Is this normalised eigenvector undefined?

In summary, the conversation discussed finding the eigenvalues and eigenvectors of a 2x2 matrix, normalizing the eigenvectors, and checking if the matrix is Hermitian. It was determined that the eigenvalues are both real and the eigenvectors satisfy the properties of a Hermitian matrix when the dot product is taken with the complex conjugate.
  • #1
ZedCar
354
1

Homework Statement



I've started off with a 2x2 matrix of

(0) (i)
(-i) (0)

and I found the eigenvalues to be +1, -1

Then I found the resulting 2x1 eigenvectors to be

(-i)
(1)

and

(1)
(-i)

I now need the normalised eigenvectors.


Homework Equations





The Attempt at a Solution



I'm getting

{1/[sqrt(0)]} x eigenvector1
{1/[sqrt(0)]} x eigenvector2

Does this mean the normalised eigenvectors in this case are undefined?
 
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  • #2
You need to take the dot product with the complex conjugate of the vector if it's over a complex field.

[itex]|a| = \sqrt{a*\ .\ a}[/itex]
 
  • #3
Thank you.

Do you mean then that the normalised eigenvectors would be

[1/(sqrt(a* . a))] x eigenvector1

and

[1/(sqrt(a* . a))] x eigenvector2
 
  • #4
yes, if a is the eigenvector in question.
This still holds if the eigenvectors are all real, the magnitude of a real vector a is still [itex]\sqrt{a*\ .\ a}[/itex] but since a is real a*=a and we get the familiar [itex]\sqrt{a\ .\ a}[/itex]
 
  • #5
I'm getting values for the normalised eigenvectors of

{1/[sqrt(2)]} x eigenvector1
{1/[sqrt(2)]} x eigenvector2

What do you think?
 
  • #6
That is correct!
 
  • #7
Great!

I noticed there, with the two 2x1 eigenvectors which I in my first post being

(-i)
(1)

and

(1)
(-i)

For the number that's going to be under the radical, in this case we discovered it to be 2, can I simply take the [magnitude of (1)]^2 + the [magnitude of (-i)]^2 which equals 1+1=2 rather than take the dot product? Or am I effectively taking the dot product by doing this?
 
  • #8
Yes, [itex](a+ bi)(a- bi)= a^2+ b^2[/itex].
 
  • #9
You are taking the dot product when you do this, yes :p
 
  • #10
That's great guys! Thanks very much for your help. It's much appreciated!
 
  • #11
The final part of this question states that the original matrix is Hermitian, and that I should check that the eigenvalues and eigenvectors have the required properties for those of a Hermitian matrix.

The eigenvalues are both real, so that is satisfied.

Therefore for the eigenvectors to satisfy the required properties of a Hermitian matrix, (eigenvector1)^T x eigenvector2 = (eigenvector2)^T x eigenvector1 = 0

^T indicates Transpose

When I do this I'm getting -2i for both. So they are both equal to each other. Though 2i is not = 0 i.e. a null vector
 
  • #12
Remember that when you take the dot product of two complex vectors you need to take the complex conjugate of one of them.
You'll find that [itex]e_1*.e_2 = e_2*.e_1 = 0[/itex], where e1 and e2 are the two eigen vectors and * is complex conjugation.
 
  • #13
That's great. Thanks very much again genericusrnme!
 
  • #14
No problem buddy :biggrin:
 

Related to Is this normalised eigenvector undefined?

1. What is a normalised eigenvector?

A normalised eigenvector is a vector that has been scaled to have a magnitude of 1. This is important because it allows us to easily compare the relative sizes of different eigenvectors and simplifies calculations involving multiple eigenvectors.

2. Why is a normalised eigenvector important in linear algebra?

In linear algebra, eigenvectors are used to represent the directions of the linear transformations of a matrix. A normalised eigenvector is important because it simplifies calculations and makes it easier to interpret the results of these transformations.

3. How is a normalised eigenvector calculated?

A normalised eigenvector is calculated by dividing the eigenvector by its magnitude. This can be done using the normalization formula: v/||v||, where v is the eigenvector and ||v|| represents the magnitude or length of v.

4. Can an eigenvector be normalised to any value other than 1?

Yes, an eigenvector can be normalised to any desired value. The purpose of normalising an eigenvector is to simplify calculations and comparisons, so the value chosen should be relevant to the problem at hand.

5. When is a normalised eigenvector undefined?

A normalised eigenvector is undefined when the eigenvector itself is a zero vector, meaning all of its components are equal to zero. This is because the magnitude of a zero vector is also equal to zero, and division by zero is undefined.

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