Eigenvector for Complex Eigenvalue help

In summary, the professor found an eigenvalue for a matrix using the eigenvalue c= 1 + i and ended up with the matrix (5 3+i) as row 1, and the second row is zeroes. After that, he simply wrote that the basis for this eigenvalue c is (3+i,-5) (in column form) without explaining.
  • #1
SeannyBoi71
84
0
In my lecture notes my prof used the eigenvalue c= 1 + i and ended up with the matrix with (5 3+i) as row 1, and the second row is zeroes. After that, he simply wrote that the basis for this eigenvalue c is (3+i,-5) (in column form) without explaining. How did he get that basis? I tried working it out and not sure what he did.
 
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  • #2
I really don't understand what you are trying to say. You cannot start with an eigenvalue and just make a matrix out of it. Possibly, you are saying that 1+i is an eigenvalue of a given matrix and that the new matrix was constructed of corresponding eigenvectors. Also, it makes no sense to say "a basis for an eigenvalue" since only vector spaces have bases and an eigenvalue is a number. Perhaps you mean "basis for the subspace of all eigenvectors corresponding to the given eigenvalue".


What was the original matrix for which 1+ i was an eigenvalue? That is essential to understanding this.

(It is certainly true that the vectors (5, 3+i) and (3+ i, -5) are orthogonal. That may be relevant.)
 
  • #3
HallsofIvy said:
Perhaps you mean "basis for the subspace of all eigenvectors corresponding to the given eigenvalue".)

Yes, this is what I meant. Sorry for any confusion.

In the example, A=(4 2) (row 1) and (-5 -2) (row 2) (my apologies, I don't know how to put actually make that into a matrix here). We found the characteristic polynomial, and that the roots were 1+i and 1-i. He took the eigenvalue 1+i, and proceeded to get the eigenvector for that eigenvalue. When he plugged in [tex] ((i+1)I_2 - A)) [/tex] he then row reduced and got the matrix I said in my first post. He then wrote that the basis for this eigenvalue was (3+i, -5). I hope that clarifies. I was just confused on the arithmetic he did to get that basis.
 
  • #4
It is because for a real operator eigenvalues and eigenvectors come in complex conjugate pairs.
so if we have the eigen pair
1 + i;(3+i,-5)
we also have the eigen pair
1 - i;(3-i,-5)
 
  • #5
If you row reduce a 2x2 singular matrix, you will always get something of the form
[tex]\left(\begin{array}{c}a & b \\ 0 & 0\end{array}\right)[/tex]
And if you want a non-zero solution to
[tex]\left(\begin{array}{c}a & b \\ 0 & 0\end{array}\right)
\left(\begin{array}{c}x \\ y \end{array}\right)=
\left(\begin{array}{c}0 \\ 0 \end{array}\right)[/tex]
If sould be obvious it will be a multiple of
[tex]\left(\begin{array}{c}-b \\ a\end{array}\right)[/tex]
 
  • #6
Ok this all makes sense. Thank you
 

1. What is an eigenvector for a complex eigenvalue?

An eigenvector for a complex eigenvalue is a vector that, when multiplied by a square matrix, results in a scalar multiple of itself. In other words, the eigenvector does not change direction when multiplied by the matrix, but only changes in length by a factor equal to the complex eigenvalue.

2. How do you find eigenvectors for complex eigenvalues?

To find eigenvectors for complex eigenvalues, you first need to find the eigenvalues of the square matrix. Then, you can use the eigenvalues to solve for the corresponding eigenvectors by setting up and solving a system of linear equations.

3. Why are eigenvectors and eigenvalues important in linear algebra?

Eigenvectors and eigenvalues are important in linear algebra because they provide a way to simplify and analyze linear transformations. They allow for the identification of important directions and scaling factors in a transformation, making it easier to understand and manipulate complex systems.

4. What is the relationship between eigenvectors and complex eigenvalues?

Eigenvectors and complex eigenvalues are related in that a complex eigenvalue represents the scaling factor for the corresponding eigenvector in a linear transformation. This means that the eigenvectors are only affected by the complex eigenvalues, rather than the entire matrix, making them useful for simplifying and analyzing linear transformations.

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

Yes, a complex matrix can have real eigenvectors and eigenvalues. This means that the eigenvectors and eigenvalues are not necessarily complex numbers, but can be real numbers. However, the complex matrix may also have complex eigenvectors and eigenvalues, depending on the matrix's properties.

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