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Questions about Mathematica functionality related to manipulating vector spaces and linear mappings between such spaces. This includes determination of matrix properties, matrix transformations, decompositions, and factoring.
1
vote
Ouput the result of Eigenvector to variables
{v1,v2}=Eigenvectors[A]
should work
12
votes
Accepted
Inconsistent results from Wolfram Cloud
I get the same result in Mathematica, so it's not a Mathematica Online issue. I don't think it's even a Mathematica issue. It's due to two factors:
w1 is not equal to w2, because N doesn't actuall …
6
votes
Compute the stationary distribution of a large transition matrix
edit: it's even simpler since this is a discrete-time Markov chain
I didn't know Roman's trick with SparseArray. Here's another trick: use Method->"Arnoldi", asking for only the eigenvector correspon …
5
votes
2
answers
1k
views
LinearSolve on a singular matrix
I have some singular transition rate matrices $m$ (columns add to zero). They have exactly one zero eigenvalue that I want to find the corresponding eigenvector of (the rest of the eigenvalues are ne …
6
votes
Calculating the equilibrium value of a discrete time system in matrix form?
Such a system for arbitrary $A$ has only the trivial equilibrium $x=0$. In this case you're lucky that the dominant eigenvalue of $A$ is 1. In this case, the equilibrium is proportional to the corre …
5
votes
Accepted
Identifying points in the frontier of a set
If I understand your problem correctly, I think you can derive the envelope using calculus. Basically you have a function n (your needs) of two variables q1 and q2 (q3 == 1 - q1 - q2 since you write …
10
votes
Tracking Eigenvalues Through a Crossing
Here's a CharacteristicPolynomial-free approach based on the formula for eigenvalue sensitivity ${d\lambda \over dB}={\vec u {dH \over dB} \vec v \over <\vec u,\vec v>}$ where $\vec v$ is the correspo …
8
votes
Tracking Eigenvalues Through a Crossing
Here's another CharacteristicPolynomial-free approach, this one using Eigenvalues[Method -> "Arnoldi"] to find a single eigenvalue, then tracking it over parameter values using linear extrapolation (o …
1
vote
Accepted
Find the parameter values for my matrix for it to have imaginary eigenvalues
Based on @george2079's suggestion, let's start by plotting the maximum real eigenvalue:
a = {{1, u^3 + 2, 1}, {0, 1, u}, {1/u^2, 0, 1}};
maxev[v_?NumericQ] := Max[Re[Eigenvalues[a /. u -> v]]]
Plot[m …
5
votes
Accepted
I want to improve my algorithm of knowing eigenvalues of the matrix H(k)
The biggest speed-up comes from constructing H only once, not every time in the main loop. I also avoided the For loop in saving your results, which repeatedly called Eigenvalues.
n = 100;
M = 0.4;
…