How do I find the eigenvalue given unknown rows & eigen vect

In summary, the conversation discusses finding the eigenvalue of a matrix A given that x is an eigenvector. The conversation also briefly touches on the concept of eigenvectors and the process of finding the roots of the characteristic equation.
  • #1
Razberryz
22
0

Homework Statement


Consider the following matrix A (whose 2nd and 3rd rows are not given), and vector x.

A =
4 4 2
* * *
* * *
x =
2
-1
10

Given that x is an eigenvector of the matrix A, what is the corresponding eigenvalue?

Homework Equations

The Attempt at a Solution



4−λ 4 2
a b−λ c
d e f−λ=

det (λI3-3) =

−λ3+b+f+4×λ2+4×a−4×b+2×d+c×e−b×f−4×f×λ+−2×b×d+4×c×d+2×a×e−4×c×e−4×a×f+4×b×f

Don't know if I'm on the right track. Trying to find the roots of this characteristic equation, but there's so many unknowns.
 
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  • #3
fresh_42 said:
What is a eigenvector?
An eigenvector of A is a non-zero vector x such that Ax = λx
 
  • #5
fresh_42 said:
So. Have you already computed Ax?
Yes

24 a2-b+c10 d2-e+f10
 
  • #6
Razberryz said:
Yes

24 a2-b+c10 d2-e+f10
I have 5 minutes left to answer the question. Would you mind helping me with the answer, and then you can explain it to me?
 
  • #7
Razberryz said:
Yes

24 a2-b+c10 d2-e+f10
I assume, this should be a column vector. Now what says the equation ##Ax = \lambda x## in the first coordinate?
 
  • #8
fresh_42 said:
I assume, this should be a column vector. Now what says the equation ##Ax = \lambda x## in the first coordinate?

Sorry? You mean 24?
 
  • #9
I got it! Thanks!
 
  • #10
I mean the first coordinate is 24 on the left and ##\lambda x_1## on the right, yes.
 
  • #11
fresh_42 said:
I mean the first coordinate is 24 on the left and ##\lambda x_1## on the right, yes.
I figured it out, thanks a bunch!
 

1. How do I find the eigenvalues given unknown rows and eigen vectors?

To find the eigenvalues, you can use the characteristic polynomial of the matrix. Set the determinant of the matrix minus lambda times the identity matrix equal to zero and solve for lambda. The resulting values of lambda will be the eigenvalues.

2. Is there a specific formula for finding eigenvalues?

Yes, there is a formula for finding the eigenvalues. It is the characteristic polynomial, det(A-lambda*I) = 0, where A is the matrix and I is the identity matrix. Solving this equation will give you the eigenvalues of the matrix.

3. Can I find the eigenvalues without knowing the rows and eigen vectors?

No, it is not possible to find the eigenvalues without knowing the rows and eigen vectors. The eigenvalues are dependent on the matrix, and without any information about the matrix, it is not possible to determine the eigenvalues.

4. How do I use the eigenvalues to find the eigen vectors?

The eigenvalues can be used to find the eigen vectors by solving the equation (A-lambda*I)x=0, where A is the matrix and I is the identity matrix. The resulting non-zero vectors will be the eigen vectors corresponding to the given eigenvalues.

5. Are there any methods or techniques for finding the eigenvalues?

Yes, there are various methods for finding the eigenvalues, such as the characteristic polynomial method, the power method, and the QR method. Each method has its advantages and disadvantages, and the choice of method depends on the properties of the matrix.

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