Proving a matrix is orthogonal

I'll mark this as closed.In summary, the problem statement is unclear and does not provide enough information to determine if the matrix is orthogonal. The provided equations do not lead to a solution and the attempted solution is based on incorrect assumptions. Further clarification from the professor is needed to properly address the problem.
  • #1
member 428835

Homework Statement


Show that the matrix ##P = \big{[} p_{ij} \big{]}## is orthogonal.

Homework Equations


##P \vec{v} = \vec{v}'## where each vector is in ##\mathbb{R}^3## and ##P## is a ##3 \times 3## matrix. SO I guess ##P## is a transformation matrix taking ##\vec{v}## to ##\vec{v}'##. I also know ##\vec{v} = v_i \hat{e}_i## where ##\hat{e}_i## is the ##i##th unit vector.

The Attempt at a Solution


Orthogonal implies ##P P^t = I##. ##P P^t## can be wrote in component form as ##p_{ij} p_{ji}##. I believe I want to show that ##p_{ij} p_{ji} = \delta_{ij}##. After this I'm not really sure how to proceed. Any ideas?
 
Physics news on Phys.org
  • #2
joshmccraney said:
pijpji=δijp_{ij} p_{ji} = \delta_{ij}.
Hi josh:

The quoted equation is wrong. You want something similar in which you show the index over which you do the sum required in multiplying a row of P by column of Pt.

joshmccraney said:
I'm not really sure how to proceed.
From your problem statement, I am guessing that you were not given a particular matrix you had to show is orthogonal, but rather show a method you can use to show that any given orthogonal matrix is in fact orthogonal. If that is the case, I think your attempted solution (with the correction) is all you need.
Hope this helps,

Regards,
Buzz
 
  • #3
Thanks for taking time to reply Buzz! But when you say

Buzz Bloom said:
Hi josh:
The quoted equation is wrong.
I don't think I wrote what you quoted? I didn't multiply ##\delta_{ij}## by ##p##. Perhaps you quoted me while I was editing? But I do agree what I wrote was wrong.

Buzz Bloom said:
You want something similar in which you show the index over which you do the sum required in multiplying a row of P by column of Pt.

Ok, so to demonstrate ##P## is orthogonal would we have to show ##p_{ki}p_{kj} = \delta_{ij}##?

And yea, come to think of it I do think ##P## is a general matrix.
 
  • #4
joshmccraney said:

Homework Statement


Show that the matrix ##P = \big{[} p_{ij} \big{]}## is orthogonal.

Homework Equations


##P \vec{v} = \vec{v}'## where each vector is in ##\mathbb{R}^3## and ##P## is a ##3 \times 3## matrix. SO I guess ##P## is a transformation matrix taking ##\vec{v}## to ##\vec{v}'##. I also know ##\vec{v} = v_i \hat{e}_i## where ##\hat{e}_i## is the ##i##th unit vector.
I'm confused as to what is the actual problem. Did you put part of the problem statement in the relevant equations? If not, the problem statement, as written, is false.
An arbitrary matrix is not orthogonal.

Also, what does this mean -- ##\vec{v} = v_i \hat{e}_i##? In the context of vectors in ##\mathbb{R}^3##, it would make more sense to write ##\vec{v} = v_1 \hat{e}_1 + v_2 \hat{e}_2 + v_3\hat{e}_3##
joshmccraney said:

The Attempt at a Solution


Orthogonal implies ##P P^t = I##. ##P P^t## can be wrote in component form as ##p_{ij} p_{ji}##. I believe I want to show that ##p_{ij} p_{ji} = \delta_{ij}##. After this I'm not really sure how to proceed. Any ideas?
 
  • #5
Mark44 said:
I'm confused as to what is the actual problem. Did you put part of the problem statement in the relevant equations?
Yes I did, I'm sorry about that!

Mark44 said:
Also, what does this mean -- ##\vec{v} = v_i \hat{e}_i##? In the context of vectors in ##\mathbb{R}^3##, it would make more sense to write ##\vec{v} = v_1 \hat{e}_1 + v_2 \hat{e}_2 + v_3\hat{e}_3##
I was using Einstein notation, so it means exactly the sum that you wrote in the end.
 
  • #6
Mark44 said:
Also, what does this mean -- ##\vec{v} = v_i \hat{e}_i##? In the context of vectors in ##\mathbb{R}^3##, it would make more sense to write ##\vec{v} = v_1 \hat{e}_1 + v_2 \hat{e}_2 + v_3\hat{e}_3##
joshmccraney said:
I was using Einstein notation, so it means exactly the sum that you wrote in the end.
Wouldn't the right side be shown in brackets, like this?
##[ v_i \hat{e}_i]##
This is similar to the shorthand notation ##[p_{ij}]## that you used in the OP to represent all of the entries of matrix P.

In any case, what is the exact problem statement? From what you've provided so far, I don't see how one can show that an arbitrary matrix is orthogonal.
 
  • #7
Mark44 said:
I'm confused as to what is the actual problem.
This was also given, but I didn't include it because it seemed like it was of no help:

If a vector ##\vec{v}## has coordinates ##v_i## with respect to a basis ##\vec{e_i}## , the transformation rule will tell us the coordinates of the same vector ##\vec{v}## with respect to a different basis ##\vec{e_i}'## . Let ##v_i'## denote the coordinates of ##\vec{v}## with respect to ##\vec{e_i}'##. Our goal is to find the transformation rule governing ##v_i'## and ##v_i##.

Since ##\vec{e_i}## is a basis, it is possible to find a unique set of 9 numbers, ##p_{ij}## such that ##\vec{e_i}' = p_{ij}\vec{e_j}##.
 
  • #8
Mark44 said:
In any case, what is the exact problem statement? From what you've provided so far, I don't see how one can show that an arbitrary matrix is orthogonal.
I have posted the notes that correspond to ##P##.
 
  • #9
From post #1:
joshmccraney said:
Orthogonal implies ##P P^t = I##.
This also implies that ##P^{-1} = P^t##.

Maybe I'm missing something, but I don't see anything in the problem description that would lead me to believe that the matrix is orthogonal. You have Pv = v', but you don't show anything about v', other than it is a vector in R3.
 
  • #10
Mark44 said:
From post #1: This also implies that ##P^{-1} = P^t##.

Maybe I'm missing something, but I don't see anything in the problem description that would lead me to believe that the matrix is orthogonal. You have Pv = v', but you don't show anything about v', other than it is a vector in R3.
I totally agree. To me it looks as though we are given a square ##3 \times 3## matrix and asked to show this property is true. I'll ask the professor about it, I just wanted to see if anyone else picked up on something I did not. Thanks for your help Mark44!
 

FAQ: Proving a matrix is orthogonal

What does it mean for a matrix to be orthogonal?

An orthogonal matrix is a square matrix whose columns and rows are orthonormal, meaning they are perpendicular to each other and have a length of 1. This results in a matrix where the dot product of any two columns (or rows) is equal to 0.

How can I prove that a matrix is orthogonal?

To prove that a matrix is orthogonal, you can use several methods such as showing that the dot product of any two columns (or rows) is equal to 0, or that the inverse of the matrix is equal to its transpose. Additionally, you can also use the Gram-Schmidt process to show that the columns (or rows) of the matrix are orthonormal.

What is the significance of an orthogonal matrix?

Orthogonal matrices have many applications in mathematics and science, such as in geometric transformations, solving linear systems of equations, and in computer graphics and engineering. They also have special properties that make them useful in calculations and proofs.

Can a non-square matrix be orthogonal?

No, a non-square matrix cannot be orthogonal. Orthogonality is a property that only applies to square matrices, where the number of rows is equal to the number of columns. Non-square matrices can have orthogonal columns or rows, but they cannot be considered orthogonal matrices.

How can I use orthogonality to simplify matrix operations?

Orthogonality can be used to simplify matrix operations in several ways. For example, if two matrices are orthogonal, their product will also be orthogonal. This can be helpful in solving systems of equations or in finding eigenvalues and eigenvectors. Additionally, orthogonal matrices have special properties that allow for efficient and accurate calculations, making them useful in various applications.

Similar threads

Replies
11
Views
721
Replies
6
Views
780
Replies
4
Views
821
Replies
3
Views
898
Replies
6
Views
3K
Replies
13
Views
2K
Replies
9
Views
1K
Back
Top