Jordan Normal Form: Find Basis B in $\mathbb{Z}_{5}^{3}$

In summary, you found out that the characteristic polynomial of f is -(\lambda-2)^{3} and that there are two linearly indenpendent vectors corresponding to \lambda =2. You also found a basis B of \mathbb{Z}_{5}^{3} such that [f]_{B}^{B}=\begin{pmatrix}2 & 1 & 0\\}\,\,\,\,0 & 2 & 0\\}\,\,\,\,0 & 0 & 2.
  • #1
Mihulik
8
0
Hi

Homework Statement


Let [itex]f:\:\mathbb{Z}_{5}^{3}\rightarrow \mathbb{Z}_{5}^{3}[/itex] be a linear operator and let [itex][f]_{e_{3}}^{e_{3}}=A=\begin{pmatrix}3 & 1 & 4\\
3 & 0 & 2\\
4 & 4 & 3
\end{pmatrix}[/itex] over [itex]\mathbb{Z}_{5}[/itex].
Find a basis B of [itex]\mathbb{Z}_{5}^{3}[/itex] such that [itex][f]_{B}^{B}=\begin{pmatrix}2 & 1 & 0\\
0 & 2 & 0\\
0 & 0 & 2
\end{pmatrix}[/itex].

The Attempt at a Solution


I found out that the characteristic polynomial of [itex]f[/itex] is [itex]-(\lambda-2)^{3}[/itex] and that there are two linearly indenpendent vectors corresponding to [itex]\lambda =2[/itex].
These vectors are [itex]v_{1}=\begin{pmatrix}1\\
0\\
1
\end{pmatrix}[/itex] and [itex]v_{3}=\begin{pmatrix}4\\
1\\
0
\end{pmatrix}[/itex].

Now, let [itex]B=\left(v_{1},\: v_{2},\: v_{3}\right)[/itex].
We have [itex]f(v_{1})=2\cdot v_{1}[/itex] and [itex]f(v_{3})=2\cdot v_{3}[/itex] as desired.
We want [itex]v_{2}[/itex] to satisfy the equation [itex]Av_{2}=f(v_{2})=v_{1}+2v_{2}[/itex], which we can rewrite as [itex](A-2I_{3})v_{2}=v_{1}[/itex].
However, this is the point I got stuck on.
This equation doesn't have a solution... Why?
I was hopping somebody could tell me what I was doing wrong because I've spent a few hours trying to figure out what's wrong...

Thank you!
 
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  • #2
You need to find a third basis vector. What you need is a "generalized eigen vector". The characteristic equation for this matrix is [itex](\lambda- 2)^3= 0[/itex] and every matrix satisfies its own characteristic equation- that is, [itex](A- 2I)^3v= 0[/itex] for every vector v in the vector space. But you were not able to find three indepedent vectors such that (A- 2I)v= 0. That means there must exist a one dimensional space of vectors, v, for which (A- 2I)v is not equal to 0 but [itex](A- 2I)^2v= (A- 2I)[(A- 2I)v]= 0[/itex]. And that means that (A- 2I)v must be an eigenvector. A "generalized eigenvector" must satisfy either (A- 2I)v= <1, 0, 1> or (A- 2I)v= <4, 1, 0>. Try to solve those equations.
 
  • #3
I tried to solve those equations before I asked here but neither of them has a solution over [itex]\mathbb Z_{5}[/itex]
That's the reason why I'm so puzzled.:-/
 
  • #4
I've double-checked my attempt at solution but I didn't find any mistakes.
Now, I'm really desperate.:confused:

I was hopping somebody could tell me what I was doing wrong.:smile:
 

Related to Jordan Normal Form: Find Basis B in $\mathbb{Z}_{5}^{3}$

1. What is the Jordan Normal Form?

The Jordan Normal Form is a way to represent a square matrix as a diagonal matrix with blocks of ones and zeros on the diagonal. It is useful for simplifying calculations and studying the properties of matrices.

2. How do you find the Jordan Normal Form?

To find the Jordan Normal Form, you must first find the eigenvalues and corresponding eigenvectors of the matrix. Then, you can construct the Jordan blocks for each eigenvalue and combine them to form the Jordan Normal Form matrix.

3. What is a Basis B in $\mathbb{Z}_{5}^{3}$?

A Basis B in $\mathbb{Z}_{5}^{3}$ is a set of three vectors that span the vector space $\mathbb{Z}_{5}^{3}$. This means that any vector in $\mathbb{Z}_{5}^{3}$ can be written as a linear combination of these three vectors.

4. How do you find a Basis B in $\mathbb{Z}_{5}^{3}$ given a Jordan Normal Form?

To find a Basis B in $\mathbb{Z}_{5}^{3}$ given a Jordan Normal Form, you can use the eigenvectors associated with the Jordan blocks in the normal form. These eigenvectors can be used as the basis vectors for the vector space.

5. Why is it important to find the basis B in $\mathbb{Z}_{5}^{3}$ for the Jordan Normal Form?

Finding the basis B in $\mathbb{Z}_{5}^{3}$ for the Jordan Normal Form allows us to understand the structure of the matrix and its eigenvectors. This can help us solve systems of linear equations, determine the stability of a system, and make predictions about the behavior of the matrix over time.

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