Obtain an eigenvector corresponding to each eigenvalue

In summary, the linear operator T on R^2 with the matrix [4 -5; -4 3] relative to the basis {(1,2), (0,1)} has eigenvalues of 8 and -1. To find the eigenvectors, the equations AX = 8X and AX = -1X were used, resulting in the eigenvectors (-5,-6) and (1,3) respectively. The answers in the book are given in terms of the standard basis {(1,0), (0,1)}.
  • #1
jesuslovesu
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Homework Statement


The linear operator T on R^2 has the matrix [4 -5; -4 3]
relative to the basis { (1,2), (0,1) }

Find the eigenvalues of T.
Obtain an eigenvector corresponding to each eigenvalue.

Homework Equations


The Attempt at a Solution



I was able to find the eigenvalues (8 and -1) easily enough; however, I have not been able to find the eigenvectors. (I have a feeling it's due to a nonstandard basis being given.)

AX = 8X
AX = -1X

In the case of the first equation I get 4a - 5b = 8a; -4a + 3b = 8b so I would think an eigenvector could be (-5, 4) however my book says it should be (-5,-6). I believe this is because of the basis, but I really don't know what to do with it.
 
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  • #2
are you sure it is (-5,-6)? or did u write down the basis correctly? {(1,2),(0,1)}

EDIT: ok i think it is correct, my mistakes
 
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  • #3
Yep, according to my book the answer is (-5,-6) and the basis is correct, is the book wrong?
 
  • #4
is the eigenvector corresponding to evalue 1 is (1,3) according to book?
 
  • #5
yep.. I can see that (-5,4) -> -5(1,2) + 4(0,1) = (-5,-6)
is (-5,4) a coordinate matrix?
 
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  • #6
yes... but I can't pinpoint the cause of the problem in your method just yet...
 
  • #7
by the way, i believe the answers in the book is written in terms of the standard basis {(1,0), (0,1)}
 
  • #8
ok, previously I made two mistakes that confused myself
note: -5 (1,2) +4 (0,1) = (-5,-6)
and 1 (1,2) +1 (0,1) = (1,3)
 
  • #9
alright i think i can see it now, thanks
 

FAQ: Obtain an eigenvector corresponding to each eigenvalue

1. What is an eigenvector?

An eigenvector is a vector that does not change direction when multiplied by a certain matrix. It only changes in length, which is determined by its corresponding eigenvalue.

2. What does it mean to obtain an eigenvector corresponding to an eigenvalue?

To obtain an eigenvector corresponding to an eigenvalue means to find the vector that satisfies the equation Av = λv, where A is a square matrix, v is the eigenvector, and λ is the eigenvalue.

3. Why is it important to obtain eigenvectors and eigenvalues?

Eigenvectors and eigenvalues are important in a variety of fields, including physics, engineering, and data analysis. They can be used to study the behavior of linear systems, identify patterns in data, and solve differential equations.

4. How do you obtain an eigenvector corresponding to an eigenvalue?

To obtain an eigenvector corresponding to an eigenvalue, you can use various methods such as solving the characteristic equation, performing row reduction on the matrix, or using software programs like MATLAB or Mathematica.

5. Can a matrix have more than one eigenvector corresponding to the same eigenvalue?

Yes, it is possible for a matrix to have multiple eigenvectors corresponding to the same eigenvalue. In fact, the number of linearly independent eigenvectors for a given eigenvalue is called the geometric multiplicity of that eigenvalue.

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