Eigenvalues and Normalised Eigenvectors

AI Thread Summary
The discussion revolves around finding the eigenvalues and normalized eigenvectors of the matrix H = [h g; g h]. The eigenvalues calculated are λ = h ± g, derived from the determinant equation. The corresponding eigenvectors are identified as (1, 1) for λ = h + g and (1, -1) for λ = h - g. However, neither eigenvector is normalized, as their lengths are √2, not unit length. Normalization requires scaling these vectors to have a length of 1.
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Homework Statement


I have a matrix
H= [h g
g h]
and I need to find the eigenvalues and normalised eigenvectors


Homework Equations





The Attempt at a Solution


I subtracted lamda from the diagonal and then solved for the determinant equally zero. The eigenvalues I found were
(h-lambda)^2=g^2
so (h-lambda)=+/- g
lamdba=h+/-g

but I'm not sure how to find the normalised eigenvectors?
 
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After finding the eigenvalues, plug them back into the equation (A - λ I)x = 0, one by one, to get your eigenvectors. Then normalize them.
 
Thank you very much.

So what I have done is
for eigenvalue h+g I have two equations
hx+gy=hx+gx and gx+hy = hy+gy which gives x=y so eigenvalue h+g has eigenvector (1,1)
and for eigenvalue h-g I have two equations
hx+gy=hx-gx and hx+gy=hy-gy so x=-y so eigenvalue h-g has eigenvector (1,-1)

Is that correct?
 
are these normalised?
 
What does it mean for a vector to be normalized?
 
to be of unit length...which these are right?
 
I am not going to check your calculations, but with respect to the standard norm neither (1, 1) nor (1, -1) have unit length, since |(1, 1)|=(|(1, -1)|) = √2.
 
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