Finding Orthogonal Matrices: 2 Solutions and Help

In summary, the two matrices are rotational, and the first matrix has a constraint in the left top corner that must be met to solve for the second matrix.
  • #1
Poetria
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Homework Statement
Find four distinct orthogonal 2x2 matrices, each of which has top-left entry equal to ##-\frac {1} {\sqrt{2}}##
Relevant Equations
Definition of an orthogonal matrix:
##M^T=M^{-1}##
I have found two such matrices:

##\begin{pmatrix} -cos( \frac {\pi} {4}) & sin(\frac {\pi} {4})\\ sin(\frac {\pi} {4}) & cos(\frac {\pi} {4})\end{pmatrix}####\begin{pmatrix} -cos( \frac {\pi} {4}) & -sin(\frac {\pi} {4})\\ -sin(\frac {\pi} {4}) & cos(\frac {\pi} {4})\end{pmatrix}##

Any hint how to find the other two? I have tried several solutions but all of them were wrong.
 
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  • #2
Poetria said:
I have found two such matrices
How ?
Poetria said:
Any hint how to find the other two?
Do the explicit matrix multiplication and solve the equations ...

##\ ##
 
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  • #3
Oh, ok, I will try. Many thanks. :)

The first matrix is a rotational one: it's easy if you know its properties. The determinant is -1.
Then I have changed the signs of both sines and verified if the second matrix is orthogonal.
BvU said:
How ?

Do the explicit matrix multiplication and solve the equations ...

##\ ##
 
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  • #4
Poetria said:
The first matrix is a rotational one
You sure ? I thought those have determinant 1 ...

##\ ##
 
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  • #5
BvU said:
You sure ? I thought those have determinant 1 ...

##\ ##
Of course, I am wrong. I confused it with this one:

##\begin{pmatrix} cos(\pi/4) & -sin(\pi/4)\\ sin(\pi/4) & cos(\pi/4)\\\end{pmatrix}##

Anyway a rotational matrix was my point of departure. But I needed a negative cos(pi/4) in the top left corner.
 
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  • #6
Poetria said:
Any hint how to find the other two? I have tried several solutions but all of them were wrong.
I think you need to reflect a little more.
 
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  • #7
PeroK said:
I think you need to reflect a little more.
I think so. I will get to the bottom of it sooner or later. :)
 
  • #8
Well, I have studied the definition of the orthogonal matrix:
https://mathworld.wolfram.com/OrthogonalMatrix.html
"The rows of an orthogonal matrix are an orthonormal basis. That is, each row has length one, and are mutually perpendicular."

There is a constraint: -1/sqrt(2) in the left top corner of the matrix.
So I have
## \sqrt {(-\frac {1} {\sqrt(2)})^{2}+x^{2}} =1##
##x= \frac {1} {\sqrt(2)}## v ##x= -\frac {1} {\sqrt(2)}##

There are two possibilities for the first row:
##\begin{pmatrix} -\frac {1} {\sqrt(2)} & \frac {1} {\sqrt(2)}\end{pmatrix}##
##\begin{pmatrix} -\frac {1} {\sqrt(2)} & -\frac {1} {\sqrt(2)}\end{pmatrix}##

The dot product of the first and second row has to be equal to zero.

vector (-1/sqrt(2), 1/sqrt(2)) dot vector (y, z) = 0

##\frac {z} {\sqrt(2)} - \frac {y} {\sqrt(2)}=0##

Therefore y=z.
But the length of the second row must be 1.
Therefore ##y=\frac {1} {\sqrt(2)}## v ##y=-\frac {1} {\sqrt(2)}##

The only thing I could do to obtain other matrices is change ##\theta##, e.g. instead of ##\sin(\frac{\pi} {4})## give ##\sin(\frac{9*\pi} {4})## but it's the same numerically.
 
  • #9
Not all orthogonal matrices are rotations. In fact, only two are rotations. The others involve rotations and a reflection.

Or, you can simply work through the options for ##\pm \frac 1 {\sqrt 2}## in each entry. That gives 8 possibilities with minus in the first entry to check.
 
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  • #10
Wow. :) I got it. :) Wonderful. Many thanks :)
 
  • #11
Poetria said:
Wow. :) I got it. :) Wonderful. Many thanks :)
A bit of quiet reflection was all it needed!
 
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1. What is an orthogonal matrix?

An orthogonal matrix is a square matrix in which all the rows and columns are orthogonal to each other. This means that the dot product of any two rows or columns is equal to 0, making the matrix a special type of matrix that preserves the length and angles of vectors.

2. Why are orthogonal matrices important?

Orthogonal matrices are important because they have many useful properties that make them useful in various fields such as mathematics, physics, and computer science. They are used in solving systems of linear equations, transforming coordinates, and in data compression techniques.

3. How do you find orthogonal matrices?

There are several methods for finding orthogonal matrices. One way is to use the Gram-Schmidt process, which involves orthogonalizing a set of linearly independent vectors. Another method is to use the QR decomposition, which decomposes a matrix into an orthogonal matrix and an upper triangular matrix.

4. Can a matrix have more than one orthogonal matrix?

Yes, a matrix can have more than one orthogonal matrix. This is because there are infinitely many ways to create an orthogonal matrix from a given matrix. For example, if you have an orthogonal matrix A, then multiplying it by any other orthogonal matrix B will also result in an orthogonal matrix.

5. How can I check if a matrix is orthogonal?

To check if a matrix is orthogonal, you can use the transpose and inverse properties. If the transpose of the matrix is equal to its inverse, then the matrix is orthogonal. You can also check if all the rows and columns are orthogonal to each other by calculating the dot product. If all the dot products are equal to 0, then the matrix is orthogonal.

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