Using inverse to find eigenvalues

In summary: Maybe the OP thought the discussion was about a particular matrix, but that's a pretty big assumption.
  • #1
ChiralSuperfields
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Homework Statement
Pleases ee below
Relevant Equations
Please see below
For this,
1684729405326.png

I don't understand how if ##(A - 2I_2)^{-1}## has an inverse then the next line is true.

Many thanks!
 

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  • #2
$$
A-2I =\begin{pmatrix}1&-2\\1&-2\end{pmatrix}-\begin{pmatrix}2&0\\0&2\end{pmatrix}=\begin{pmatrix}-1&-2\\1&-4\end{pmatrix}
$$
and thus ##(A-2I)^{-1}=\dfrac{1}{6}\begin{pmatrix}-4&2\\-1&-1\end{pmatrix}##

So ##A-2I## is invertible. Since we have ##A\cdot \begin{pmatrix}x\\y\end{pmatrix}=2I\cdot \begin{pmatrix}x\\y\end{pmatrix},## we get
$$
A\cdot \begin{pmatrix}x\\y\end{pmatrix}-2I\cdot \begin{pmatrix}x\\y\end{pmatrix}= (A-2I)\begin{pmatrix}x\\y\end{pmatrix}=\begin{pmatrix}0\\0\end{pmatrix}
$$
Applying ##(A-2I)^{-1}## on both sides results in
$$
(A-2I)^{-1}\cdot (A-2I)\cdot \begin{pmatrix}x\\y\end{pmatrix}= I\cdot \begin{pmatrix}x\\y\end{pmatrix} =\begin{pmatrix}x\\y\end{pmatrix} =(A-2I)^{-1}\cdot \begin{pmatrix}0\\0\end{pmatrix}=\begin{pmatrix}0\\0\end{pmatrix}
$$
 
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  • #3
The thread title, "Using inverse to find eigenvalues," doesn't make sense to me. When your goal is to find the eigenvalues and eigenvectors for a given matrix A, the matrix expression you work with is by definition noninvertible. The process of finding eigenvalues involves a matrix expression whose determinant is zero; i.e., ##|A - \lambda I| = 0##. The determinant of a invertible matrix is always nonzero.

The matrix expression ##A - 2I_2## in this thread turns out to be invertible precisely because 2 is not an eigenvalue of A. If the author of the material in the picture you uploaded has a point, it's not clear to me what it is.

The matrix A - 2I that fresh_42 shows is the same as the matrix A I found in your thread from yesterday, namely ##A = \begin{bmatrix}-1 & -2 \\ 1 & -4 \end{bmatrix}##. I mentioned yesterday that the eigenvalues for this matrix expression happen to be -2 and -3.

The matrix ##A + 2I_2 = A - (-2)I_2 = \begin{bmatrix}1 & -2 \\ 1 & -2 \end{bmatrix}##. Because the determinant of ##A + 2I_2 = 0##, ##A + 2I_2## does not have an inverse. The same is true for the matrix ##A + 3I_2 = A - (-3)I_2##.

The process of finding an eigenvalue ##\lambda## for a matrix A is this:
  1. Write the matrix ##A - \lambda I_n##, with n = 2 for 2 x 2 matrices, n = 3 for 3 x 3 matrices, and so on.
  2. Set the determinant of ##A - \lambda I_n## to zero, and solve the resulting polynomial involving powers of ##\lambda##.
 
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  • #4
fresh_42 said:
$$
A-2I =\begin{pmatrix}1&-2\\1&-2\end{pmatrix}-\begin{pmatrix}2&0\\0&2\end{pmatrix}=\begin{pmatrix}-1&-2\\1&-4\end{pmatrix}
$$
and thus ##(A-2I)^{-1}=\dfrac{1}{6}\begin{pmatrix}-4&2\\-1&-1\end{pmatrix}##
The attached image in post 1 of this thread doesn't specify any particular matrix, so it's not possible to determine the entries of A - 2I. You might be confusing what was in the hand-drawn sketch of the previous thread from the OP, which itself was confused.
fresh_42 said:
So ##A-2I## is invertible. Since we have ##A\cdot \begin{pmatrix}x\\y\end{pmatrix}=2I\cdot \begin{pmatrix}x\\y\end{pmatrix},## we get
$$
A\cdot \begin{pmatrix}x\\y\end{pmatrix}-2I\cdot \begin{pmatrix}x\\y\end{pmatrix}= (A-2I)\begin{pmatrix}x\\y\end{pmatrix}=\begin{pmatrix}0\\0\end{pmatrix}
$$
Applying ##(A-2I)^{-1}## on both sides results in
$$
(A-2I)^{-1}\cdot (A-2I)\cdot \begin{pmatrix}x\\y\end{pmatrix}= I\cdot \begin{pmatrix}x\\y\end{pmatrix} =\begin{pmatrix}x\\y\end{pmatrix} =(A-2I)^{-1}\cdot \begin{pmatrix}0\\0\end{pmatrix}=\begin{pmatrix}0\\0\end{pmatrix}
$$
 
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  • #5
Mark44 said:
The attached image in post 1 of this thread doesn't specify any particular matrix, so it's not possible to determine the entries of A - 2I.
Occam's razor. Why complicate things? I do not debate typos.

However, the nice part is: it does not even matter! The line of the argument remains the same if ##A## has a different form as long as ##A-2I## remains regular!
 
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  • #6
fresh_42 said:
Occam's razor. Why complicate things?
The OP is already sufficiently confused as evidenced in the thread title, in thinking that finding the inverse of a matrix plays any role in finding eigenvalues. Muddying up the water by tossing in a specific matrix where none was given doesn't help alleviate that confusion.
 
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1. What is the inverse method used for in finding eigenvalues?

The inverse method is used to find the eigenvalues of a matrix by first finding the inverse of the matrix and then using the inverse to calculate the eigenvalues.

2. How do you find the inverse of a matrix?

The inverse of a matrix can be found by using the Gaussian elimination method or by using the adjugate matrix method. Both methods involve performing a series of row operations on the matrix to reduce it to its inverse form.

3. Can any matrix have an inverse?

No, not all matrices have an inverse. A matrix must be square and have a non-zero determinant in order to have an inverse. Matrices with zero determinants are called singular matrices and do not have an inverse.

4. How does the inverse method work to find eigenvalues?

The inverse method works by first finding the inverse of the matrix, which is a new matrix that when multiplied by the original matrix results in the identity matrix. Then, the eigenvalues can be calculated by solving the characteristic equation using the inverse matrix.

5. Are there any limitations to using the inverse method for finding eigenvalues?

Yes, there are some limitations to using the inverse method. It can only be used for square matrices with non-zero determinants. Additionally, the inverse method can be computationally expensive for large matrices, so other methods may be more efficient in those cases.

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