Difference between revisions of "031 Review Part 3, Problem 3"

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<span class="exam">(b) Is the matrix &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; diagonalizable? Explain.
 
<span class="exam">(b) Is the matrix &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; diagonalizable? Explain.
 
  
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
 
{| class="mw-collapsible mw-collapsed" style = "text-align:left;"
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|Now, to find a basis for the eigenspace corresponding to &nbsp;<math style="vertical-align: -4px">5,</math>&nbsp; we need to solve &nbsp;<math style="vertical-align: -5px">(A-5I)\vec{x}=\vec{0}.</math>
 
|Now, to find a basis for the eigenspace corresponding to &nbsp;<math style="vertical-align: -4px">5,</math>&nbsp; we need to solve &nbsp;<math style="vertical-align: -5px">(A-5I)\vec{x}=\vec{0}.</math>
 
|-
 
|-
|To do this, we use row reduction. Thus, we get
+
|We have
 
|-
 
|-
 
|&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
 
|&nbsp; &nbsp; &nbsp; &nbsp;<math>\begin{array}{rcl}
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         \end{bmatrix}}\\
 
         \end{bmatrix}}\\
 
&&\\
 
&&\\
& \sim & \displaystyle{\begin{bmatrix}
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& = & \displaystyle{\begin{bmatrix}
 
           0 & 1 \\
 
           0 & 1 \\
 
           0 & 0  
 
           0 & 0  
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!Step 1: &nbsp;  
 
!Step 1: &nbsp;  
 
|-
 
|-
|
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|From part (a), we know that &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; only has one linearly independent eigenvector.
 
|}
 
|}
  
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!Step 2: &nbsp;
 
!Step 2: &nbsp;
 
|-
 
|-
|
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|By the Diagonalization Theorem, &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; must have &nbsp;<math style="vertical-align: 0px">2</math>&nbsp; linearly independent eigenvectors to be diagonalizable.
 +
|-
 +
|Hence, &nbsp;<math style="vertical-align: 0px">A</math>&nbsp; is not diagonalizable.
 
|}
 
|}
  
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|-
 
|-
|&nbsp;&nbsp; '''(b)''' &nbsp; &nbsp;  
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|&nbsp;&nbsp; '''(b)''' &nbsp; &nbsp; <math style="vertical-align: 0px">A</math>&nbsp; is not diagonalizable.
 
|}
 
|}
[[031_Review_Part_3|'''<u>Return to Sample Exam</u>''']]
+
[[031_Review_Part_3|'''<u>Return to Review Problems</u>''']]

Latest revision as of 13:54, 15 October 2017

Let  

(a) Find a basis for the eigenspace(s) of  

(b) Is the matrix    diagonalizable? Explain.

Foundations:  
Recall:
1. The eigenvalues of a triangular matrix are the entries on the diagonal.
2. By the Diagonalization Theorem, an    matrix    is diagonalizable
if and only if    has    linearly independent eigenvectors.


Solution:

(a)

Step 1:  
Since    is a triangular matrix, the eigenvalues are the entries on the diagonal.
Hence, the only eigenvalue of    is  
Step 2:  
Now, to find a basis for the eigenspace corresponding to    we need to solve  
We have
       
Solving this system, we see    is a free variable and  
Therefore, a basis for this eigenspace is

(b)

Step 1:  
From part (a), we know that    only has one linearly independent eigenvector.
Step 2:  
By the Diagonalization Theorem,    must have    linearly independent eigenvectors to be diagonalizable.
Hence,    is not diagonalizable.


Final Answer:  
   (a)     The only eigenvalue of    is    and the corresponding eigenspace has basis  
   (b)       is not diagonalizable.

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