Solving Eigenvectors for Root -7 of 2x3 Matrix

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SUMMARY

The discussion centers on finding the eigenvector for the eigenvalue -7 of the 2x2 matrix |2 3| |3 -6|. The user initially calculated the eigenvector as (1, -3), while the reference book states it as (-1, 3). It is established that both answers are valid since any scalar multiple of an eigenvector is also an eigenvector corresponding to the same eigenvalue. Thus, the signs do not affect the correctness of the eigenvector, confirming that eigenvectors are not unique.

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Homework Statement



Find eigenvector for the root -7 of:

|2 3|
|3 -6|

Homework Equations



|2 3|
|3 -6|

The Attempt at a Solution



I got
1
-3

But my books says
-1
3

I am only wondering if this is possibly the same answer, because when I check my answer by multiplying the eigenvector by the original matrix and the root by the eigenvector the answer appears correct.

I.e.
|2 3|
|3 -6| times (1/-3) = (-7)(1/-3) = -7/21, while if you do the same for (-1/3), allbeit a different answer, but the condition still holds.

Is this correct? Is this condition truly the indicator of if you got the correct answer? (original vector * eigenvector) = (root * eigenvector)
 
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Yes, any "eigenvector", v, corresponding to a given eigenvalue (I would not say "root") \lambda, of matrix A, has the property that Av= \lambda v.

What you are missing is that if v is such an eigenvector then av, for any number a, is also an eigenvector, corresponding to eigenvalue \lambda: A(av)= a (Av)= a(\lambda v)= \lambda (av).

In particular, with a= -1, if v is an eigenvalue then so is -v. The eigenvector is NOT unique.
 
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HallsofIvy said:
Yes, any "eigenvector", v, corresponding to a given eigenvalue (I would not say "root") \lambda, of matrix A, has the property that Av= \lambda v.

What you are missing is that if v is such an eigenvector then av, for any number a, is also an eigenvector, corresponding to eigenvalue \lambda: A(av)= a (Av)= a(\lambda v)= \lambda (av).

In particular, with a= -1, if v is an eigenvalue then so is -v. The eigenvector is NOT unique.

Thanks a lot.

Just to confirm, the signs in this case do not matter and both answers are correct? I am such a noobie...
 
Last edited:

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