Complex Eigenvalues and Eigenvectors of a 2x2 Matrix: Diagonalizable or Not?

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In summary, the matrix A cannot be diagonalized because its characteristic polynomial has complex roots. The determinant of A is λ2 - 1 = 0, leading to eigenvalues of λ1 = 1 and λ2 = -1. Therefore, A is not diagonalizable.
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Homework Statement


Find the eigenvalues and eigenvectors of A. (Both eigenvalues and eigenvectors are now allowed
to be complex.) Is it diagonalizable? Explain why or why not. If it is diagonalizable, explicitly
find matrices P and D such that
A = PDP−1
where D is a diagonal 2 × 2 matrix.

A = [ 0 -i | i 0 ]

The Attempt at a Solution



I determined that A cannot be diagonalized because, by the characteristic polynomial equation we get [tex]\lambda[/tex]2 + 1 = 0

Therefore [tex]\lambda[/tex]1 = -i [tex]\lambda[/tex]2 = i

plugging [tex]\lambda[/tex]2 into my matrix A I get:

ix + iy = 0
-ix + iy = 0

but the only solution to this is x=y=0, I get the same result for [tex]\lambda[/tex]1

Is this correct? I have a feeling this trivial solution is wrong
I tried row reduction, but I still get the same result.
 
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  • #2
so many minuses!

Hi Iconate! :smile:

(have a lambda: λ :wink:)
Iconate said:
A = [ 0 -i | i 0 ]

… by the characteristic polynomial equation we get [tex]\lambda[/tex]2 + 1 = 0

Noooo! :redface:
 
  • #3


Ahhh I see
my determinant should be
λ2 - (-i)(i) = 0
λ2 + (i2) = 0
λ2 - 1 = 0

thus λ1 = 1 λ1 = -1

Thanks >.<
 

1. What are complex eigenvalues and eigenvectors?

Complex eigenvalues and eigenvectors are a set of numbers and corresponding vectors that describe the behavior of a linear transformation in a complex vector space. In simpler terms, they represent the direction and magnitude of stretching or shrinking of a vector when multiplied by a specific matrix.

2. How are complex eigenvalues and eigenvectors different from real eigenvalues and eigenvectors?

While real eigenvalues and eigenvectors only exist in real vector spaces, complex eigenvalues and eigenvectors exist in complex vector spaces. Additionally, complex eigenvalues have both a real and imaginary component, while real eigenvalues are purely real numbers.

3. Why are complex eigenvalues and eigenvectors important?

Complex eigenvalues and eigenvectors are important in many areas of mathematics and science. They are used in solving differential equations, understanding the behavior of dynamical systems, and in quantum mechanics. They also have applications in engineering, computer science, and economics.

4. How do you find complex eigenvalues and eigenvectors?

Finding complex eigenvalues and eigenvectors involves solving a characteristic equation, which is a polynomial equation that involves the matrix and an unknown eigenvalue. The solutions to this equation are the complex eigenvalues, and the corresponding eigenvectors can be found by solving a system of linear equations.

5. Can a matrix have only complex eigenvalues and eigenvectors?

Yes, a matrix can have only complex eigenvalues and eigenvectors. This is the case when the matrix has complex entries, and it is not possible to find real eigenvalues and eigenvectors. In such cases, the matrix is said to have a complex spectrum.

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