Eigenvector with Complex Eigenvalues - What am I doing wrong?

In summary, the conversation discusses solving a problem involving complex numbers and matrix reduction. One person shares their attempted solution and asks for help in identifying their mistake. Another person points out the error and provides the correct solution using an eigenvector.
  • #1
alsvt
4
0

Homework Statement


eigenvector.png

Homework Equations


Conjugate of a complex number
Matrix reduction

The Attempt at a Solution



My attempt is bordered. Sorry about the quality.
snapshot.jpg


So I'm not sure what I'm missing. I use the exact same method that I use for normal eigenvectors, just with complex numbers in the mix.
 
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  • #2
You messed up in the last step and swapped x1 and x2. If you let x2=1, then your equation gave you x1=-1/2+1/2 i. In the vector, however, you have the two values in the other order.
 
  • #3
I can't quite read all of your work, but if you subtract [tex]\lambda[/tex] along the diagonal, you get:

[tex] \bmatrix
1 + i & 1 \\
-2 & -1 + i \\
\endbmatrix x = 0 [/tex]

The rows of this matrix are multiples (-1 + i) of each other, so you can use either row to find the eigenvector:

[tex] x_1 (1 + i) + x_2 = 0 [/tex]
[tex] -x_1 (1 + i) = x_2 [/tex]

so your vector is (1, -1 - i). This happens to not be one of your choices, but you can multiply it by i to obtain (i, 1 - i).
 
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  • #4
@vela Thanks. I wasn't really thinking it through at the end.
 

FAQ: Eigenvector with Complex Eigenvalues - What am I doing wrong?

1. What is an eigenvector with complex eigenvalues?

An eigenvector with complex eigenvalues is a vector that, when multiplied by a square matrix, results in a scalar multiple of itself. The eigenvalues associated with this eigenvector are complex numbers, which means they have both a real and imaginary component.

2. Why do I keep getting complex eigenvalues when calculating eigenvectors?

Complex eigenvalues can occur when the matrix being used has complex entries or when the matrix is not symmetric. It is important to check the properties of the matrix before calculating eigenvectors to ensure that complex eigenvalues are expected.

3. How do I find the eigenvectors for a matrix with complex eigenvalues?

The process for finding eigenvectors with complex eigenvalues is the same as finding eigenvectors with real eigenvalues. However, the resulting eigenvectors will be complex vectors instead of real vectors. It is important to remember to use complex arithmetic when performing calculations with complex eigenvectors.

4. Can an eigenvector have both real and imaginary components?

Yes, an eigenvector can have both real and imaginary components. This means that the eigenvector is a complex vector, and its corresponding eigenvalue will also be complex.

5. What are some real-world applications of eigenvectors with complex eigenvalues?

Eigenvectors with complex eigenvalues have many applications in physics, engineering, and computer science. For example, they are used in quantum mechanics to describe the state of a quantum system, in image processing to identify patterns and features, and in control systems to analyze the stability of a system.

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