Questions tagged [linear-algebra]

Questions on the algorithmic/computational aspects of linear algebra, including the solution of linear systems, least squares problems, eigenproblems, and other such matters.

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1answer
42 views

How to optimize nuclear norm subject to positive semidefinite constraints?

For finite dimensional symmetric positive semidefinite matrices $A$ and $B$, I would like to solve \begin{align}&\min |X - A|_1 \\ &\text{subject to}\\ &X \preceq B \\ &0 \preceq X\...
7
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5answers
447 views

Checking singularity of a matrix

Suppose that we don't know $n \times n$ matrix $A$ explicitly but we are only able to compute products $Ax$ where $x$ is a column vector with $n$ elements. Is there an algorithm to determine whether $...
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0answers
57 views

Derivative-free ill-conditioned non-linear least squares

I am looking for a package which can solve (non-linear) least squares problems without the use of derivatives (because of an expensive model), but which also deals with ill-conditioning well (such as ...
26
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11answers
8k views

Robust algorithm for $2 \times 2$ SVD

What is a simple algorithm for computing the SVD of $2 \times 2$ matrices? Ideally, I'd like a numerically robust algorithm, but I'll like to see both simple and not-so-simple implementations. C code ...
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3answers
69 views

How to determine global stiffness matrix is constrained or not

Background In solid fem, we often solve $$\mathbf{Ku}=\mathbf{p}$$ where $\mathbf{K}$ is global stiffness matrix, $\mathbf{u}$ is displacement, $\mathbf{p}$ is global load vector. If displacement not ...
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2answers
843 views

Discrete-time Algebraic Riccati Equation (DARE) solver in C++

I need to use a Discrete-time Algebraic Riccati Equation (DARE) solver for an embedded controller (with limited processing power) in a research project and sadly, I can't find any implementation of it ...
1
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1answer
196 views

Method to solve linear, first order ODE of generalized matrix matrix form

The equation and its meaning: Consider two sets $(A)_{l=0,...,m_a},$,$(B)_{l=0,...,m_b}$ of hermitian matrices and a set of positive semidefinite matrices $(C)_{l=0,...,m_c}$. Each matrix has the ...
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0answers
28 views

How to generate a symmetric matrix that will produce a pos-def matrix after application of a pos-def kernel function?

Note in advance that I'm not trying to sample symmetric, positive-definite matrices - that, at least, I know how to do. What I'd like to sample, is symmetric matrices (ideally with diagonal 0, ...
2
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1answer
80 views

Efficient projection of a vector onto matrix kernel

Given an $m \times n$ matrix $A$ and a vector $x\in\mathbb R^n$, with $m<n$, what's an efficient way of computing the projection of $x$ onto the kernel of $A$?
7
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2answers
256 views

Is there an iterative solver for dense matrices with possible zero diagonal entries?

Is there an iterative solver that can handle potentially zero entries on the central diagonal? I am implementing a polynomial fitting algorithm (up to $10^{th}$-order) and my matrix is a "...
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2answers
188 views

Why OpenFOAM uses its own data structures and linear solvers?

I wonder why OpenFOAM code has its own data structures Lists, HashTables, ... etc. when there is the STL in C++? Another ...
2
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1answer
186 views

Solution of the linear system using Sherman-Morrison formula for 1000000x1000000 (7450.6GB) matrix using MATLAB

Let $n = 10^6.$ Let $A \in \mathbb{R}^{n\times n} $ be the lower triangular matrix having 1's on and below the main diagonal. We want to solve the following linear system: $$ (A + uv^T)x = b$$ by the ...
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0answers
81 views

Compute Nullspace of Sparse Matrix

I am computing the nullspace of a sparse rectangular $m$ x $n$ matrix $A$, where $m$ << $n$. I do this by computing the QR decomposition of $A^T$ and extract the $n-m$ right-most columns of the ...
35
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18answers
9k views

Good examples of “two is easy, three is hard” in computational sciences

I recently encountered a formulation of the meta-phenomenon: "two is easy, three is hard" (phrased this way by Federico Poloni), which can be described, as follows: When a certain problem is ...
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0answers
82 views

Is the matrix exponential and the Jordan canonical form actually useful for solving differential equations?

All of my yearlong graduate-level Linear Algebra course notes from my professor—an algebraist/representation theorist—shows his love for the exponential map $e^A$ and the Jordan canonical form—and one ...
3
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0answers
36 views

Numerical calculation of the Berry connection

I'm doing some numerical calculations involving Hermitian matrices, and derivatives of the eigenvectors. Essentially, I have an n x n, Hermitian matrix H(x), which is dependent on some continuous ...
5
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1answer
88 views

Accurately Computing a Positive Vector in the Nullspace of a Matrix

I'm sure this question has been asked before yet after many hours of searching I am unable to find a definitive answer. The problem at hand is solving the linear system: $$A \mathbf{x} = \mathbf{0}$$ ...
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0answers
74 views

A parallelized GMRES solver?

My application calls for solving a dense, 40,000 x 40,000, ill-conditioned linear system. The native SciPy GMRES solver with preconditioning has worked well for my application and solving a single ...
1
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1answer
147 views

Is LAPACK behind the cutting edge of dense linear algebra?

I have been digging into some numerical linear algebra lately, and reading in particular about how LAPACK solves symmetric eigenvalue problems. I noticed that the ...
2
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0answers
65 views

Why is LAPACK (seemingly) suboptimal for packed and banded eigenvalue problems?

Based on this LAPACK routines list, it looks like there is no relatively robust representation (RRR) driver routine for either packed or banded symmetric eigenvalue problems. According to the relevant ...
2
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1answer
72 views

Parallel, matrix-free estimate of the trace

What would be the best way to estimate the trace of a large, distributed matrix, if one only know its action on a vector throug a parallel "matvec" routine? In the application I am interested in, the ...
3
votes
2answers
418 views

Fast and accurate eigenvalue computation for 3x3 posdef matrices

I am looking for a very fast and efficient algorithm for the computation of the eigenvalues of a $3\times 3$ symmetric positive definite matrix. The algorithm will be part of a massive computational ...
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0answers
39 views

Triangle on top of diagonal least squares

I need to solve many least squares problems with the following matrices: $$ \pmatrix{ R \\ D_i } $$ where $R$ is upper triangular and $D_i$ is diagonal. $R$ is the same for all the problems, while $...
2
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1answer
136 views

Boundary conditions in a finite element eigenvalue problem

I've been reading multiple papers and related posts for a while now, but I can't seem to find a specific answer to the issues I'm having so I hope someone can clarify things here. I'll provide some ...
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0answers
40 views

Spurious eigenvalues in a finite element eigenvalue problem

This post is closely related to this one and uses the exact same setup: a mix of quadratic and cubic basis functions in a finite element approach, where variables $u_1$ and $u_2$ are quadratic and $...
3
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1answer
134 views

Implementation of a $O(n \log(n))$ method to compute eigenvalues of real symmetric tridiagonal matrices

I just came upon this paper, which details the implementation of a fast method to get eigenvalues of tridiagonal symmetric matrices : Coakley, Ed S.; Rokhlin, Vladimir, A fast divide-and-conquer ...
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1answer
71 views

Solving triangular matrix equations on a GPU

Suppose I have these two $N\times N$ lower triangular banded matrices: $A = \begin{bmatrix} a_0 & & \\ a_1 & a_0 & \\ a_2 & a_1 & a_0 \\ a_3 & a_2 & a_1 & a_0 \\ &...
0
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1answer
28 views

Norm of operator in finite element discretization of Heat equation

I am solving the heat equation discretized spatially via FEM and temporally via backward Euler. I get the system $$M \dot{u} = K u +f$$ where $u$ is a vector representing the solution at spatial ...
2
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3answers
179 views

Generating Random Orthogonal Matrices in C++

I'm looking for an open-source library for the generation of random n-dimensional orthogonal matrices in C++. In python, it looks like such a function is available in the NumPy package. But I was not ...
1
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0answers
31 views

Choosing the pivot for the rotation matrix in similarity transformation

I have arrived at an equation in the similarity transformation - $M_r$ = $T. M_{r-1}. T^t$ ,where $T$ is the rotation matrix and $M_r$ ,$M_{r-1}$ are similar matrices. My aim is to find the rotation ...
15
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2answers
777 views

Preconditioning a Krylov method with another Krylov method

In methods like gmres or bicgstab it could be attractive to use another Krylov method as a preconditioner. After all they are easy to implement in a matrix-free way and in a parallel environment. For ...
3
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0answers
61 views

Fastest matrix library for Android (with GPU is possible)

I was working on an Android app that requires some linear algebra with matrices. The matrices will be somewhat medium-sized as they are not too small or too big. I was originally using jBlas because ...
2
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0answers
38 views

Is there a published RQ decomposition column-major algorthm?

I am refactoring an existing algorithm where where a RQ decomposition (as opposed to the more common QR) would be rather useful. Most common books on the subject (e.g. Golub and Van Loan) discuss QR ...
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0answers
87 views

Is there a subfield within computational science research that's done on pencil and paper?

Is there an area of computational science research that can be done on pencil and paper (with results written up for a journal format later on)? I'm wondering if there is abstract proof-based linear ...
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1answer
47 views

Find mass matrix in a system of linear equations

Given $z_t=\sum_{i=1}^t \theta_iz_{t-i}+v_t $, where $t=1,...,N$ where $N=1024$. I need to write this in matrix form (a system of linear equations) as $\mathsf{A}\mathsf{z} = \mathsf{z} - \mathsf{v}$. ...
17
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6answers
1k views

How to reorder variables to produce a banded matrix of minimum bandwidth?

I'm trying to solve a 2D Poisson equation by finite differences. In the process, I obtain a sparse matrix with only $5$ variables in each equation. For example, if the variables were $U$, then the ...
1
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1answer
65 views

Flops of the computation of symmetric matrix $A$ to the power of $p$

What is the cost in terms of flops for the computation of $A$ to the power of $p$, where $p$ is a positive integer and $A \in \mathbb R^{n\times n}$ is a symmetric matrix?
12
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3answers
5k views

Testing if a matrix is positive semi-definite

I have a list ${\cal L}$ of symmetric matrices that I need to check for positive semi-definiteness (i.e their eigenvalues are non-negative.) The comment above implies that one could do it by ...
3
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3answers
226 views

Using matrix exponential to solve linear system

Consider the system of linear equations: $$ Ax=b \tag{1} \label{eq1} $$ where $A\in\mathbb F^{n\times n}$, diagonalizable dense matrix, over the field $\mathbb F$ of real or complex numbers, $x\...
3
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1answer
572 views

Efficient ways to numerically evaluate matrix exponentials

What are some computationally efficient ways to solve matrix exponentials, i.e. functions of the form : $f(X)=e^{X}$, where $X$ is a square matrix? So far I have been able to diagonalise some ...
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1answer
58 views

How to solve system of equations with almost-zero determinant?

I have a system of equations that I am trying to solve. In matrix form, it's written as $$x(I - S) = b.$$ I am solving for $x$, where $I$ is the identity matrix and $S$ is a matrix where each column ...
0
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1answer
74 views

Desmos saying there are too many variables [closed]

I wasn't sure if this is a Computational Science SE question or a Stack Overflow question but I think it's more of this one. I wanted to make a graph where I can rotate a hyperbola (not parabola or ...
6
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1answer
536 views

Jacobi preconditioner not reducing condition number?

Let's say you have a general matrix $A$, with diagonal entries $a_{ii} = d>0$. (No assumptions are made about the off-diagonal elements.) Then Jacobi preconditioning doesn't improve condition ...
2
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1answer
114 views

Sparse matrix-matrix multiplication using AVX2

I have two sparse general matrices stored in CSR format I need to multiply. Is there any chance to gain performance using AVX2? In general the matrices are big (hundreds of millions of non-zeros and ...
4
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0answers
132 views

Explanation of subspace strategy regarding CG described in Golub's book

I was wondering about the last paragraph in Matrix Computations (4th edition) by Golub, Chapter 11 (11.3.3), specifically his explanation of subspace strategy for Conjugate Gradient. Note that in ...
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1answer
103 views

How to implement the Hessenberg QR Algorithm?

For context, I'm creating a linear algebra library from scratch for learning purposes in C. Right now I'm working on calculating eigenvalues but my implementation of the QR Algorithm is diverging. ...
9
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1answer
2k views

Increasing computational performance by using 16 bit numbers

I recently found the following article where it was stated that using 16 bit numbers can be used to increase the computational performance of AI applications. According to the article numbers above 16 ...
0
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2answers
75 views

Update for QR factorization least squares

I found after some research that the most numerically stable way to solve the least squares problem is through QR factorization. For $n$ number of observations and $p$ number of parameters it takes ...
3
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2answers
226 views

Cholesky decomposition vs LDL decomposition

In different books and on Wikipedia, you can see mentions of Cholesky decomposition and only sometimes of LDL decomposition. As far as I understand, LDL decomposition can be applied to a broader ...
4
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1answer
209 views

Fast algorithm for computing cofactor matrix

I wonder if there is a fast algorithm, say ($\mathcal O(n^3)$) for computing the cofactor matrix (or conjugate matrix) of an $N\times N$ square matrix. And yes, one could first compute its determinant ...

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