- #1
zenterix
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- Homework Statement
- Suppose ##T\in\mathcal{L}(V)##.
Prove that 9 is an eigenvalue of ##T^2\iff## ##3## or ##-3## is an eigenvalue of ##T##.
- Relevant Equations
- Let's consider just one direction of the biconditional. Let's suppose 9 is an eigenvalue of ##T^2## and prove that 3 or ##-3## is an eigenvalue of ##T##.
Suppose ##9## is an eigenvalue of ##T^2##.
Then ##T^2v=9v## for certain vectors in ##V##, namely the eigenvectors of eigenvalue ##9##.
Then
##(T^2-9I)v=0##
##(T+3I)(T-3I)v=0##
There seem to be different ways to go about continuing the reasoning here.
My question will be about the associated eigenvectors.
One proof is the following
- Since ##(T^2-9I)=(T+3I)(T-3I)## is not injective then it can be shown that one of ##T+3I## or ##T-3I## must also not be injective.
- But this means that either 3 or ##-3## is an eigenvalue of ##T##.
Here is another proof
- Let ##p(x)=x+3## and ##q(x)=x-3##.
- Then ##p(T)=T+3I## and ##q(T)=T-3I##.
- Now, the product of the polynomials is ##(pq)(T)=p(T)q(T)=(T+3I)(T-3I)## and it can be shown that we can change the order of the factors. That is ##(pq)(T)=q(T)p(T)=(T-3I)(T+3I)##.
- Thus, if ##(T+3I)(T-3I)v=(T-3I)(T+3I)v=0## then let's consider all (four) possible cases.
Case 1: 3 is an eigenvalue of ##T##.
Case 1.1: -3 is an eigenvalue of ##T##.
The equation is satisfied.
Case 1.2: -3 is not an eigenvalue of ##T##.
The equation is satisfied.
Case 2: 3 is not an eigenvalue of ##T##.
Subcase 2.1: -3 is not an eigenvalue of ##T##.
The equation is not satisfied since no matter what ##(T-3I)v## is, when we apply ##T+3I## to it we will not get ##0##.
Subcase 2.2: -3 is an eigenvalue of ##T##.
The equation is satisfied because ##(T-3I)(T+3I)v=(T-3I)0=0##.
So a this point we've considered all possibilities. The conclusion is that we must either have Case 1.1, Case 1.2, or Case 2.2.
Thus, 3 is an eigenvalue of ##T## or ##-3## is an eigenvalue of ##T##.
My question is about the eigenvectors.
Notice that ##(T^2-9I)v=0## is true for eigenvectors of eigenvalue 9 of ##T^2##.
It seems that in case 1 an implicit result is that the eigenvectors of ##T^2## for eigenvalue 9 are the same eigenvectors of ##T## for eigenvalue 3.
Similarly, in case 2.2 these are also the eigenvectors for eigenvalue -3 of ##T##.
But what happens in case 1.1, when both -3 and 3 are eigenvalues?
Then ##T^2v=9v## for certain vectors in ##V##, namely the eigenvectors of eigenvalue ##9##.
Then
##(T^2-9I)v=0##
##(T+3I)(T-3I)v=0##
There seem to be different ways to go about continuing the reasoning here.
My question will be about the associated eigenvectors.
One proof is the following
- Since ##(T^2-9I)=(T+3I)(T-3I)## is not injective then it can be shown that one of ##T+3I## or ##T-3I## must also not be injective.
- But this means that either 3 or ##-3## is an eigenvalue of ##T##.
Here is another proof
- Let ##p(x)=x+3## and ##q(x)=x-3##.
- Then ##p(T)=T+3I## and ##q(T)=T-3I##.
- Now, the product of the polynomials is ##(pq)(T)=p(T)q(T)=(T+3I)(T-3I)## and it can be shown that we can change the order of the factors. That is ##(pq)(T)=q(T)p(T)=(T-3I)(T+3I)##.
- Thus, if ##(T+3I)(T-3I)v=(T-3I)(T+3I)v=0## then let's consider all (four) possible cases.
Case 1: 3 is an eigenvalue of ##T##.
Case 1.1: -3 is an eigenvalue of ##T##.
The equation is satisfied.
Case 1.2: -3 is not an eigenvalue of ##T##.
The equation is satisfied.
Case 2: 3 is not an eigenvalue of ##T##.
Subcase 2.1: -3 is not an eigenvalue of ##T##.
The equation is not satisfied since no matter what ##(T-3I)v## is, when we apply ##T+3I## to it we will not get ##0##.
Subcase 2.2: -3 is an eigenvalue of ##T##.
The equation is satisfied because ##(T-3I)(T+3I)v=(T-3I)0=0##.
So a this point we've considered all possibilities. The conclusion is that we must either have Case 1.1, Case 1.2, or Case 2.2.
Thus, 3 is an eigenvalue of ##T## or ##-3## is an eigenvalue of ##T##.
My question is about the eigenvectors.
Notice that ##(T^2-9I)v=0## is true for eigenvectors of eigenvalue 9 of ##T^2##.
It seems that in case 1 an implicit result is that the eigenvectors of ##T^2## for eigenvalue 9 are the same eigenvectors of ##T## for eigenvalue 3.
Similarly, in case 2.2 these are also the eigenvectors for eigenvalue -3 of ##T##.
But what happens in case 1.1, when both -3 and 3 are eigenvalues?