How do I find the change of basis matrix for the JCF of M?

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SUMMARY

The discussion focuses on finding the change of basis matrix for the Jordan Canonical Form (JCF) of the matrix M = \(\begin{pmatrix} 2 & -3 & 0 \\ 3 & -4 & 0 \\ -2 & 2 & 1 \end{pmatrix}\). The characteristic polynomial is identified as \(\chi(\lambda) = (\lambda + 1)^3\), leading to the conclusion that the JCF is \(J_M = \begin{pmatrix} -1 & 1 & 0 \\ 0 & -1 & 0 \\ 0 & 0 & -1 \end{pmatrix}\). The transition matrix can be computed using generalized eigenvectors, which are derived from the nullspace of \(M + I\) and its powers. The discussion emphasizes the importance of understanding eigenvectors and generalized eigenvectors for larger matrices.

PREREQUISITES
  • Understanding of Jordan Canonical Form (JCF)
  • Knowledge of characteristic polynomials
  • Familiarity with eigenvectors and generalized eigenvectors
  • Ability to perform row reduction to RREF
NEXT STEPS
  • Study the computation of Jordan Canonical Form for matrices with multiple eigenvalues
  • Learn about the process of finding generalized eigenvectors
  • Explore the implications of the rank-nullity theorem in relation to eigenspaces
  • Practice solving for transition matrices in various linear transformations
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Mathematicians, graduate students in linear algebra, and anyone involved in advanced matrix theory or applications requiring the computation of Jordan forms and transition matrices.

TMO
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Let

## \begin{align}M =\begin{pmatrix} 2& -3& 0 \\ 3& -4& 0 \\ -2& 2& 1 \end{pmatrix} \end{align}. ##

Here is how I think the JCF is found.

STEP 1: Find the characteristic polynomial

It's ## \chi(\lambda) = (\lambda + 1)^3 ##

STEP 2: Make an AMGM table and write an integer partition equation

The AM is given by looking at the power. The GM is found by finding the nullspace for each eigenvalue. For this matrix this is the table:

Code:
+-----+------+------+
|  λ  |  AM  |  GM  |
+-----+------+------+
| -1  |  3   |  2   |
+-----+------+------+

which gives the integer partition equation ## J_{1, \lambda_{-1}} + J_{2, \lambda_{-1}} = 3 ##. Because there's only one integer partition possible (up to permutation: remember that the JCF is unique only up to permutation not in general), we can guess the JCF is

## \begin{align}J_M =\begin{pmatrix} -1& 1& 0 \\ 0& -1& 0 \\ 0& 0& -1 \end{pmatrix} \end{align}. ##

But I don't know how to compute the transition matrix. I know it involves generalized eigenvectors. Can someone help me?
 
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You could solve for ##SJ_M=MS## or transform it from step to step.
 
fresh_42 said:
You could solve for ##SJ_M=MS## or transform it from step to step.

I need to find the change of basis matrix using eigenvectors and generalized eigenvectors. Why? Because for larger matrices I may not be able to get a nice number partition that allows me to guess the JCF. I know there's a way to do this. How do I do this?
 
O.k., another method is to calculate ##M.v=-v## which should give a decomposition ##\mathbb{R}^3= \mathbb{E}_{-1}^{(1)} \oplus \mathbb{E}_{-1}^{(2)}## with a one dimensional eigenspace ##\mathbb{E}_{-1}^{(1)}## and a two dimensional generalized eigenspace ##\mathbb{E}_{-1}^{(2)}=\{\,v\in \mathbb{R}^3\,|\,(M+I)^2.v=0\,\}##
 
Taking ## (M + I) = 0 ## and transforming it into RREF gives

##\begin{align}\begin{pmatrix} 1& -1& 0 \\ 0& 0& 0 \\ 0& 0& 0 \end{pmatrix} \end{align}##.

The non-pivot columns are two, so the eigenspace is given by

##\begin{align} v_1 - v_2 =& 0& \\ v_2 =& r \\ v_3 =& s \end{align}##

Rewriting this in terms of linear span gives

## \begin{align}\left\{\begin{pmatrix} 1 \\ 1 \\ 0\end{pmatrix}, \begin{pmatrix} 0 \\ 0 \\ 1\end{pmatrix}\right\}\end{align} ##.

Is this the eigenspace ## \mathbb{E}_{-1}^2 ##?
 
I haven't done your homework, but it is easy to check that ##(1,1,0)^\tau## is an eigenvector to ##-1## and ##(0,0,1)^\tau## an eigenvector to ##1##, which contradicts your characteristic polynomial. I also think that ##J_M=\operatorname{diag}(-1,-1,1)##.
 
TMO said:
Taking ## (M + I) = 0 ## and transforming it into RREF gives

##\begin{align}\begin{pmatrix} 1& -1& 0 \\ 0& 0& 0 \\ 0& 0& 0 \end{pmatrix} \end{align}##.
I got a 1 in the third column of the second row after row reduction.

I also got 1 and -1 as the eigenvalues, and you get only one eigenvector for ##\lambda = -1##.

TMO said:
But I don't know how to compute the transition matrix. I know it involves generalized eigenvectors. Can someone help me?
You just form a matrix where the columns are the generalized eigenvectors.
 

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