Proving Orthonormal Basis for an Orthogonal Matrix

In summary, to prove that an n x n matrix A is orthogonal, you must show that the column vectors form an orthonormal basis for R^n with respect to the standard Euclidean inner product. To do this, you need to show that the column vectors are linearly independent and span R^n. This can be shown by assuming that the vectors v1, v2, ... vn form a basis and using the fact that c1*v1+c2*v2+...+cn*vn=0 only has the solution c1=c2=...=cn=0, which can be proven by using the dot product and the orthonormality of the vectors.
  • #1
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Homework Statement



Prove: if an n × n matrix A is orthogonal (column vectors are orthonormal), then the columns form an orthonormal basis for R^n.
(with respect to the standard Euclidean inner product [= the dot product]).

Homework Equations


None.


The Attempt at a Solution



I know that since the column vectors are orthonormal, all I have to show is that these vectors are also linearly independent and span R^n.

But I'm having some trouble showing this, so I was thinking about showing it through the basis coordinates:

u= <u, v1>v1 + <u, v2>v2 +...+ <u, vn>vn

But I think I have to start with assuming that the vectors v1, v2, ... vn form a basis. So I think that method can't work.
 
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  • #2
Linear independence is what you want to show. That means c1*v1+c2*v2+...+cn*vn=0 (where vi are your orthonormal vectors and the ci are constants) only has the solution c1=c2=...=cn=0. Can you show that? Once you have that, any set of n linearly independent vectors in R^n is a basis.
 
  • #3
I've been trying to figure out how, but I just can't seem to think of a way...anymore advice?
 
  • #4
You assume c1*v1+c2*v2+...+cn*vn=0. What is vi.(c1*v1+...+cn*vn)? '.'=dot product. Use orthonormality.
 

Related to Proving Orthonormal Basis for an Orthogonal Matrix

1. What is an orthonormal basis?

An orthonormal basis is a set of vectors that are mutually perpendicular (orthogonal) and have a magnitude of 1 (normalized). This means that the vectors are not only independent but also form a right angle with each other.

2. Why is it important to have an orthonormal basis?

Having an orthonormal basis allows for easy calculation and manipulation of vectors. It also simplifies the representation and analysis of geometric objects in higher-dimensional spaces.

3. How do you prove that a set of vectors forms an orthonormal basis?

To prove that a set of vectors forms an orthonormal basis, you need to show that they are orthogonal to each other and have a magnitude of 1. This can be done by calculating the dot product of each vector with the other vectors in the set and confirming that the result is 0 (orthogonal) and 1 (normalized).

4. Can a set of vectors form an orthonormal basis in any vector space?

No, a set of vectors can only form an orthonormal basis in a vector space that has an inner product defined. This means that the vector space is equipped with a binary operation that satisfies certain properties, such as the dot product in Euclidean space.

5. How is an orthonormal basis used in linear algebra?

In linear algebra, an orthonormal basis is used to decompose a vector into its component parts. This is known as the Gram-Schmidt process and is used to find an orthonormal basis for a given set of vectors. Orthonormal bases are also used in matrix transformations, such as rotation and reflection matrices.

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