Eigenvalue/vector and similar matrices

  • Thread starter A_lilah
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In summary, to find a matrix B such that B^2 = A, we can use the similar matrices rule and find the diagonal matrix D with eigenvalues of A and the matrix X with corresponding eigenvectors. By taking the square root of the diagonal elements of D and using X*D^(1/2)*X^-1, we can find B. However, it is important to consider all rows when finding eigenvectors and be careful when dealing with zero eigenvalues.
  • #1
A_lilah
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Homework Statement


Find a matrix B such that B^2 = A

A = 3x3 =

9 -5 3
0 4 3
0 0 1

Homework Equations



B^2 = A

A = XDX^(-1) (similar matrices rule)

also used to find eigenvectors: A - λI

The Attempt at a Solution



Thoughts: If A = XDX^(-1), then B^2 = XDX(-1), and B = X * D^(1/2) * X^-1
So, if I could find D and X for A, I could find B. D = diagonal matrix where the diagonal elements are the eigenvalues of A, and A is lower triangular, so it's eigenvalues are:

λ1 = 9, λ2 = 4, λ3 = 1,

so D = 3x3 =

9 0 0
0 4 0
0 0 1

To find X, I need the eigenvectors:

A-9I =
0 -5 3
0 -5 3
0 0 -8
so (-5)v2 + (3)v3 = 0, or v2 = (3/5)v3
and the eigenvector (representative) = [0 1 3/5]^T

I suspect there is something wrong here because my bottom row in A-9I isn't all 0 and I think it is supposed to be... I don't know what I did wrong though.

For the other eigenvalues, I got eigenvectors that were:

λ2 = 4,
[1 1 0]^T

λ3 = 1
[1 1 -1]

X = 3x3 =

0 1 1
1 1 1
(3/5) 0 -1

X^-1 =
-1 1 0
(8/5) (-3/5) 1
(-3/5) (3/5) -1

To get D^(1/2) I square-rooted the diagonal elements:
3 0 0
0 2 0
0 0 1

Then find X * D^(1/2) * X^-1, which = B, but when I square B, it doesn't = A...
Any input would be great! Thanks
 
Last edited:
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  • #2
A_lilah said:
Find a matrix B such that B^2 = A

A = 3x3 =

9 -5 3
0 4 3
0 0 1

Hi A_lilah! :smile:

Hint: is the square of a triangular matrix triangular?

if so, what happens to the diagonal elements? :wink:
 
  • #3
A_lilah said:

Homework Statement


Find a matrix B such that B^2 = A

A = 3x3 =

9 -5 3
0 4 3
0 0 1

Homework Equations



B^2 = A

A = XDX^(-1) (similar matrices rule)

also used to find eigenvectors: A - λI

The Attempt at a Solution



Thoughts: If A = XDX^(-1), then B^2 = XDX(-1), and B = X * D^(1/2) * X^-1
So, if I could find D and X for A, I could find B. D = diagonal matrix where the diagonal elements are the eigenvalues of A, and A is lower triangular, so it's eigenvalues are:

λ1 = 9, λ2 = 4, λ3 = 1,

so D = 3x3 =

9 0 0
0 4 0
0 0 1

To find X, I need the eigenvectors:

A-9I =
0 -5 3
0 -5 3
0 0 -8
so (-5)v2 + (3)v3 = 0, or v2 = (3/5)v3
and the eigenvector (representative) = [0 1 3/5]^T
You've completely ignored the third row: -8v3= 0 so v3= 0. Yes, the second row then gives v2= (3/5)v3 and since v3= 0, v2= 0. Now the important point: the fact that the first column is 0 does NOT mean that v1= 0! It says there is NO CONDITION on v1. With v2= v3= 0, 0v1-5v2+ 3v3= 0, 0v1- 5v2+ 3v3= 0, and 0v1+ 0v2- 8v3= 0 are true for ALL VALUES of v3: [1, 0, 0]^T is an eigenvector.

I suspect there is something wrong here because my bottom row in A-9I isn't all 0 and I think it is supposed to be... I don't know what I did wrong though.

For the other eigenvalues, I got eigenvectors that were:

λ2 = 4,
[1 1 0]^T
yes, this is correct.

λ3 = 1
[1 1 -1]
Did you check it?
[tex]\left[\begin{array}{ccc}9 & -5 & 3 \\ 0 & 4 & 3 \\ 0 & 0 & 1\end{array}\right]\left[\begin{array}{c}1 \\ 1 \\ 1\end{array}\right]= \left[\begin{array}{c} 7 \\ 7 \\ 1\end{array}\right][/tex]
No, that is not [1 1 -1]^T again.

For eigenvalue 1, you get the three equations 8v1- 5v2+ 3v3= 0, 3v2+ 3v3= 0, and 0= 0. The last equations says that v3 can be anything. From the second equation, 3v2= -3v3 so v2= -v3 and, putting that into the first equation, 8v1+ 5v3+ 3v3= 0, v1= -v3. You can write down the eigenvector corresponding to eigenvalue 1 from that.

X = 3x3 =

0 1 1
1 1 1
(3/5) 0 -1

X^-1 =
-1 1 0
(8/5) (-3/5) 1
(-3/5) (3/5) -1

To get D^(1/2) I square-rooted the diagonal elements:
3 0 0
0 2 0
0 0 1

Then find X * D^(1/2) * X^-1, which = B, but when I square B, it doesn't = A...
Any input would be great! Thanks
 
Last edited by a moderator:
  • #4
Thank you both so much! Of course I should have looked at the other rows ~ silly of me. Thanks again :)
 

Related to Eigenvalue/vector and similar matrices

1. What is an eigenvalue and eigenvector?

An eigenvalue is a scalar value that represents the amount by which an eigenvector is scaled when multiplied by a matrix. An eigenvector is a vector that remains in the same direction after being multiplied by a matrix.

2. Why are eigenvalues and eigenvectors important?

Eigenvalues and eigenvectors are important because they provide a way to understand the behavior and properties of a matrix. They are used in a variety of applications, such as solving systems of linear differential equations and in data analysis and machine learning.

3. How are eigenvalues and eigenvectors calculated?

Eigenvalues and eigenvectors can be calculated using various methods, such as the characteristic polynomial method or the power iteration method. These calculations can be done by hand or using computer algorithms.

4. Can similar matrices have different eigenvalues?

Yes, similar matrices can have different eigenvalues. Similar matrices have the same eigenvalues if and only if they have the same determinant, trace, and rank.

5. How are eigenvalues and eigenvectors used in data analysis?

Eigenvalues and eigenvectors are used in data analysis to reduce the dimensionality of a dataset, which helps to identify the most important features or patterns in the data. This process is known as principal component analysis (PCA) and is used in fields such as image and signal processing, finance, and genetics.

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