Linear Algebra - Find Orthogonal Matrix Q that diagonals

In summary, the answer key for homework says that S = (1/3)... but I don't know where this 1/3 comes from. I get the same answer for X_1, X_2, and X_3 when I form this matrix with the values for X_1, X_2, X_3, but when I factor out a 1/3 I'm not able to. Does anyone know where this value comes from? I tried adding a common constant to the vector, but that didn't work.
  • #1
YoshiMoshi
228
8

Homework Statement


I'm told to find the matrix Q of the matrix A
equation 1.PNG


Homework Equations

The Attempt at a Solution



So my problem is that in the answer key they have S = (1/3)... and I have no idea where this 1/3 comes from. I get an equivalent answer for X_1, X_2, and X_3
S = [X_1, X_2, X_3] but when I form this matrix with the values for X_1, X_2, X_3 I'm not able to factor out a 1/3. Does anyone know where this value comes from?
This is the solutions

equation2.PNG

and this is my attempt, again I would get the same answer but have no idea were the 1/3 came from.
IMG_20160424_204918869.jpg

thanks for any help
 
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  • #2
An orthogonal matrix is a unitary matrix. Therefore ##Q^*Q = QQ^*=I##. This is why the vectors making up the column of ##Q## must be orthonormal - 1/3 is a normalization constant.
 
  • #3
How do I calculate this normalization constant? Thanks for your help. Like I'm exactly sure which vector I'm normalizing and getting 1/3. But I know to normalize a vector it's

V/||V||

Thanks for your help!
 
  • #4
A vector is said to be normalized if its norm equal unity.
 
  • #5
So it's just

1/sqrt((1+1+1)^2)?
 
  • #6
YoshiMoshi said:
1/sqrt((1+1+1)^2)?
I don't understand what you want to say there.
Suppose you have three component vectors ##u = (a,b,c)^T##. In order to make it normalized you have to add a common constant by yourself to the vector: ##u = \gamma (a,b,c)^T##. By requiring its norm to be equal to one, namely ##\gamma^2(|a|^2 + |b|^2 + |c|^2) = 1##. This way you can find ##\gamma## in terms of the components of ##u##. For a general unitary matrix, ##\gamma## can be complex but since here the problem asks for an orthogonal matrix, ##\gamma## must be real.
 
  • #7
Oh I see that makes more since to me know. So it's for the whole Matrix S? When I square all the terms in S and sum each row individually I get 9, so the constant must be 1/sqrt(9) = 1/3.

What if each row doesn't sum up to the same value like it did in this case?

Thanks for your help!
 
  • #8
Then you cannot pull the common normalization constant out of the matrix's bracket. Nothing wrong with that.
 
  • #9
ah ok thanks for your help
 

Related to Linear Algebra - Find Orthogonal Matrix Q that diagonals

1. What is a diagonal matrix in linear algebra?

A diagonal matrix is a special type of square matrix where all the elements outside the main diagonal (from top left to bottom right) are zero. The main diagonal consists of the elements of the matrix that are in the same row and column.

2. What is an orthogonal matrix?

An orthogonal matrix is a square matrix whose columns and rows are all orthogonal unit vectors. This means that the dot product of any two columns or rows of the matrix is equal to zero, and the norm (length) of each column or row is equal to one.

3. How do you find an orthogonal matrix Q?

To find an orthogonal matrix Q, you can use the Gram-Schmidt process or the QR decomposition method. In the Gram-Schmidt process, you take a set of linearly independent vectors and orthogonalize them to create an orthonormal set of vectors, which can then be used as the columns of your orthogonal matrix Q. In the QR decomposition method, you decompose your original matrix A into a product of an orthogonal matrix Q and an upper triangular matrix R.

4. Why is finding an orthogonal matrix Q useful?

Finding an orthogonal matrix Q is useful in many applications of linear algebra, such as solving systems of linear equations, finding eigenvalues and eigenvectors, and performing rotations and reflections in geometry. Orthogonal matrices also have the property of preserving angles and lengths, making them useful for transformations in many fields, including computer graphics and machine learning.

5. Can any matrix have an orthogonal matrix Q?

No, not all matrices have an orthogonal matrix Q. For a matrix to have an orthogonal matrix Q, it must be a square matrix with linearly independent columns or rows. Additionally, the matrix must also be invertible, meaning its determinant is non-zero. If a matrix does not meet these criteria, it will not have an orthogonal matrix Q.

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