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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72 views

Regularisation of ill-conditioned matrix-vector problem

I have a linear* problem which arises from an integro-differential system, and writes: $$ (\mathbf{I}+\lambda \mathbf{A})x = b $$ where $\mathbf{A}$ is a real full matrix, size $n\times n$, but is not ...
3
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0answers
84 views

PETSc-like library for Julia

I want to build an application for Material Point Method (and probably other meshfree methods too) in Julia and I am looking for library for direct and iterative solvers that can help me with it. One ...
5
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2answers
465 views

Computational method to compute both the (log) determinant and inverse of a matrix

Suppose I have a square matrix $\mathbf{A} \in \mathbb{R}^{n\times n}$ and a vector $\mathbf{b}\in\mathbb{R}^n$. In my application I need to accomplish two things. I need to find the solution of the ...
4
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1answer
102 views

Solving for a single element of a solution of a linear system

I wish to solve a linear system $A x =b$ in which $A$ is dense but not too large, say no larger than $10\times10$. However, I am not interested in the full solution vector $x = [x_0, x_1, \dots]$, ...
2
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0answers
58 views

Multigrid method: linear solver and modified residual

I am trying to better understand the FAS multigrid algorithm for Euler equation in FV discretization. The usage of the modified residual (the residual with forcing) inside the different cases: ...
3
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1answer
74 views

Find $x$ that satisfy $(I-A^*A)+x(\frac{A+A^*}{2})\prec0$ using LMI or SDP on Matlab

Given $A\in\mathbb{C}^{n\times n}$, I want to use LMI or SDP to find feasibility of $x>0$ in the following inequality: $$(I-A^*A)+x(\frac{A+A^*}{2})\prec0,$$ where $D\prec0$ means that $D$ is ...
3
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0answers
84 views

Stable iterative solver for complex symmetric linear systems

I am interested in the iterative solution (preferably Krylov-type solvers) of a problem Ax=b, with x, b ∈ ℂn x 1 and A ∈ ℂn x n. A is symmetric, invertible, and its real and imaginary parts are ...
0
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2answers
118 views

Implementation of $[X, \cdot]$ as an $n^2 \times n^2$ matrix, where $X$ is an $n \times n$ matrix

Let $M_n(\mathbb{R})$ denote the set of $n\times n$ matrices with real entries. I have an $n\times n$ matrix $X\in M_n(\mathbb{R})$, and I would like to implement the linear operator $[X, \cdot] : M_n(...
5
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2answers
103 views

Optimizing a quadratic form integral over unit sphere

I have an optimization problem, which is to maximize the following integral over the unit sphere: $$ \max_B \int d\Omega \mathbf{f}^{\dagger}(\theta,\phi) (B^{\dagger} + B) \mathbf{f}(\theta,\phi) $$ ...
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0answers
58 views

Comparing minimas of two different functions

The goal is to find vectors $x_u$ and $y_i$, both of the same length $f=64$, and to do this the following loss function is minimized: $$\sum_{u, i} (1 + \alpha \cdot r_{ui})(p_{ui} - x_{u}^{T}y_i)^2$$ ...
6
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1answer
192 views

Algorithm for solving systems which are nearly symmetric/adjoint?

I am familiar with Cholesky decomposition and LU factorization for solving systems of linear equations. I have a problem where I have large sparse matrices (say, 1000x1000 or larger) where only one or ...
18
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4answers
2k views

Why do we usually not want the eigenvalues of non-symmetric matrices?

I came across this line in a class note I am reading where it discusses finding eigenvalues of matrices. In reality we don't go all the way with Arnoldi. We stop at a decent value of 𝑘. Then the 𝑘 ...
5
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1answer
132 views

Solving absolute value systems

Let $z, b \in \mathbb R^n$, $A \in M_n (\mathbb R)$ and $|z| := (|z_1|, \dots, |z_n|)$. I am searching for an efficient algorithm to solve the absolute value system: \begin{equation} z - A |z| = b. \...
1
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1answer
70 views

Efficiency of scipy.sparse.linalg.expm_multiply with sparse vs unsparse vectors

From the package scipy.sparse.linalg in Python, calling expm_multiply(X, v) allows you to compute the vector ...
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0answers
83 views

Matlab - Equality between 2 Fisher matrices constructed in a different way

I want to know if, on a Fisher matrix, the projection operation (with a Jacobian matrix) commutes with a matricial inversion operation. The 2 ways to build these 2 matrices are: 1) First method: 1.1) ...
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50 views

PLASMA usage (Linear algebra routines that supports multithreading)

I have been looking for linear algebra libraries that support multithreading. I have found PLASMA which looks promising. It is from the same group that developed LAPACK. http://icl.cs.utk.edu/...
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135 views

Do the projection (with Jacobian) and marginalisation (inversion of matrix and remove a row/column and reinversion) commute?

I try to check the equality or the inequality between 2 Fisher matrices. The goal is too see if the projection (with Jacobian) and marginalisation (inversion of matrix and remove a row/column and ...
3
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1answer
117 views

How can I extract the banded or block diagonal part of a sparse matrix in MATLAB?

Given a large sparse (square) matrix in MATLAB, how can I extract the banded or the block-diagonal parts (of fixed size) of it efficiently? These are useful operations when prototyping and testing ...
0
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1answer
47 views

Efficient solution to linear system involving Kronecker sum in MATLAB

High dimensional finite difference problems often lead to linear systems of the form $$ A x = b, \qquad A = B_1 \oplus B_2 \oplus \cdots \oplus B_d, $$ where $\oplus$ denotes the Kronecker sum. $B_i \...
4
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0answers
79 views

Unstable Algorithms which become stable when hardware provides Kulisch exact dot product instruction

In John Gustaffson's book The End of Error, he discusses Ulrich Kulisch's exact dot product, which (in double precision) requires a 2100 bit fixed point register which rounds only once after the ...
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0answers
53 views

Number of words that a processor can handle for PMMM

The PMMM which stands for parallel matrix-matrix multiplication essentially accelerates the algorithm of the matrix-matrix multiplication of two matrices $A$ and $B$ both of size $n$ so that $C:= AB$. ...
3
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0answers
85 views

Jacobian Matrix of 2D element mapped to 3D

Note: I previously posted this question to MathStackExchange, but got no attention there. So I'm rewritting and trying over here. Problem summary Given a common¹ set of shape functions defined at ...
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0answers
75 views

Solution of an underdetermined system stemming from a PDE with Neumann BC

Consider the Poisson's equation in 1D with homogeneous b.c.'s $\mathrm{d} \phi/\mathrm{d} x=0$ with the seven point Laplacian (1 -54 783 -1460 783 -54 1 / 576 on a uniform grid). The resulting system ...
2
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4answers
163 views

Eigenvalue decomposition for a very huge matrix of medical images (such as the pixel physical coordinates of CT images)

I am trying to do eigenvalue decomposition for a huge matrix larger than 788000×788000 for medical image analysis. The matrix is not sparse and every element in the matrix has a real value. And, for ...
4
votes
1answer
112 views

Solving geodesics on triangular meshes gives negative distances

I have implemented the heat method for geodesics: https://www.cs.cmu.edu/~kmcrane/Projects/HeatMethod/paperCACM.pdf When I run it I am getting a solution that, visually, seems correct: In this image, ...
3
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0answers
64 views

Check if LinearOperator is symmetric

I have a scipy.sparse.linalg.LinearOperator object. I'd like to check if its associated matrix is symmetric without actually instantiating the matrix in the most ...
3
votes
1answer
105 views

Lanczos algorithm for finding top eigenvalues of a matrix sum

I am trying to find the top k leading eigenvalues of a NumPy matrix (using python dot product notation) L@L + a*X@X.T, where $L$ ...
0
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0answers
148 views

Numerical Range of a matrix in Python

In the mathematical field of linear algebra and convex analysis, the numerical range or field of values of a complex $n\times n$ matrix $A$ is the set $$W(A)=\left\{{\frac {{\mathbf {x}}^{*}A{\...
2
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3answers
160 views

Linear solver recommendation(s) for small problems

I am interested in solving many linear systems $Ax = b$, where $A$ is symmetric positive definite and small (i.e. less than 25,000 rows) --- $b$ will be changing. We can assume that $A$ arises from ...
2
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0answers
59 views

Software for solving large systems of linear equations over gf(2)

What available solvers are there for linear equation solver over GF(2) (Boolean), capable of dealing with large sparse systems (in the 10k - 100k variables range)?
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1answer
34 views

Interpretation of error between Hessian approximation and real Hessian - Quasi-Newton Method

$$ ||I- H_{k}^{BFGS}\nabla^{2}f(x_{k})||_{2}$$ , where $H_{k}$ is the inverse of hessian approximation at each iteration. I am given this expression to assess the error in Hessian approximation in ...
-2
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1answer
76 views

Forward Euler Adaptive Step Size Stability

Given with a generalization using adaptive times-stepping as then is it still reasonable to assume that to ensure stability of the Euler’s forward method we need the growth factor for all n to be ...
8
votes
3answers
579 views

Accurate Way to Calculate Matrix Powers and Matrix Exponential for Sparse Positive Semidefinite Matrices

I do need to numerically calculate the following forms for any $x\in\mathbb{R}^n$, possibly in python: $x^T M^k x$, where $M\in\mathbb{R^{n\times n}}$ is a PSD sparse matrix, $n$ can be quite large ...
2
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0answers
43 views

How to solve this boundary value problem which has more unknown than equation on MATLAB

I need your helps about solving the problem below with MATLAB. I am trying to solve 2D Stress Wave Propagation problem by using FDTD(Finite difference time domain) method on the cylindrical coord. I ...
1
vote
2answers
159 views

Diagonalization using LAPACK

Say, we have a Hamiltonian which for simplicity does not mix particle hole sectors. It is just a simple Hamiltonian in real space as shown, $H=\sum_{ij,\sigma} A(i,j)(c_{i\sigma}^{\dagger}c_{j\sigma} +...
0
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2answers
127 views

Given a symmetric matrix, is it ok to apply Cholesky decomposition to see if it has negative eigenvalues?

I intend to check the diagonal of L, where A = L'L, for negative elements. However, I don't know if Cholesky is meaningful in theoretical / computational sense if there are some negative eigenvalues.
0
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1answer
70 views

Solve for large array of PD matrices

I have N matrices that are positive definite, and I have to solve for a M vectors. As M is large in my case, doing all solves simultaneously using np.linalg.solve ...
1
vote
1answer
64 views

Algebraic multigrid as solver and as preconditioner

My question is around the efficiency of AMG. In which case AMG can perform better,as solver or as a preconditioner(for example a Krylov space method as CG)? Assume the case of elliptic pdes.
2
votes
1answer
124 views

Efficiently compute a projection matrix from Householders reflectors

Let $A \in \mathbb{R}^{m \times n}$ where $m \geq n$. Let $B$ and $\tau$ be the result of applying LAPACK's dgeqrfp method (R on the upper right triangle, and the ...
3
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1answer
133 views

A notion of resolution in inverse problems

Suppose I have a linear inverse problem of the form: \begin{align} Ax=b \end{align} I would like to reconstruct $x$ from the measurement $b$ via the objective $$\min_x\{\vert\vert Ax-b\vert\vert^2_2+\...
1
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0answers
74 views

Upper bound on condition number in linear preconditioning

I'm studying iterative methods for solving linear system, and I find the following setting in Wikipedia: Consider a matrix splitting $A = M-N$, where $A,M,N$ are all symmetric and positive definite ...
6
votes
1answer
257 views

Efficiently computing $e^{tX}$ for many different values of $t$

Given an anti-Hermitian and sparse matrix $X$, I am using Python (NumPy and SciPy) to compute the matrix exponential $f(t) := e^{tX}$ for many values of $t$. The method I am currently using is to ...
2
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1answer
131 views

Numerical Linear Algebra: When to use Direct methods versus iterative methods to solve a linear system - for PDEs in particular

I am reading the Chapra and Canale book on numerical methods, and was working through the chapters on solving linear systems. Now the book goes through direct methods including Gaussian Elimination, ...
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0answers
65 views

Given an unpivoted form of Aasen's algorithm, how does one add pivoting?

I've implemented the version of Aasen's algorithm described in the book Matrix Computations 4th Edition. The version there doesn't have pivoting. The book's description of how to add pivoting is a bit ...
2
votes
1answer
58 views

How do I extract the output of Aasen's algorithm into a usable form?

I tried implementing the algorithm in Aasen's 1971 paper on factorizing symmetric indefinite matrices. I've translated the code verbatim from Algol into Python, and I used the test example given in ...
1
vote
1answer
117 views

Complexity of solving an image differential linear system

Define an "image differential linear system" as a linear system $A\mathbf{x}=\mathbf{b}$ wherein $\mathbf{x}$ contains the ($\mathbb{R}$) pixels of an image and each row of $A$ constrains ...
6
votes
1answer
283 views

Parallelize Scipy iterative methods for linear equation systems(bicgstab) in Python

I need to solve linear equations system Ax = b, where A is a sparse CSR matrix with size 500 000 x 500 000. I'am using scipy.bicgstab and it takes almost 10min to solve this system on my PC and I need ...
6
votes
1answer
199 views

Symmetric matrix which satisfies conditions of the form $v_i^T X v_i = 0$

I want to solve an underdetermined system of linear equations $A x = b$ with $A \in \mathbb{R}^{n \times r^2}, x \in \mathbb{R}^{r^2}, b \in \mathbb{R}^n$. The matrix $A$ has the following additional ...
0
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0answers
76 views

How to make a directed graph symmetric?

Say I have a directed graph given as an adjacency matrix $A$ in CSR format represented by the arrays ia (row indexes) and ja (...
3
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2answers
110 views

Equations that are easier to verify than to solve?

Are there interesting examples of (systems) of equations where it is known to be harder to find a solution (in terms of scaling with respect to problem size) than verifying a provided solution for ...

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