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

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    Eigenvectors
In summary: Therefore $A$ has two linearly independent eigenvectors corresponding to the eigenvalue $\lambda=-1$. In summary, the matrix $A$ with the eigenvalue $\lambda=-1$ has the corresponding eigenvectors $(-1,1,0)$ and $(-1,0,1)$.
  • #1
Fernando Revilla
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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.
 
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  • #2
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: $B_{-1}=\{(-1,1,0),(-1,0,1)\}$.
 

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

1. What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are mathematical concepts used in linear algebra to describe the behavior of a linear transformation or matrix. An eigenvector is a vector that when multiplied by a given matrix results in a scalar multiple of itself, called an eigenvalue.

2. How are eigenvalues and eigenvectors used?

Eigenvalues and eigenvectors have many applications in various fields, including physics, engineering, and computer science. They are used to study the behavior of systems, analyze data, and solve differential equations.

3. What is the importance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are important because they simplify complicated systems and allow us to understand their behavior in a more manageable way. They also help us identify key features of a system and make predictions about its future behavior.

4. How do you calculate eigenvalues and eigenvectors?

The process of calculating eigenvalues and eigenvectors involves finding the characteristic polynomial of a matrix and solving for its roots. This can be done by hand using techniques such as the characteristic equation or by using specialized software.

5. Can eigenvalues and eigenvectors have complex values?

Yes, eigenvalues and eigenvectors can have complex values. In fact, complex eigenvalues and eigenvectors are often encountered in real-world applications, especially in quantum mechanics and signal processing.

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