Orthogonal Matrices: Questions & Answers

In summary, if you get a square orthogonal matrix, then you can make a new one by rearranging its rows, but it's not necessarily orthogonal.
  • #1
war485
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0

Homework Statement



1. If I got a square orthogonal matrix, then if I make up a new matrix from that by rearranging its rows, then will it also be orthogonal?

2. True/false: a square matrix is orthogonal if and only if its determinant is equal to + or - 1

Homework Equations



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The Attempt at a Solution



1. I think it should also be orthogonal since it forms a basis, and the basis would be the same, but just a linear combination of the previous, right?

2. false, its determinant doesn't necessarily ensure it is orthogonal. So, how would/should I correct that statement?
 
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  • #3
war485 said:
1. If I got a square orthogonal matrix, then if I make up a new matrix from that by rearranging its rows, then will it also be orthogonal?

1. I think it should also be orthogonal since it forms a basis, and the basis would be the same, but just a linear combination of the previous, right?
An nxn matrix is orthogonal iff its rows form an orthormal basis for [tex]\mathbb{R}^n[/tex] (note the symmetry of [tex]AA^T=A^TA=I[/tex] for an orthogonal matrix A). The linear independence of a collection of vectors doesn't depend on the order in which you write them, so the rows of the new matrix still form an orthonormal basis.

Just be careful your language: a linear combination of a basis reads as a linear combination of its vectors, which gives just one vector.
 
  • #4
I forgot about the linear independence part of it for #1.

As for #2, I took a counter-example from wikipedia XD
[ 2 0 ]
[ 0 0.5 ]
where its determinant = 1
but the length of each column is not 1 (not orthonormal)
I guess counter-examples should be enough?

Thanks for the help you two. :)
 
  • #5
war485 said:
As for #2, I took a counter-example from wikipedia XD
[ 2 0 ]
[ 0 0.5 ]
where its determinant = 1
but the length of each column is not 1 (not orthonormal)
I guess counter-examples should be enough?
The statement #2 is (colloquially) of the form "(property X implies property Y) AND (property Y implies property X)" (*). If all you want to do is show that (*) is false (e.g., if you were asked to prove or disprove the statement), then it suffices to show that property Y does not imply property X.

To show that property Y does not imply property X, it suffices to give an example for which property Y holds but X does not. Why? Because it definitively answers the question as to whether Y implies X. There is no guessing about it!
 
  • #6
Yea, you're right Unco. I need to work on my logic a bit more. I'm very grateful for your help :D
 

FAQ: Orthogonal Matrices: Questions & Answers

What is an orthogonal matrix?

An orthogonal matrix is a square matrix in which all the columns and rows are perpendicular to each other. This means that the dot product of any two distinct columns or rows is equal to zero.

What are some properties of orthogonal matrices?

Some properties of orthogonal matrices include:

  • They have an inverse that is equal to their transpose.
  • They preserve the length of vectors under multiplication.
  • They preserve angles between vectors under multiplication.

How can orthogonal matrices be used in applications?

Orthogonal matrices are commonly used in linear algebra and geometry. They can be used to transform vectors and matrices, perform rotations, and solve systems of linear equations.

Are all orthogonal matrices also symmetric?

No, not all orthogonal matrices are symmetric. While symmetric matrices are also orthogonal, the inverse of a symmetric matrix is not always equal to its transpose.

How are orthogonal matrices related to the concept of orthonormal basis?

An orthonormal basis is a set of vectors that are orthogonal to each other and have a length of 1. Orthogonal matrices can be used to transform a standard basis into an orthonormal basis, making it easier to perform calculations and solve problems in linear algebra.

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