Please help with this matrix question Solve for Eigenvales, and Eigenvectors

In summary, the eigenvalues for the given matrix M are λ1 = (a+b) + sqrt{(a-b)2 +c 2}/2 λ2 = (a+b) - sqrt{(a-b)2 + c2}/2.
  • #1
sidinsky
6
1
M = (a c)
(c b)

Sorry for the double sets of brackets, its all in one. I'll also show as far as i got below:

[a-λ c] => (a-λ)(b-λ) - c^2 = λ^2 + (-a-b)λ + (ab-c^2) =0
[c b-λ] =>

then using the quadratic formula: λ = [-(-a-b) +/- Sqrt{(-a-b)^2 - 4(1)(ab-c^2)}]/ 2

then after some algebra I got stuck: λ = [(a+b) +/- Sqrt{a^2 + 2ab + b^2 -4ac^2}]/2

λ = [(a+b) +/- Sqrt{a^2 - 2ab + b^2 + c^2}]/2 ==>> THIS IS WHERE I GOT STUCK. PLEASE HELP
 
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  • #2
welcome to pf!

hi sidinsky! welcome to pf! :wink:

(have a square-root: √ and a ± and try using the X2 button just above the Reply box :wink:)
sidinsky said:
λ = [(a+b) +/- Sqrt{a^2 - 2ab + b^2 + c^2}]/2

looks ok :smile:

that gives you the two eigenvalues,

so now use the standard techniques to find an eigenvector for each :wink:
 
  • #3
is there any way this expression can be simplified further? I am sort of having trouble with the algebra :S
 
  • #4
sidinsky said:
is there any way this expression can be simplified further?

i don't think so

how far have you got?​
 
  • #5
well I managed to clean up the expression inside the sqrt a bit to: [(a-b)2 + c 2 ]/2

a2 -2ab + b2 + c2 = (a-b)2 + c2

λ1 = (a+b) + sqrt{(a-b)2 +c 2}[itex]/2[/itex]

and λ2 = (a+b) - sqrt{(a-b)2 + c2}[itex]/2[/itex]

now these expressions for Lambda are too difficult for me to use to solve for eigenvectors
 

1. What is an Eigenvector and Eigenvalue?

An Eigenvector is a vector that, when multiplied by a square matrix, results in a scaled version of itself. The corresponding scaling factor is known as the Eigenvalue.

2. Why do we need to solve for Eigenvectors and Eigenvalues?

Eigenvectors and Eigenvalues are important in understanding the behavior of a system or matrix. They provide valuable information about the direction and magnitude of transformations and can be used to simplify complex calculations.

3. How do you find Eigenvectors and Eigenvalues?

To find Eigenvectors and Eigenvalues, you need to solve the characteristic equation of the matrix. This involves subtracting the Eigenvalue from the main diagonal of the matrix and taking the determinant. The resulting equation can be solved to find the Eigenvalues, which can then be used to find the corresponding Eigenvectors.

4. What are some real-world applications of Eigenvectors and Eigenvalues?

Eigenvectors and Eigenvalues have various applications in fields such as physics, engineering, and data analysis. They are used to study the behavior of mechanical systems, analyze data in machine learning algorithms, and understand the properties of quantum systems, among others.

5. Are Eigenvectors and Eigenvalues always unique?

No, Eigenvectors and Eigenvalues are not always unique. The number of unique Eigenvectors and Eigenvalues depends on the dimensionality of the matrix and the algebraic multiplicity of the Eigenvalues. In some cases, there may be repeated Eigenvalues and corresponding Eigenvectors.

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