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Section 5.4 Eigenvectors and Eigenspaces (GT4)

Subsection 5.4.1 Class Activities

Activity 5.4.1.

It's possible to show that \(-2\) is an eigenvalue for \(\left[\begin{array}{ccc}-1&4&-2\\2&-7&9\\3&0&4\end{array}\right]\text{.}\)

Compute the kernel of the transformation with standard matrix

\begin{equation*} A-(-2)I = \left[\begin{array}{ccc} \unknown & 4&-2 \\ 2 & \unknown & 9\\3&0&\unknown \end{array}\right] \end{equation*}

to find all the eigenvectors \(\vec x\) such that \(A\vec x=-2\vec x\text{.}\)

Definition 5.4.2.

Since the kernel of a linear map is a subspace of \(\IR^n\text{,}\) and the kernel obtained from \(A-\lambda I\) contains all the eigenvectors associated with \(\lambda\text{,}\) we call this kernel the eigenspace of \(A\) associated with \(\lambda\text{.}\)

Activity 5.4.3.

Find a basis for the eigenspace for the matrix \(\left[\begin{array}{ccc} 0 & 0 & 3 \\ 1 & 0 & -1 \\ 0 & 1 & 3 \end{array}\right]\) associated with the eigenvalue \(3\text{.}\)

Activity 5.4.4.

Find a basis for the eigenspace for the matrix \(\left[\begin{array}{cccc} 5 & -2 & 0 & 4 \\ 6 & -2 & 1 & 5 \\ -2 & 1 & 2 & -3 \\ 4 & 5 & -3 & 6 \end{array}\right]\) associated with the eigenvalue \(1\text{.}\)

Activity 5.4.5.

Find a basis for the eigenspace for the matrix \(\left[\begin{array}{cccc} 4 & 3 & 0 & 0 \\ 3 & 3 & 0 & 0 \\ 0 & 0 & 2 & 5 \\ 0 & 0 & 0 & 2 \end{array}\right]\) associated with the eigenvalue \(2\text{.}\)

Subsection 5.4.2 Videos

Figure 68. Video: Finding eigenvectors

Subsection 5.4.3 Slideshow

Slideshow of activities available at https://teambasedinquirylearning.github.io/linear-algebra/2022/GT4.slides.html.

Exercises 5.4.4 Exercises

Exercises available at https://teambasedinquirylearning.github.io/linear-algebra/2022/exercises/#/bank/GT4/.

Subsection 5.4.5 Mathematical Writing Explorations

Exploration 5.4.6.

Given a matrix \(A\text{,}\) let \(\{\vec{v_1},\vec{v_2},\ldots,\vec{v_n}\}\) be the eigenvectors with associated distinct eigenvalues \(\{\lambda_1,\lambda_2,\ldots, \lambda_n\}\text{.}\) Prove the set of eigenvectors is linearly independent.

Subsection 5.4.6 Sample Problem and Solution

Sample problem Example B.1.24.