assumption is that the distance between $\{a_i\}$ and $\{b_j\}$ is greater ...
7
votes
1answer
821 views

Sparse hermitian eigensystems: are there better techniques than Arpack or TRLan?

As a part of other work I need to solve relatively large (~1E5x1E5) and sparse (~100 non-zero elements in each raw in few blocks) hermitian eigensystems. Usually only few eigenvalues+vectors are ...
3
votes
1answer
807 views

Is a checkerboard block decomposition of a matrix useful when solving a linear system with a parallel conjugate gradient method?

According to these lecture notes, a checkerboard block decomposition should exhibit better scalability when applied to parallel matrix-vector multiplication (presumably because of greater cache hit ...
6
votes
2answers
312 views

What guidelines should I use when choosing a scalable linear solver?

There are many different linear solvers, some which work best for diagonally dominant matrices, some for symmetric, some for positive definite ones, some for banded matrices, etc... There are direct ...
4
votes
0answers
134 views

Probabilistic algorithms for matrix approximation

Considering regular matrix approximation inequality || $A - QQ^TA $|| < e where we try to approximate matrix $A$ by a lower rank orthonormal matrix $Q$. I've read an article on probabilistic ...
15
votes
2answers
958 views

Estimation of condition numbers for very large matrices

Which approaches are used in practice for estimating the condition number of large sparse matrices?
34
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6answers
2k views

Symbolic software packages for Matrix expressions?

We know that $\mathbf A$ is symmetric and positive-definite. We know that $\mathbf B$ is orthogonal: Question: is $\mathbf B \cdot\mathbf A \cdot\mathbf B^\top$ symmetric and positive-definite? ...