Eigentheory of Transformations between Matrix Spaces

In summary, the conversation is discussing how to find the matrix of T with respect to a basis and how to apply it to a 2x2 matrix. They also discuss finding the characteristic polynomial and its roots, which will be the eigenvalues.
  • #1
TranscendArcu
285
0

Homework Statement



Screen_shot_2012_02_28_at_12_38_46_PM.png


My instructor wants me to only solve for the case m=2.

The Attempt at a Solution



So I thought I should discover what T does to the standard basis for matrices of size 2x2:

[itex]T \left| \begin{array}{cc}
1 &0 \\
0&0 \end{array} \right| = \left| \begin{array}{cc}
1 &0 \\
0&0 \end{array} \right|[/itex]

[itex]T \left| \begin{array}{cc}
0 &1 \\
0&0 \end{array} \right| =\left| \begin{array}{cc}
0 &0 \\
1&0 \end{array} \right|[/itex]

[itex]T \left| \begin{array}{cc}
0 &0 \\
1&0 \end{array} \right| =\left| \begin{array}{cc}
0 &1 \\
0&0 \end{array} \right|[/itex]

[itex]T \left| \begin{array}{cc}
0 &0 \\
0&1 \end{array} \right| =\left| \begin{array}{cc}
0 &0 \\
0&1 \end{array} \right|[/itex]

At this point do I have to create a matrix consisting of these transformed matrices in order to find [itex]Δ_T (t) = det(M - tI)[/itex]? I'm kind of confused about my next step.
 
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  • #2
Yes, try to find the matrix of T with respect to your basis. This will be a 4x4 matrix.
 
  • #3
micromass said:
Yes, try to find the matrix of T with respect to your basis. This will be a 4x4 matrix.

But if the matrix is 4x4, how will I apply it to a 2x2 matrix? The inner matrix dimensions won't agree.
 
  • #4
The 2x2-matrices won't have anything to do with the matrix of T.

The entries of the matrix of T are coordinates.

For example, if we put on [itex]M_{2,2}(\mathbb{R})[/itex] (the 2x2-matrices) the basis you mention, then the 4x4-matrix will contain the coordinates of the image of the basis.

For example, you have to write

[tex]T\left(\begin{array}{cc} 1 & 0\\ 0 & 0\end{array}\right) [/tex]

as a linear combination of the basis. So we have

[tex]T\left(\begin{array}{cc} 1 & 0\\ 0 & 0\end{array}\right) = 1 \left(\begin{array}{cc} 1 & 0\\ 0 & 0\end{array}\right) + 0\left(\begin{array}{cc} 0 & 1\\ 0 & 0\end{array}\right) + 0\left(\begin{array}{cc} 0 & 0\\ 1 & 0\end{array}\right) +0\left(\begin{array}{cc} 0 & 0\\ 0 & 1\end{array}\right)[/tex]

So the coordinates of

[tex]T\left(\begin{array}{cc} 1 & 0\\ 0 & 0\end{array}\right)[/tex]

are (1,0,0,0). This will be the first column of the 4x4-matrix.
 
  • #5
Okay, then I have for my matrix:
[tex]
\left| \begin{array}{cccc}
1 &0&0&0 \\
0&0&1&0 \\
0&1&0&0 \\
0&0&0&1 \end{array} \right| = Q
[/tex]
[tex]
det(Q- tI) = det\left| \begin{array}{cccc}
1-t &0&0&0 \\
0&-t&1&0 \\
0&1&-t&0 \\
0&0&0&1-t \end{array} \right| = (1-t)(1-t)[(t)(t) - 1] = (t-1)^3 (t+1)
[/tex]

That is the characteristic polynomial, and its roots are the eigenvalues. So we have eigenvalues 1,-1. Look about right?
 
  • #6
That sounds correct. Now you need to find the eigenspaces.
 

1. What is the Eigentheory of Transformations between Matrix Spaces?

The Eigentheory of Transformations between Matrix Spaces is a mathematical concept that deals with the relationship between matrices and their corresponding eigenvectors and eigenvalues. It is a fundamental tool in linear algebra and is used to analyze the behavior of linear transformations.

2. How is the Eigentheory of Transformations between Matrix Spaces used in real-world applications?

The Eigentheory of Transformations between Matrix Spaces has numerous applications in various fields such as physics, engineering, and computer science. It is used in image and signal processing, data compression, and in the study of quantum mechanics, among others.

3. What is the significance of eigenvectors and eigenvalues in the Eigentheory of Transformations between Matrix Spaces?

Eigenvectors and eigenvalues play a crucial role in the Eigentheory of Transformations between Matrix Spaces as they represent the axes along which a linear transformation acts and the corresponding scaling factor, respectively. They provide important insights into the behavior of a transformation and can be used to simplify calculations.

4. How is the Eigentheory of Transformations between Matrix Spaces related to diagonalization?

The Eigentheory of Transformations between Matrix Spaces is closely related to the concept of diagonalization, which involves finding a diagonal matrix that is similar to the original matrix. The eigenvectors and eigenvalues of a matrix are used to perform this transformation, making the Eigentheory an essential tool in the process of diagonalization.

5. What are some common misconceptions about the Eigentheory of Transformations between Matrix Spaces?

One common misconception about the Eigentheory of Transformations between Matrix Spaces is that it only applies to square matrices. However, it can also be applied to rectangular matrices. Another misconception is that the eigenvalues and eigenvectors of a matrix are unique, when in fact, they can have multiple sets of eigenvalues and eigenvectors.

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