Amanda's question at Yahoo Answers (Eigenvalues and eigenvectors)

  • Context: MHB 
  • Thread starter Thread starter Fernando Revilla
  • Start date Start date
  • Tags Tags
    Eigenvectors
Click For Summary
SUMMARY

The discussion revolves around finding eigenvectors corresponding to the eigenvalue λ = -1 for the matrix A defined as:
0 1 1
1 0 1
1 1 0.
The eigenvectors derived from the calculations are (-1, 1, 0) and (-1, 0, 1). The process involves using transformations and determinants to establish the characteristic polynomial, resulting in the eigenvalues λ = 2 (simple) and λ = -1 (double). The basis for the eigenspace corresponding to λ = -1 is confirmed to be two-dimensional.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with matrix operations and transformations
  • Knowledge of determinants and characteristic polynomials
  • Experience with linear algebra concepts
NEXT STEPS
  • Study the process of finding eigenvalues using the characteristic polynomial
  • Learn about the geometric interpretation of eigenvectors in linear transformations
  • Explore the implications of simple and double eigenvalues on eigenspaces
  • Investigate matrix diagonalization and its applications in solving linear systems
USEFUL FOR

Students and professionals in mathematics, particularly those focusing on linear algebra, as well as educators seeking to clarify concepts related to eigenvalues and eigenvectors.

Fernando Revilla
Gold Member
MHB
Messages
631
Reaction score
0
Here is the question:

So, I'm attempting to work on this question:

Given that matrix A =
0 1 1
1 0 1
1 1 0

and has λ = -1 as one of its eigenvalues, find the corresponding eigenvectors.

The answers are
-1
1
0

and

-1
0
1

BUT.. I don't understand how they got that because can't you bring it down to the reduced form of
1 0 0
0 1 0
0 0 1

So how do you get the corresponding eigenvalues from that? I'm so confused! Help please :)

Here is a link to the question:

How to I find corresponding eigenvectors? - Yahoo! Answers

I have posted a link there to this topic so the OP can find my response.
 
Physics news on Phys.org
Hello Amanda,

I don't understand either how they got those eigenvalues, surely is a typo. Using the transformations $R_2\to R_2-R_1$, $R_3\to R_3-R_1$ and $C_1\to C_1+C_2+C_3$ we get: $$\begin{aligned}
\begin{vmatrix}{-\lambda}&{\;\;1}&{\;\;1}\\{\;\;1}&{-\lambda}&{\;\;1}\\{\;\;1}&{\;\;1}&{-\lambda}\end{vmatrix}&=\begin{vmatrix}{-\lambda}&{\;\;1}&{\;\;1}\\{\;\;1+\lambda}&{-\lambda}-1&{\;\;0}\\{\;\;1+\lambda}&{\;\;0}&{-\lambda-1}\end{vmatrix}\\&=\begin{vmatrix}{-\lambda+2}&{\;\;1}&{\;\;1}\\{\;\;0}&{-\lambda}-1&{\;\;0}\\{\;\;0}&{\;\;0}&{-\lambda-1}\end{vmatrix}\\&=(-\lambda+2)(\lambda+1)^2=0\\&\Leftrightarrow \lambda=2\mbox{ (simple) }\vee \;\lambda=-1\mbox{ (double) }
\end{aligned}$$ The eigenvectors are: $$\ker (A-2I)\equiv \left \{ \begin{matrix}-2x_1+x_2+x_3=0\\x_1-2x_2+x_3=0\\x_1+x_2-2x_3=0\end{matrix}\right. $$ As $\lambda=2$ is simple, $\dim(\ker(A-2I))=1$ and easily we find a basis of this eigenspace: $B_2=\{(1,1,1)\}$. On the other hand: $$\ker (A+I)\equiv \left \{ \begin{matrix}x_1+x_2+x_3=0\\x_1+x_2+x_3=0\\x_1+x_2+x_3=0\end{matrix}\right.$$ Now, $\dim(\ker(A+I))=3-\mbox{rank }(A+I)=3-1=2$ and easily we find a basis of this eigenspace: $B_{-1}=\{(-1,1,0),(-1,0,1)\}$.
 

Similar threads

  • · Replies 33 ·
2
Replies
33
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 12 ·
Replies
12
Views
2K
  • · Replies 13 ·
Replies
13
Views
3K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
4K
  • · Replies 16 ·
Replies
16
Views
2K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 1 ·
Replies
1
Views
4K