Learn How to Find Eigenvalues of 3x3 Matrices | Eigenvalue Algorithm Explained

  • Thread starter sciencegirl1
  • Start date
  • Tags
    Eigenvalues
In summary, you need to solve the equation -A- \lambda I=0 for eigenvalues. Polynomial long division can help you with this.
  • #1
sciencegirl1
30
0

Homework Statement



find the eigenvalues of 3x3 matrix:

I have to learn how to find eigenvalues of 3x3 matrix

and this is the link, am I not supposed to do lamda-1 instead of 1-lamda like here?
http://en.wikipedia.org/wiki/Eigenvalue_algorithm
(the chapter name is "Eigenvalues of 3×3 matrices")


is there any simpler rule?
 
Physics news on Phys.org
  • #2
Sadly, no simple rules.

For eigenvalues, you're solving the following equation for [itex]\lambda[/itex].
A[itex]\lambda[/itex] = [itex]\lambda[/itex]x
or equivalently,
(A - [itex]\lambda[/itex]I)x = 0

For the equation above to be true for arbitrary x (which turn out to be the eigenvectors),
(A - [itex]\lambda[/itex]I) has to be singular, which means that its determinant must be zero.
 
  • #3
A= ( -1 -2 -2;
1 2 1;
-1 -1 0)

this is the matrix

I don´t understand how to get the eigenvalues which are supposed to be -1 1 1
because when I calculate it with the wikipedia rule I get -lamda^3+lamda^2-3lamda+1 and that does not make sense to me.
 
  • #4
You're taking the determinant of A - [itex]\lambda[/itex]I and setting it to zero, so you'll have a cubic polynomial in [itex]\lambda[/itex] that is equal to zero.
You need to solve for [itex]\lambda[/itex] in that polynomial.
 
  • #5
What do you mean? :confused:
 
  • #6
Which part of what I said don't you understand?
 
  • #7
so you'll have a cubic polynomial in LaTeX Code: \\lambda that is equal to zero.
You need to solve for LaTeX Code: \\lambda in that polynomial.

can you show me?
 
  • #8
Here's the equation you need to solve:
[tex]-\lambda^3+\lambda^2-3\lambda+1 = 0[/tex]

I haven't checked your work, so it's possible that this isn't the right equation.

If ([itex]\lambda - a[/itex]) is a factor, a has to be a divisor of 1, which severely limits the possibilities for a. By divisor, I mean a has to go into 1 a whole number of times.

Use polynomial long division to work this out. Once you get one factor, you'll be left with a quadratic in lambda, which should be pretty easy to factor or use the quadratic formula on.
 
  • #9
thanks for your help
i just don´t know how to solve it :( I´be been trying but is there any rule for solving equations like this or...?
 
  • #10
Let me say it again.
Use polynomial long division to work this out. Once you get one factor, you'll be left with a quadratic in lambda, which should be pretty easy to factor or use the quadratic formula on.
Didn't you learn about polynomial long division back when you took elementary or intermediate algebra?
 
  • #11
sciencegirl1 said:
A= ( -1 -2 -2;
1 2 1;
-1 -1 0)

this is the matrix

I don´t understand how to get the eigenvalues which are supposed to be -1 1 1
because when I calculate it with the wikipedia rule I get -lamda^3+lamda^2-3lamda+1 and that does not make sense to me.

It may be worth looking at your determinant calculation again as well, very easy to make a miscalulation in those steps.

if you know the eigenvalues are -1, 1, 1 the you should be able to factorise the determinant in term of these... so try subsitituting 1 or -1 into
[tex] -\lambda^3+\lambda^2-3\lambda+1=0[/tex]
ie
[tex] -(1)^3+(1)^2-3.(1)+1=-2\neq 0[/tex]
which makes me think something may have gone wrong in the det calc

and then
[tex] -\lambda^3+\lambda^2-3\lambda+1 \neq (\lambda-1)^2(\lambda+1) [/tex]
 
  • #12
Your matrix is
[tex]A= \begin{bmatrix} -1 & -2 & -2 \\ 1 & 2 & 1 \\ -1 & -1 & 0\end{bmatrix}[/tex]

So the characteristic equation is
[tex]|A- \lambda I|= \left|\begin{array}{ccc}-1- \lambda & -2 & -2 \\ 1 & 2- \lambda & 1 \\ -1 & -1 & -\lambda\end{array}\right|= 0[/tex]
expanding, on, say, the first row, that is
[tex](-1-\lambda)\left|\begin{array}{cc}2-\lambda 1 \\ -1 & -\lambda\end{array}\right|+ 2\left|\begin{array}{cc}1 & 1 \\ -1 & -\lambda\end{array}\right|+ 2\left|\begin{array}{cc}1 & 2-\lambda \\ -1 & -1\end{array}\right|[/tex]
[tex]= (-1-\lambda)(\lambda^2- 2\lambda+ 1)+ 2(-\lambda+ 1)-2(1-\lambda)[/tex]
[tex]= -(1+\lambda)(\lambda- 1)^2- 2(\lambda-1)+ 2(\lambda-1)[/tex]
and, in that form, it is obvious that the last two terms cancel leaving the already factored form
[tex]-(\lambda+ 1)(\lambda- 1)^2[/tex]
 
  • #13
When you are learning all this keep in mind that no-one actually solves the characteristic polynomial to find eigenvalues in real-world problems. This is mostly useful for small toy problems, or to gain understanding of the theory.

For real problems you would use something like the QR algorithm or the Arnoldi iteration.
 
  • #15
Thanks a lot everybody!
 

FAQ: Learn How to Find Eigenvalues of 3x3 Matrices | Eigenvalue Algorithm Explained

What are eigenvalues?

Eigenvalues are a special set of numbers that are associated with a square matrix. They represent the values of the matrix that, when multiplied by a vector, result in a scalar multiple of that same vector.

How do eigenvalues relate to eigenvectors?

Eigenvectors are the corresponding vectors to eigenvalues. They represent the direction in which the matrix is scaled by the eigenvalue. The eigenvector associated with the largest eigenvalue is known as the dominant eigenvector.

Why are eigenvalues important?

Eigenvalues have many important applications in mathematics, engineering, and science. They are used to solve systems of differential equations and to analyze complex systems in physics and engineering.

How do you find eigenvalues?

To find the eigenvalues of a matrix, you must first find the determinant of the matrix. Then, you can solve for the eigenvalues using various methods such as the characteristic polynomial or Gaussian elimination.

What do eigenvalues tell us about a matrix?

Eigenvalues provide important information about a matrix, such as its stability and the behavior of the system it represents. They can also be used to determine the rank, trace, and determinant of a matrix.

Back
Top