Linear Algebra- Commuting matrix

In summary, the task at hand is to determine the subspace of R2x2 consisting of all matrices that commute with the given matrices. This means that AB=BA, and after analyzing the given matrices, we find that the first one results in the set of diagonal matrices, while the second one results in the set of matrices with b21=0 and b11=b22. The provided solution is also confirmed to be correct through further explanation and calculations.
  • #1
Roni1985
201
0

Homework Statement


Determint the subspace fo R2x2 consisting of all matrices that commute with the given matrix:
a) A=[(1,0)^T,(0,-1)^T]

c) A=[(1,0)^T,(1,1)^T]

Homework Equations


The Attempt at a Solution


What I need to show is that AB=BA. So, I am trying to see when it happens...

I think I got them right buy let me see:
let B be any matrix in the subspace

a) S= {B | b12=b21=0} OR it should be S= {B | b12=-b21}

c) S= {B | b21=0 and b11=b22 }

are they correct ?

perhaps I am a little off with the notations :\
 
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  • #2
Okay, so
[tex]A= \begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}[/tex]

Saying that [tex]B= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}[/tex] commutes with A means
[tex]AB= \begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}\begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}\begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}= BA[/tex]

[tex]\begin{bmatrix}b_{11} & b_{12} \\ -b_{21} & -b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & -b_{12} \\ b_{21} & -b_{22}\end{bmatrix}[/tex]

So the conditions are that [itex]b_{12}= -b_{12}[/itex] which gives [itex]b_{12}= 0[/itex] and [itex]-b_{21}= b_{21}[/itex] so [itex]b_{21}= 0[/itex].

Your first statement is correct- this is the set of diagonal matrices.

With [tex]A= \begin{bmatrix} 1 & 1 \\ 0 & 1\end{bmatrix}[/tex]
we have
[tex]AB= \begin{bmatrix}1 & 1 \\ 0 & 1\end{bmatrix}\begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}\begin{bmatrix}1 & 1 \\ 0 & 1\end{bmatrix}= BA[/tex]

[tex]\begin{bmatrix}b_{11}+ b_{21} & b_{12}+ b_{22} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{11}+ b_{12} \\ b_{21} & b_{21}+ b_{22}\end{bmatrix}[/tex]
So we must have [itex]b_{11}+ b_{21}= b_{11}[/itex], which means [itex]b_{21}= 0[/itex], [itex]b_{12}+ b_{22}= b_{11}+ b_{12}[/itex], which means [itex]b_{11}= b_{22}[/itex], and [itex]b_{22}= b_{21}+ b_{22}[/itex], which means [itex]b_{21}= 0[/itex].

That's exactly what you have! Very good!
 
  • #3
HallsofIvy said:
Okay, so
[tex]A= \begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}[/tex]

Saying that [tex]B= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}[/tex] commutes with A means
[tex]AB= \begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}\begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}\begin{bmatrix}1 & 0 \\ 0 & -1\end{bmatrix}= BA[/tex]

[tex]\begin{bmatrix}b_{11} & b_{12} \\ -b_{21} & -b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & -b_{12} \\ b_{21} & -b_{22}\end{bmatrix}[/tex]

So the conditions are that [itex]b_{12}= -b_{12}[/itex] which gives [itex]b_{12}= 0[/itex] and [itex]-b_{21}= b_{21}[/itex] so [itex]b_{21}= 0[/itex].

Your first statement is correct- this is the set of diagonal matrices.

With [tex]A= \begin{bmatrix} 1 & 1 \\ 0 & 1\end{bmatrix}[/tex]
we have
[tex]AB= \begin{bmatrix}1 & 1 \\ 0 & 1\end{bmatrix}\begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{12} \\ b_{21} & b_{22}\end{bmatrix}\begin{bmatrix}1 & 1 \\ 0 & 1\end{bmatrix}= BA[/tex]

[tex]\begin{bmatrix}b_{11}+ b_{21} & b_{12}+ b_{22} \\ b_{21} & b_{22}\end{bmatrix}= \begin{bmatrix}b_{11} & b_{11}+ b_{12} \\ b_{21} & b_{21}+ b_{22}\end{bmatrix}[/tex]
So we must have [itex]b_{11}+ b_{21}= b_{11}[/itex], which means [itex]b_{21}= 0[/itex], [itex]b_{12}+ b_{22}= b_{11}+ b_{12}[/itex], which means [itex]b_{11}= b_{22}[/itex], and [itex]b_{22}= b_{21}+ b_{22}[/itex], which means [itex]b_{21}= 0[/itex].

That's exactly what you have! Very good!
This is some amazing explanation :)
Thank you very much.
This was very helpful.

Thanks a lot, HallsofIvy.
 

1. What is a commuting matrix?

A commuting matrix is a square matrix that can be multiplied with another matrix in any order without changing the result. This means that the two matrices "commute" with each other.

2. How do you determine if two matrices commute?

Two matrices A and B commute if and only if AB = BA. In other words, if the product of the two matrices is equal regardless of the order in which they are multiplied.

3. Can non-square matrices commute?

No, non-square matrices cannot commute because the product of two matrices is only defined when the number of columns in the first matrix is equal to the number of rows in the second matrix.

4. Why is it important to study commuting matrices?

Commuting matrices play a crucial role in many areas of mathematics and science, particularly in linear algebra and quantum mechanics. They have applications in solving systems of linear equations, diagonalizing matrices, and understanding the behavior of quantum particles.

5. How do commuting matrices relate to eigenvectors and eigenvalues?

If two matrices commute, then they share a common set of eigenvectors. This means that the eigenvectors of one matrix are also eigenvectors of the other matrix. However, the eigenvalues may be different. This relationship can be useful in simplifying computations and understanding the properties of the matrices.

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