Help! Wrong Eigenvalues Using Matrix A

In summary, the problem is that you substituted the wrong eigenvector into the third system of equations.
  • #1
Yankel
395
0
Hello all,

I have a problem with eigenvalues. I tried finding eigenvalues and eigenvectors of a matrix A. I did once using:

\[\lambda I-A\]

And a second time using:

\[A-\lambda I\]

For the first eigenvalue I got identical eigenvectors in both methods, but for the second eigenvalue, the first method was wrong, while the second was correct. I can't find the problem. I am attaching my solution using

\[\lambda I-A\]

which is wrong. Can you assist ? Thank you !

View attachment 3800
 

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  • #2
Why don't you substitute the third, problematic, eigenvector, in each of the three systems of equations you got in the process of finding the echelon form?
 
  • #3
Not sure I follow you...

I would like to know why this eigenvector is problematic
 
  • #4
You have three systems of linear equations on the second page with matrices
\[
\begin{pmatrix}1&-1&-1\\-1&1&-1\\0&0&2\end{pmatrix}\qquad
\begin{pmatrix}1&1&1\\0&0&-2\\0&0&1\end{pmatrix}\qquad
\begin{pmatrix}1&1&1\\0&0&1\\0&0&0\end{pmatrix}
\]
I suggest substituting $x=-1$, $y=1$, $z=0$ into those systems to see if it is really a solution.
 
  • #5
I see, it isn't a solution. So you confirmed the fact that I made a mistake, but where is it ?
 
  • #6
Maybe I was writing in Russian... (Smile)

Evgeny.Makarov said:
Why don't you substitute the third, problematic, eigenvector, in each of the three systems of equations you got in the process of finding the echelon form?
This way you can see which of the system is correct ($x=−1$, $y=1$, $z=0$ is not a solution) and which is wrong (it is a solution), and thus determine the first system that is wrong. Looking at it carefully, you'll see the mistake.

This is the way to find mistakes in other similar situations.
 
  • #7
Hi,

After first arrow in second page you have modified first row of the matrix.
 
  • #8
Evegeny, you were writing in English, not Russian, it's my fault for not getting it quicker. Now I understand (finally) your method, it's a good idea, thank you !

Fallen Angel, thanks ! I made a silly mistake, thanks for finding it !
 

1. What are eigenvalues and why are they important in matrix A?

Eigenvalues are a set of numbers that represent the scaling factor of a linear transformation in a matrix. They are important because they help us understand the behavior of the matrix and its corresponding linear transformation.

2. How do you calculate eigenvalues for matrix A?

Eigenvalues can be calculated by finding the roots of the characteristic polynomial of the matrix A. This involves solving a system of equations, where the determinant of the matrix minus a scalar multiple of the identity matrix is equal to 0.

3. What does it mean if the eigenvalues of matrix A are wrong?

If the eigenvalues of matrix A are wrong, it means that there is an error in the calculation. This could be due to a mistake in the method used to calculate the eigenvalues or an error in the values of the matrix itself.

4. How can I check if the eigenvalues of matrix A are correct?

You can check the correctness of the eigenvalues by calculating the determinant of the matrix minus a scalar multiple of the identity matrix using the eigenvalues. The determinant should be equal to 0 if the eigenvalues are correct.

5. Can the eigenvalues of matrix A be negative?

Yes, the eigenvalues of matrix A can be negative. The sign of the eigenvalues depends on the characteristics of the matrix and its corresponding linear transformation. However, for a symmetric matrix, all eigenvalues will be real and positive or equal to 0.

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