For 2 = -1, we found the eigenspace consists of solutions to the following. 20 2 0 0 0 0 0 0 0 0 0 Writing this as a system of equations gives 2x, + 2x3 = 0, or x, = ] )*3• Let x3 = s be the free variable in the equation. Also, note that x, = t is a free variable as it does not appear in the equations. Therefore, the set of solutions is given by the vector . Thus, the eigenvectors are of the form Find the spanning set for the eigenspace for 1 = -1. span
For 2 = -1, we found the eigenspace consists of solutions to the following. 20 2 0 0 0 0 0 0 0 0 0 Writing this as a system of equations gives 2x, + 2x3 = 0, or x, = ] )*3• Let x3 = s be the free variable in the equation. Also, note that x, = t is a free variable as it does not appear in the equations. Therefore, the set of solutions is given by the vector . Thus, the eigenvectors are of the form Find the spanning set for the eigenspace for 1 = -1. span
Algebra and Trigonometry (6th Edition)
6th Edition
ISBN:9780134463216
Author:Robert F. Blitzer
Publisher:Robert F. Blitzer
ChapterP: Prerequisites: Fundamental Concepts Of Algebra
Section: Chapter Questions
Problem 1MCCP: In Exercises 1-25, simplify the given expression or perform the indicated operation (and simplify,...
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![For \(\lambda = -1\), we found the eigenspace consists of solutions to the following:
\[
\begin{bmatrix}
2 & 0 & 2 & 0 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{bmatrix}
\]
Writing this as a system of equations gives \(2x_1 + 2x_3 = 0\), or \(x_1 = \left(\rule{20px}{0.5pt}\right)x_3\). Let \(x_3 = s\) be the free variable in the equation. Also, note that \(x_2 = t\) is a free variable as it does not appear in the equations.
Therefore, the set of solutions is given by the vector \(\begin{bmatrix} \left(\rule{20px}{0.5pt}\right)s \\ t \\ s \end{bmatrix}\). Thus, the eigenvectors are of the form
\[
s \begin{bmatrix} -1 \\ 0 \\ 1 \end{bmatrix} + t \begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix}.
\]
Find the spanning set for the eigenspace for \(\lambda = -1\).
\[
\text{span}\left(
\begin{bmatrix}
\rule{20px}{0.5pt} \\
\rule{20px}{0.5pt} \\
\rule{20px}{0.5pt}
\end{bmatrix}
\right)
\]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4b2b33db-c80f-4b0b-994f-adea14a053ac%2F9aee6a29-ea3a-448f-9c49-5baf498358be%2Fuiajseo_processed.jpeg&w=3840&q=75)
Transcribed Image Text:For \(\lambda = -1\), we found the eigenspace consists of solutions to the following:
\[
\begin{bmatrix}
2 & 0 & 2 & 0 \\
0 & 0 & 0 & 0 \\
0 & 0 & 0 & 0
\end{bmatrix}
\]
Writing this as a system of equations gives \(2x_1 + 2x_3 = 0\), or \(x_1 = \left(\rule{20px}{0.5pt}\right)x_3\). Let \(x_3 = s\) be the free variable in the equation. Also, note that \(x_2 = t\) is a free variable as it does not appear in the equations.
Therefore, the set of solutions is given by the vector \(\begin{bmatrix} \left(\rule{20px}{0.5pt}\right)s \\ t \\ s \end{bmatrix}\). Thus, the eigenvectors are of the form
\[
s \begin{bmatrix} -1 \\ 0 \\ 1 \end{bmatrix} + t \begin{bmatrix} 0 \\ 1 \\ 0 \end{bmatrix}.
\]
Find the spanning set for the eigenspace for \(\lambda = -1\).
\[
\text{span}\left(
\begin{bmatrix}
\rule{20px}{0.5pt} \\
\rule{20px}{0.5pt} \\
\rule{20px}{0.5pt}
\end{bmatrix}
\right)
\]
![Consider the following.
\[ A = \begin{bmatrix} 1 & 0 & 2 \\ 3 & -1 & 3 \\ 2 & 0 & 1 \end{bmatrix} \]
(a) Compute the characteristic polynomial of \( A \).
(b) Compute the eigenvalues and bases of the corresponding eigenspaces of \( A \).
(c) Compute the algebraic and geometric multiplicity of each eigenvalue.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4b2b33db-c80f-4b0b-994f-adea14a053ac%2F9aee6a29-ea3a-448f-9c49-5baf498358be%2F5eatnu_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Consider the following.
\[ A = \begin{bmatrix} 1 & 0 & 2 \\ 3 & -1 & 3 \\ 2 & 0 & 1 \end{bmatrix} \]
(a) Compute the characteristic polynomial of \( A \).
(b) Compute the eigenvalues and bases of the corresponding eigenspaces of \( A \).
(c) Compute the algebraic and geometric multiplicity of each eigenvalue.
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