Orthogonal Matrices: Questions & Answers

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Homework Help Overview

The discussion revolves around properties of orthogonal matrices, specifically whether rearranging the rows of a square orthogonal matrix preserves its orthogonality and the relationship between a matrix's determinant and its orthogonality.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the implications of rearranging rows of an orthogonal matrix and question whether this affects its orthogonality. They also discuss the validity of a statement regarding the determinant of a matrix and its orthogonality, with some providing counter-examples to challenge the assertion.

Discussion Status

Participants are actively engaging with the concepts, providing counter-examples and clarifying definitions. There is acknowledgment of the need for careful language and logical reasoning in the discussion.

Contextual Notes

Some participants reference external sources for definitions and properties, indicating a reliance on established mathematical literature. There is a mention of the importance of linear independence in the context of orthogonal matrices.

war485
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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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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.
 
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. :)
 
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!
 
Yea, you're right Unco. I need to work on my logic a bit more. I'm very grateful for your help :D
 

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