Eigenvalues and Eigenlines

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In summary, the conversation discusses finding the corresponding eigenline for a given matrix A. The equation k^2-(a+d)k+(ad-bc)=0 is used to solve for the eigenvalues, which are found to be k=2 and k=-3. These values are then substituted into the equations (3y=0 and 2x-7y=0 for k=2, and 5x-3y=0 and 2x-2y=0 for k=-3) to find the corresponding eigenvectors. The final solution is x=y/2.
  • #1
Justin90
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0
1.
Find the corresponding Eigenline

A= (3 -3 2 -4)



Homework Equations


A=(a b c d)
k2-(a+d)k+(ad-bc)=0


The Attempt at a Solution



k2-(3-(-4))k+(3(-4)-(-3)2)=0
k2+k-6=0
(k+2)(k-3)

So k=-2 and k=3

Eigenvector for k=3
(3 -3 2 -4)(x y) = 3(x y)
(3x -3y 2x -4y)= (3x 3y)

Hence 3y=0 and 2x-7y=0

Eigenvector for k=-2
(3 -3 2 -4)(x y) = -2(x y)
(3x -3y 2x -4y)=(-2x -2y)

Hence 5x-3y=0 and 2x-2y=0

This is where I get confused because my notes say that 3y=0 and 2x-7y=0 need to reduce to a single equation, and similarly 5x-3y=0 and 2x-2y=0 need to reduce to a single equation to give the eigenline for the given eigenvalue?
 
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  • #2
Justin90 said:
1.
Find the corresponding Eigenline

A= (3 -3 2 -4)


Do you mean [tex]
A = \begin{pmatrix} 3 & - 3 \\ 2 & -4 \end{pmatrix}[/tex]

Homework Equations


A=(a b c d)
k2-(a+d)k+(ad-bc)=0


The Attempt at a Solution



k2-(3-(-4))k+(3(-4)-(-3)2)=0
k2+k-6=0
(k+2)(k-3)

So k=-2 and k=3

Here is your problem: [tex](-2)^2 + (-2) - 6 = -4 \neq 0 \\
(3)^2 + 3 - 6 = 6 \neq 0[/tex] Therefore neither -2 nor 3 is an eigenvalue of [itex]A[/itex]. Try solving [itex]k^2 + k - 6 = 0[/itex] again.
 
  • #3
pasmith said:
Do you mean [texy/
A = \begin{pmatrix} 3 & - 3 \\ 2 & -4 \end{pmatrix}[/tex]


Here is your problem: [tex](-2)^2 + (-2) - 6 = -4 \neq 0 \\
(3)^2 + 3 - 6 = 6 \neq 0[/tex] Therefore neither -2 nor 3 is an eigenvalue of [itex]A[/itex]. Try solving [itex]k^2 + k - 6 = 0[/itex] again.

Thanks for that! Couldn't see the wood through the trees. Got it now.

K^2+k-6=0
(k-2)(k+3)=0
So k=2 and k=-3

So eventual both equations reduce to x=y/2

Can't believe I missed that.
 

1. What are eigenvalues and eigenvectors?

Eigenvalues and eigenvectors are mathematical concepts used in linear algebra. Eigenvalues represent the scaling factor of an eigenvector when multiplied by a linear transformation, while eigenvectors are the non-zero vectors that remain in the same direction after the transformation.

2. How are eigenvalues and eigenvectors used?

Eigenvalues and eigenvectors are commonly used in data analysis, signal processing, and engineering to understand the behavior of linear transformations and systems. They are also used in computer graphics to rotate and scale objects.

3. What is the importance of eigenvalues and eigenvectors?

Eigenvalues and eigenvectors play a crucial role in understanding the behavior of linear transformations and systems. They help in finding the dominant behavior of a system, which is useful in many applications such as in physics, engineering, and data analysis.

4. How can eigenvalues and eigenvectors be calculated?

The calculation of eigenvalues and eigenvectors involves finding the roots of a characteristic polynomial. This process can be done manually for small matrices, or through software programs for larger matrices. There are also various numerical methods for calculating eigenvalues and eigenvectors.

5. Can there be multiple eigenvalues and eigenvectors for a single matrix?

Yes, a matrix can have multiple eigenvalues and corresponding eigenvectors. However, the number of eigenvalues and eigenvectors is limited by the size of the matrix. For example, a 3x3 matrix can have at most 3 eigenvalues and 3 eigenvectors.

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