Matrices, Proof and Eigenvalues.

In summary, I am looking for help with the proof for my homework, but I made a mistake and need to fix it. Somebody in class mentioned imaginary numbers, but I'm unsure as to how to proceed.
  • #1
chris_avfc
85
0

Homework Statement



Looking for some help with the proof if possible.

Vector r =
x
y
z

Rotation R =
cos(θ) 0 sin(θ)
0 1 0
-sin(θ) 0 cos(θ)

r' = Rr

It asks me to prove that
r'.r' = r.r




Second part of the question is about eigenvalues, it asks me to find the three eigenvalues of R.
I used the formula
det(m - λI)

Where m = R, λ = the eigenvalues and I is the appropriate identity matrix

I end up with λ = cos() or 1, which is clearly wrong as there isn't enough answers.
Somebody in class mentioned imaginary numbers, but I'm unsure as to how to proceed.


The Attempt at a Solution



First Part:

I found r' to be
xcos(θ) + xsinθ
y
-zsin(θ) + xcos(θ)

To get r'.r' am I right to just multiply two of the above together, as in
(xcos(θ) + xsin(θ))(xcos(θ) + xsin(θ))
(yy)
(-zsin(θ) + xcos(θ))(-zsin(θ) + xcos(θ))

Because this is the way I did it and it doesn't lead to the same answer.

Obviously these should all have big brackets around them, but I am unsure of how to represent them on here, if someone would advise me I would gladly fix that.

Second Part:
I used the formula
det(m - λI)

Where m = R, λ = the eigenvalues and I is the appropriate identity matrix

I end up with λ = cos() or 1, which is clearly wrong as there isn't enough answers.
Somebody in class mentioned imaginary numbers, but I'm unsure as to how to proceed.
 
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  • #2
chris_avfc said:

Homework Statement



Looking for some help with the proof if possible.

Vector r =
x
y
z

Rotation R =
cos(θ) 0 sin(θ)
0 1 0
-sin(θ) 0 cos(θ)

r' = Rr

It asks me to prove that
r'.r' = r.r

Second part of the question is about eigenvalues, it asks me to find the three eigenvalues of R.
I used the formula
det(m - λI)

Where m = R, λ = the eigenvalues and I is the appropriate identity matrix

I end up with λ = cos() or 1, which is clearly wrong as there isn't enough answers.
Somebody in class mentioned imaginary numbers, but I'm unsure as to how to proceed.

The Attempt at a Solution



First Part:

I found r' to be
xcos(θ) + xsinθ
This is incorrect but I expect it is a typo.

y
-zsin(θ) + xcos(θ)

To get r'.r' am I right to just multiply two of the above together, as in
(xcos(θ) + xsin(θ))(xcos(θ) + xsin(θ))
(yy)
(-zsin(θ) + xcos(θ))(-zsin(θ) + xcos(θ))
Because I did it this way and it doesn't lead to the same answer.
Yes, that is what you want to do- and add them. You need to fix that first coordinate of course. What did you get? Don't forget that [itex]cos^2(\theta)+ sin^2(\theta)= 1[/itex].

Obviously these should all have big brackets around them, but I am unsure of how to represent them on here, if someone would advise me I would gladly fix that.

Second Part:
I used the formula
det(m - λI)

Where m = R, λ = the eigenvalues and I is the appropriate identity matrix

I end up with λ = cos() or 1, which is clearly wrong as there isn't enough answers.
Somebody in class mentioned imaginary numbers, but I'm unsure as to how to proceed.
We're not mindreaders! No one can tell you what you did wrong unless you tell us what you did!
 
  • #3
HallsofIvy said:
This is incorrect but I expect it is a typo.
Yes, that is what you want to do- and add them. You need to fix that first coordinate of course. What did you get? Don't forget that [itex]cos^2(\theta)+ sin^2(\theta)= 1[/itex]. We're not mindreaders! No one can tell you what you did wrong unless you tell us what you did!

What's wrong with the first bit, have I made a stupid mistake?

I've attached what I have done.
 

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  • #4
You have [itex]det(A-\lambda I)= (cos(\theta)- \lambda)(1- \lambda)(cos(\theta)- \lambda)[/itex] which is wrong. That is the product of the values on the main diagonal but is not the determinant.
 
  • #5
HallsofIvy said:
You have [itex]det(A-\lambda I)= (cos(\theta)- \lambda)(1- \lambda)(cos(\theta)- \lambda)[/itex] which is wrong. That is the product of the values on the main diagonal but is not the determinant.

Ah yeah, I've sorted that all out now.
Thank you so much for the help mate.
 

FAQ: Matrices, Proof and Eigenvalues.

What are matrices and how are they used in science?

Matrices are rectangular arrays of numbers or symbols that are used to represent mathematical and scientific data. They are commonly used in fields such as physics, statistics, and computer science to organize and manipulate data for analysis and modeling.

What is the purpose of using proofs in scientific research?

Proofs are used in scientific research to provide logical and mathematical evidence for a hypothesis or theory. They are often used to validate the results of experiments and to support scientific claims.

How are eigenvalues and eigenvectors used in data analysis?

Eigenvalues and eigenvectors are used in data analysis to identify the most important components of a dataset. They are used in techniques such as principal component analysis (PCA) to reduce the dimensionality of a dataset and find patterns in the data.

Can you provide an example of a real-world application of matrices, proofs, and eigenvalues?

One example of real-world application of these concepts is in image and signal processing. Matrices are used to represent images and signals, proofs are used to validate the algorithms used for processing and analysis, and eigenvalues are used in techniques such as image compression and noise reduction.

How do eigenvalues and eigenvectors relate to each other?

Eigenvalues and eigenvectors are closely related, as eigenvectors are the vectors that do not change direction when multiplied by a corresponding eigenvalue. In other words, an eigenvector is a vector that remains in the same direction, but may be scaled by a certain factor (eigenvalue) when multiplied by a matrix.

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