Eigenvalue of Polynomial Transformation

In summary, PandaGunship is trying to find the matrix for T, which will give the eigenvalues and bases for the eigenspaces of T. He is having trouble with the matrix, but is getting close with the help of Tiny Tim.
  • #1
PandaGunship
6
0

Homework Statement


Let T:P2→P2 be defined by
T(a0+a1x+a2x2)=(2a0-a1+3a2)+(4a0-5a1)x + (a1+2a2)x2
1) Find the eigenvalues of T
2) Find the bases for the eigenspaces of T.

I believe the 'a' values are constants.

Homework Equations


None.

The Attempt at a Solution


The problem I am having is actually pulling out the matrix for T. I know how to find eigenvalues (by solving det(λI-A) - A being the matrix) and from that finding the bases of the eigenspaces comes from substituting the eigenvalues into (λI-A) and performing elementary row operations to find the eigenvectors which form the bases.

What I have tried to do is separate the basis (1,x,x2) from the rest and come up with the matrix :
2a0 -a1 3a2
4a0 -5a1 0a2
0a0 a1 2a2
Am I on the right track here or am I barking up the wrong tree? If so what method should i follow?
 
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  • #2
Well, sort of. You need to figure out which elements the polynomials [itex]1,x,x^2[/itex] get sent to by [itex]T[/itex]. Once you do that, put them into a matrix and proceed as you have described. So, if you put the polynomial [itex]p_1(x) = x[/itex] into [itex]T[/itex] what would come out "the other side"?
 
  • #3
Hi PandaGunship! Welcome to PF! :smile:
PandaGunship said:
2a0 -a1 3a2
4a0 -5a1 0a2
0a0 a1 2a2

leave all the a's out! :wink:
 
  • #4
Robert1986 said:
Well, sort of. You need to figure out which elements the polynomials [itex]1,x,x^2[/itex] get sent to by [itex]T[/itex]. Once you do that, put them into a matrix and proceed as you have described. So, if you put the polynomial [itex]p_1(x) = x[/itex] into [itex]T[/itex] what would come out "the other side"?
Just to check, my matrix is correct?
As per your direction, a0 goes to 2a0 + 4a0x +0x2 which I make into a column like the matrix I put it already?
tiny-tim said:
Hi PandaGunship! Welcome to PF! :smile:

leave all the a's out! :wink:
Thanks Tim :) I thought of leaving the a's out, but what of their importance? Are they just to show what each constant of the basis is mapped into?
 
  • #5
PandaGunship said:
Thanks Tim :) I thought of leaving the a's out, but what of their importance? Are they just to show what each constant of the basis is mapped into?

No, your vectors will have a's. :smile:

(The 1 x x2 are just a basis like x y z …

you wouldn't expect x y z to appear in a vector or matrix, would you? :wink:)​
 
  • #6
Well, I said to find out where [itex]p_1(x) = x[/itex] goes, and what you did was find where [itex]p(x) = a_0 [/itex] goes. I only mentioned to do it as an example, so its OK that you did it for [itex]p(x) = a_0 [/itex].

So, the [itex]a_0, a_1, a_2 [/itex] are there because you need to know what [itex]T[/itex] does to a general quadratic polynomial, and that is the form of a general quadratic polynomial.

Now, the three basis polynomials we are using are: [itex] p_0(x) = 1, p_1(x) = x, p_2(x) = x^2[/itex]. Now, for each of these basis polynomials, what is [itex]a_0, a_1, a_2[/itex]? As an example, for [itex]p_0[/itex] we have that [itex]a_0 = 1, a_1 = 0, a_2 = 0[/itex]. So, [itex]T(p_0(x)) = 2a_0 + 4a_0x = a + 4x[/itex]. So, you got it correct, but as Tiny Tim said, you need to get rid of the a's because for the basis polynomials they are all 1 or 0.
 
  • #7
tiny-tim said:
No, your vectors will have a's. :smile:

(The 1 x x2 are just a basis like x y z …

you wouldn't expect x y z to appear in a vector or matrix, would you? :wink:)​
I suppose not :P Thanks :)
Robert1986 said:
Well, I said to find out where [itex]p_1(x) = x[/itex] goes, and what you did was find where [itex]p(x) = a_0 [/itex] goes. I only mentioned to do it as an example, so its OK that you did it for [itex]p(x) = a_0 [/itex].

So, the [itex]a_0, a_1, a_2 [/itex] are there because you need to know what [itex]T[/itex] does to a general quadratic polynomial, and that is the form of a general quadratic polynomial.

Now, the three basis polynomials we are using are: [itex] p_0(x) = 1, p_1(x) = x, p_2(x) = x^2[/itex]. Now, for each of these basis polynomials, what is [itex]a_0, a_1, a_2[/itex]? As an example, for [itex]p_0[/itex] we have that [itex]a_0 = 1, a_1 = 0, a_2 = 0[/itex]. So, [itex]T(p_0(x)) = 2a_0 + 4a_0x = a + 4x[/itex]. So, you got it correct, but as Tiny Tim said, you need to get rid of the a's because for the basis polynomials they are all 1 or 0.
Ok I understand properly now. In the beginning when I was going over this problem I thought that I must remove the a's but I didnt want to remove them 'just because'. I wanted to know that what I was doing was actually correct, even if my reasoning was a bit off the mark.
Thank you both for your help:biggrin:
 

FAQ: Eigenvalue of Polynomial Transformation

What is the eigenvalue of a polynomial transformation?

The eigenvalue of a polynomial transformation is a scalar value that represents the amount by which a vector is stretched or compressed when it is transformed by the polynomial transformation. It is an important concept in linear algebra and is used to understand the behavior of a transformation.

How is the eigenvalue of a polynomial transformation calculated?

The eigenvalue of a polynomial transformation is calculated by finding the roots of the characteristic polynomial of the transformation. This can be done by solving the characteristic equation, which is the determinant of the transformation's matrix minus the identity matrix multiplied by the eigenvalue.

Why is the eigenvalue of a polynomial transformation important?

The eigenvalue of a polynomial transformation is important because it provides information about the behavior of the transformation. It can tell us about the stretching or compressing effect of the transformation on vectors and can also be used to find eigenvectors, which are vectors that are only scaled by the transformation.

How is the eigenvalue of a polynomial transformation related to eigenvectors?

The eigenvalue and eigenvectors of a polynomial transformation are closely related. The eigenvalue represents the amount by which a vector is scaled, while the eigenvector is the direction in which the vector is scaled. In other words, an eigenvector is a vector that is only scaled by the transformation and its corresponding eigenvalue.

What is the significance of multiple eigenvalues in a polynomial transformation?

If a polynomial transformation has multiple eigenvalues, it means that there are multiple directions in which vectors are scaled by the transformation. This can provide insight into the behavior of the transformation and can be used to find a basis for the transformation's matrix.

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