Find two linearly independent eigenvectors for eigenvalue 1

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Homework Help Overview

The discussion revolves around finding two linearly independent eigenvectors for the eigenvalue 1 of a given matrix A. The matrix is specified, and it is noted that the eigenvalue 1 has a multiplicity of 2.

Discussion Character

  • Exploratory, Assumption checking

Approaches and Questions Raised

  • Participants describe their attempts to solve for eigenvectors by manipulating an augmented matrix. There is a comparison of results between the original poster's findings and those in a textbook, leading to questions about the nature of the eigenvectors derived.

Discussion Status

Some participants affirm the correctness of the original poster's eigenvectors, noting that they span the same subspace as those in the textbook. Others explore the differences in the approaches taken to arrive at the eigenvectors, indicating a productive exchange of ideas without reaching a definitive consensus.

Contextual Notes

There is mention of differing methods for solving the eigenvector equations, with one approach leading to different arbitrary variables compared to the textbook solution. This highlights the flexibility in the methods used to find eigenvectors.

Potatochip911
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Homework Statement


A linear transformation with Matrix A = ##
\begin{pmatrix}
5&4&2\\
4&5&2\\
2&2&2
\end{pmatrix} ## has eigenvalues 1 and 10. Find two linearly independent eigenvectors corresponding to the eigenvalue 1.

Homework Equations


3. The Attempt at a Solution [/B]
I know from the trace of matrix A that eigenvalue 1 has a multiplicity of 2 and that eigenvalue 10 has a multiplicity of 1. Solving for eigenvectors corresponding for ## \lambda = 1 ##, pretend it's an augmented matrix...
##
\begin{pmatrix}
4&4&2\\
4&4&2\\
2&2&1
\end{pmatrix}
R_2 ->R_2 - R_1;
R_3 ->R_3 - \dfrac{1}{2} \cdot R_2 =
\begin{pmatrix}
4&4&2\\
0&0&0\\
0&0&0
\end{pmatrix}
R_1-> \dfrac{1}{2} \cdot R_1 =
\begin{pmatrix}
2&2&1\\
0&0&0\\
0&0&0
\end{pmatrix}
##
Therefore ##x_2## and ##x_3## are arbitrary. Solving for ##x_1## gives $$x_1=-x_2-\dfrac{1}{2} x_3$$ $$x_2=x_2$$ $$x_3=x_3$$
$$v= \begin{pmatrix}
-x_2-\dfrac{1}{2} x_3\\
x_2\\
x_3
\end{pmatrix} $$
##v= x_2 \begin{pmatrix}
-1 \\
1 \\
0
\end{pmatrix} +
x_3 \begin{pmatrix}
-1 \\
0 \\
2
\end{pmatrix} ## Now those are the two eigenvectors I got however the answer in my book says the two eigenvectors are ##v_1=<1,0,-2>## and ##v_2=<0,1,-2>##
 
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Potatochip911 said:

Homework Statement


A linear transformation with Matrix A = ##
\begin{pmatrix}
5&4&2\\
4&5&2\\
2&2&2
\end{pmatrix} ## has eigenvalues 1 and 10. Find two linearly independent eigenvectors corresponding to the eigenvalue 1.

Homework Equations


3. The Attempt at a Solution [/B]
I know from the trace of matrix A that eigenvalue 1 has a multiplicity of 2 and that eigenvalue 10 has a multiplicity of 1. Solving for eigenvectors corresponding for ## \lambda = 1 ##, pretend it's an augmented matrix...
##
\begin{pmatrix}
4&4&2\\
4&4&2\\
2&2&1
\end{pmatrix}
R_2 ->R_2 - R_1;
R_3 ->R_3 - \dfrac{1}{2} \cdot R_2 =
\begin{pmatrix}
4&4&2\\
0&0&0\\
0&0&0
\end{pmatrix}
R_1-> \dfrac{1}{2} \cdot R_1 =
\begin{pmatrix}
2&2&1\\
0&0&0\\
0&0&0
\end{pmatrix}
##
Therefore ##x_2## and ##x_3## are arbitrary. Solving for ##x_1## gives $$x_1=-x_2-\dfrac{1}{2} x_3$$ $$x_2=x_2$$ $$x_3=x_3$$
$$v= \begin{pmatrix}
-x_2-\dfrac{1}{2} x_3\\
x_2\\
x_3
\end{pmatrix} $$
##v= x_2 \begin{pmatrix}
-1 \\
1 \\
0
\end{pmatrix} +
x_3 \begin{pmatrix}
-1 \\
0 \\
2
\end{pmatrix} ## Now those are the two eigenvectors I got however the answer in my book says the two eigenvectors are ##v_1=<1,0,-2>## and ##v_2=<0,1,-2>##
Your eigenvectors are correct, which I verified by multiplying them on the left by your matrix, with both multiplications resulting in 1 times the eigenvector.
The book's first eigenvector is the -1 multiple of your second eigenvector. Their second eigenvector is not a scalar multiple of your first eigenvector, but it still is an eigenvector associated with the eigenvalue 1. Your two vectors and the book's two vectors span the same two-dim. subspace of R3, so all is good.
 
Mark44 said:
Your eigenvectors are correct, which I verified by multiplying them on the left by your matrix, with both multiplications resulting in 1 times the eigenvector.
The book's first eigenvector is the -1 multiple of your second eigenvector. Their second eigenvector is not a scalar multiple of your first eigenvector, but it still is an eigenvector associated with the eigenvalue 1. Your two vectors and the book's two vectors span the same two-dim. subspace of R3, so all is good.
Okay thanks!
 
In the book's solution, they solved for ##x_3 = -2 x_1 -2 x_2##, so ##x_1## and ##x_2## ended up being arbitrary instead of ##x_2## and ##x_3## as in your case.
 
vela said:
In the book's solution, they solved for ##x_3 = -2 x_1 -2 x_2##, so ##x_1## and ##x_2## ended up being arbitrary instead of ##x_2## and ##x_3## as in your case.
Oh, so that's where they're getting that eigenvector from.
 

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