Finding an orthonormal basis of V

In summary, the conversation involves finding an orthonormal basis for a finite-dimensional vector space of 2 x 2 matrices with real entries. The dimensions of the vector space and the definition of an inner product using a real-valued function are stated without proof. It is shown that the inner product defined is valid and that certain types of matrices are orthogonal under this inner product. The conversation then discusses finding an orthonormal basis for the vector space and possible methods for deducing it from the previous steps. It is ultimately suggested to use the standard basis and show that the inner product yields 0 for non-equal matrices and 1 for equal matrices in order to find the desired orthonormal basis.
  • #1
Unredeemed
120
0
I've done most of this question apart from the very last bit. I have an answer to the very last bit, but it doesn't use any of my previously proved statements and I think they probably mean me to deduce from what I already have.

Homework Statement


Let V be the finite-dimensional vector space of 2 x 2 matrices with real entries.

State, without proof, the dimension of V as a real vector space. (done)

A real-valued function V x V is defined by:

<A|B> = tr((A^t)B) where A^t is the transpose of the matrix A.

Show that <A|B> defines an inner product on V. (done)

Show that, with respect to this inner product, any symmetric matrix is orthogonal to any antisymmetric matrix, and that the identity matrix is orthogonal to any matrix whose trace is zero. (done)

Find an orthonormal basis of V. (bit I can't do)


Homework Equations





The Attempt at a Solution



I thought I could just write down:

\begin{equation}
\begin{pmatrix}
1 & 0 \\
0 & 1
\end{pmatrix}
\end{equation}
\begin{equation}
\begin{pmatrix}
1 & 0 \\
0 & -1
\end{pmatrix}
\end{equation}
\begin{equation}
\begin{pmatrix}
0 & -1 \\
1 & 0
\end{pmatrix}
\end{equation}
\begin{equation}
\begin{pmatrix}
0 & 1 \\
1 & 0
\end{pmatrix}
\end{equation}

And then show that it's an orthonormal basis. But, this obviously doesn't use what I've already proved. How can I deduce it from what I already have?

Cheers.
 
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  • #2
Why do you have to deduce it from the previous steps? And note that, while your examples are orthogonal, they aren't orthonormal, although that's easy to fix. What about the four matrices like this one$$
\begin{pmatrix} 1 & 0\\0 & 0\end{pmatrix}$$which might be slightly easier to show are a basis.
 
  • #3
Unredeemed said:
And then show that it's an orthonormal basis. But, this obviously doesn't use what I've already proved. How can I deduce it from what I already have?
But you will need to use the function you showed was an inner product to show your choice of matrices form an orthonormal basis. Plus it looks like you already did use some of what you proved in choosing those matrices.
 
  • #4
LCKurtz said:
Why do you have to deduce it from the previous steps? And note that, while your examples are orthogonal, they aren't orthonormal, although that's easy to fix. What about the four matrices like this one$$
\begin{pmatrix} 1 & 0\\0 & 0\end{pmatrix}$$which might be slightly easier to show are a basis.

Oh yeah, good point, they are only orthogonal.

vela said:
But you will need to use the function you showed was an inner product to show your choice of matrices form an orthonormal basis. Plus it looks like you already did use some of what you proved in choosing those matrices.

So, as LCKurtz suggested, I should just use the standard basis for V and show that <A|B>=0 for A≠B and 1 for A=B?
 
  • #5
Unredeemed said:
Oh yeah, good point, they are only orthogonal.



So, as LCKurtz suggested, I should just use the standard basis for V and show that <A|B>=0 for A≠B and 1 for A=B?

Yes. Although your original matrices can be normalized to work too.
 

Related to Finding an orthonormal basis of V

1. What is an orthonormal basis?

An orthonormal basis is a set of vectors in a vector space V that are both orthogonal (perpendicular) and normalized (unit length). This means that the dot product of any two vectors in the basis is equal to 0, and the length of each vector is equal to 1.

2. Why is finding an orthonormal basis important?

Finding an orthonormal basis is important because it simplifies many calculations in linear algebra. It allows for easier computation of inner products, projections, and distances between vectors. Additionally, it is a useful tool in solving systems of linear equations and in diagonalizing matrices.

3. How do you find an orthonormal basis of a vector space V?

To find an orthonormal basis of a vector space V, you can use the Gram-Schmidt process. This involves taking a set of linearly independent vectors in V and applying a series of orthogonalization and normalization steps to them. The resulting set of vectors will form an orthonormal basis for V.

4. Can any vector space have an orthonormal basis?

No, not all vector spaces have an orthonormal basis. For a vector space to have an orthonormal basis, it must have a finite or countably infinite dimension. In other words, it must have a basis with a finite or countably infinite number of vectors. Additionally, the inner product of the vector space must be defined.

5. Are orthonormal bases unique?

Yes, orthonormal bases are unique. This means that any two orthonormal bases of the same vector space will have the same number of vectors and the same vectors, up to a permutation and scaling of the vectors. This is because the Gram-Schmidt process produces a unique orthonormal basis for a given set of linearly independent vectors.

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