Linear Algebra - Eigenvalues/Eigenvectors?

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Homework Help Overview

The discussion revolves around eigenvalues and eigenvectors in the context of a matrix \( A \) that satisfies the condition \( A^2 = I \). Participants are exploring the implications of this condition, particularly for a 2x2 matrix that is neither the identity matrix \( I \) nor its negative \( -I \). The topic is situated within the broader study of matrix diagonalization.

Discussion Character

  • Mixed

Approaches and Questions Raised

  • Participants discuss the possible eigenvalues of matrix \( A \) and the relationships between the determinant and trace of \( A \). Some express confusion regarding the implications of the determinant being equal to 1 or -1. Others question the consistency of their calculations and the complexity introduced by the trace equation when determining eigenvectors.

Discussion Status

There is an ongoing exploration of the eigenvalue equation and its implications for the determinant and trace of the matrix. Some participants have offered hints and corrections regarding the eigenvalues, while others are still grappling with their calculations and understanding of the problem. Multiple interpretations of the determinant and trace are being considered.

Contextual Notes

Participants note that the original problem does not provide specific equations or values, leading to uncertainty in their attempts to solve for the second row of the matrix. There is also a recognition of the complexity introduced by the need to diagonalize the matrix and the relationships between the eigenvalues and the determinant.

KIDRoach
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Homework Statement


a.) If A2 = I, what are the possible eigenvalues of A?
b.) If this A is 2 by 2, and not I or -I, find its trace and determinant.
c.) If the first row is (3,-1), what is the second row?

Homework Equations


None was given, but I think:

1. det(A) = 1 for A2 = I or A-1 = A

We're studying about Matrix diagonalization and the topic is called "Diagonalization of a Matrix". The equation S[tex]\Lambda[/tex]S-1 = A is supposed to be relevant.

The Attempt at a Solution


a.) I got the possible eigenvalues to be: [tex]\lambda[/tex]1 x [tex]\lambda[/tex] 2 x ... x [tex]\lambda[/tex]n = 1
b.) tr(A) = [tex]\lambda[/tex] + [tex]1/\lambda[/tex]
det(A) = 1
c.) This is where I'm stuck... I know I'm supposed to use the equation det(A) = 1 but there are two unknowns and I only know one equation. I was going to use the equation S[tex]\Lambda[/tex]S-1 = A but then I realized that I need the eigenvectors and I can't find the eigenvectors since I don't know the whole matrix.
 
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Welcome to PF!

Hi KIDRoach! Welcome to PF! :smile:

You're making this very complicated. :redface:

Hint: if det(A) = a, and det(B) = b, what is det(AB)? :wink:

(alternatively, just write A relative to a basis in which A is diagonal)
 
Hi Tim!

Thanks for answering my question. I tried that too I think, but I don't think it's right, or at least either that's wrong or one of the earlier answer is wrong. :(

I know that det(AB) = det(A) x det(B) = ab

When I tried it to solve the equation:
[tex] <br /> \[ \left( \begin{array}{ccc}<br /> 3 & -1 \\<br /> 0 & x \end{array} \right)\] [/tex]

I get x = 1/3, which, when I square the A matrix, I don't get the I matrix, so the equation is inconsistent/ something is wrong... But I can't figure out which part I'm wrong at... :(
 
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KIDRoach said:
I know that det(AB) = det(A) x det(B) = ab

ok, so if A2 = I, and if A ≠ I or -I, then det(A) = … ? :smile:
 
The eigenvalue equation is [tex]Ax=\lambda x[/tex]. Multiply by A to obtain
[tex] A^{2}x=\lambda Ax=>x=\lambda^{2}x[/tex]
So for this to hold [tex]\lambda =\pm 1[/tex]
In order to compute the third part, you have two equations, one coming from the determinant equation and the other one coming from the trace equation.
 
Just wondering, so my answers in part a and b is wrong then? No one has mentioned it yet so I'm not sure... I know that part b is wrong now, that det(A) = -1 instead of 1 ?

Tim,

If A is 2x2 and not I or -I, then det(A) = -1 right? I still don't get how to get from that point to the third though. I still get 1/3 when I use det(A) = -1 to solve the diagonal matrix equation:
Sorry for being so dumb... :frown:

hunt_mat
Wouldn't it be A2x = [tex]\lambda^{2}[/tex]x instead?
I tried using the trace equation. The thing is, the trace equation brings in the two [tex]\lambda[/tex] into the equation and adds significant complexity when I'm computing the eigenvectors.
 
From the question, we know that A^2 =I. One thing which you may not know is that you can diagonalise a matrix via the eigenvectors. So the determinant is just the product of the eigenvalues, hence det(A)=(+1)(-1)=1. Off the top of my head, I think that the tr(A) is given by the sum of the eigenvalues, so tr(A)=0. Write you matrix as:
[tex] A=\left(\begin{array}{cc}<br /> -3 & 1 \\<br /> x & y <br /> \end{array}\right)[/tex]
Use the two equations which I mentioned to obtain your solution.
 
KIDRoach said:
Just wondering, so my answers in part a and b is wrong then? No one has mentioned it yet so I'm not sure... I know that part b is wrong now, that det(A) = -1 instead of 1 ?
Yes, they're wrong. Hunt_mat showed you that the eigenvalues have to be +1 or -1. So think about how A looks in the basis where it's been diagonalized. There are only four possible matrices.

Wouldn't it be A2x = [tex]\lambda^{2}[/tex]x instead?
I tried using the trace equation. The thing is, the trace equation brings in the two [tex]\lambda[/tex] into the equation and adds significant complexity when I'm computing the eigenvectors.
Remember that A2=I, so no more A's on the lefthand side.
 

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