Matrix Factorization: Spherical & Cartesian Vectors

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    Factorization Matrix
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Discussion Overview

The discussion revolves around the matrix that relates spherical unit vectors to Cartesian unit vectors, specifically examining whether this matrix can be factored into simpler matrices. The conversation includes technical aspects of matrix decomposition and transformations between coordinate systems.

Discussion Character

  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant presents a transformation matrix T relating spherical and Cartesian coordinates and asks if it can be factored into simpler matrices.
  • Another participant asserts that the matrix cannot be simplified, expressing uncertainty about the direction of the original question.
  • A different participant suggests that there are multiple ways to decompose the matrix, proposing a method involving rotations and questioning the ordering of the output coordinates.
  • One participant mentions LU factorization as a potential method for solving the matrix but argues that certain entries will prevent it from being reduced to row echelon form, suggesting the use of trigonometric identities instead.
  • A repeated point emphasizes the challenges of reducing the matrix due to specific entries that cannot be simplified.

Areas of Agreement / Disagreement

Participants express differing views on the possibility of simplifying the matrix. While some suggest that it cannot be simplified, others propose alternative decomposition methods, indicating that the discussion remains unresolved.

Contextual Notes

There are assumptions regarding the ordering of angles and the right-handedness of the coordinate systems that are not fully clarified. The discussion also highlights the limitations of certain mathematical techniques in this context.

psholtz
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The matrix giving the relation between spherical (unit) vectors and cartesian (unit) vectors can be expressed as:

[tex]\left( \begin{array}{c} \hat{r} \\ \hat{\phi} \\ \hat{\theta} \end{array} \right) = <br /> \left( \begin{array}{ccc} \sin\theta \cos\phi & \sin\theta \sin\phi & \cos\theta \\ -\sin\phi & \cos \phi & 0 \\ \cos\theta \cos\phi & \cos\theta \sin\phi & -\sin\theta \end{array}\right) \cdot \left( \begin{array}{c} \hat{x} \\ \hat{y} \\ \hat{z} \end{array} \right)[/tex]

or

[tex]T = \left( \begin{array}{ccc} \sin\theta \cos\phi & \sin\theta \sin\phi & \cos\theta \\ -\sin\phi & \cos \phi & 0 \\ \cos\theta \cos\phi & \cos\theta \sin\phi & -\sin\theta \end{array}\right)[/tex]

where phi is the polar angle and theta is the azimuthal angle.

Can this matrix T be factored into simpler matrices?
 
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Hi psholtz! :smile:

I'm not really sure where you're headed with your question.
But the short answer would be: no, you can't simplify this matrix.
 
There is more than one way to decompose this. Usually for this kind of thing you simply perform rotations to construct the transformation from one set of coordinates to the other. In your case it is a little weird since you didn't order your output coordinates in a right-handed way. By the way, I am assuming here that you mis-typed: phi is azimuthal and theta is polar?

Anyway, here is one option

[tex]T = \left( \begin{array}{ccc} 0 & 0 & 1 \\ 0 & 1 & 0 \\ 1 & 0 & 0 \end{array}\right) \left( \begin{array}{ccc} \cos \theta & 0 & -\sin \theta \\ 0 & 1 & 0 \\ \sin \theta & 0 & \cos\theta \end{array}\right) \left( \begin{array}{ccc} \cos \phi & \sin \phi & 0 \\ -\sin \phi & \cos \phi & 0 \\ 0 & 0 & 1 \end{array} \right)[/tex]

edit: The left-most matrix is not a rotation; a non-rotation is required here since your output coordinates are not in rigt-handed order. I mapped to (theta,phi,r), which is right-handed, and then used the left matrix to map to your ordering. Given my ordering, the right-most matrix rotates about z to make y and phi coincide, the middle matrix then rotates about the y-axis to make z and r coincide and x and theta coincide.

jason
 
Last edited:
The only way to solve this matrix is to try and use LU factorisation ,but if look @ entries (t11 and t13 are will never be reduced and this is similar to the other entries in the matrix ,HENCE this matrix can not be reduced to row echelon form. 4 an advice try and use trigonometry identites and see if u r goinn to find U. or u can try and use (sin) as the scalar multiple of T.
 
The only way to solve this matrix is to try and use LU factorisation ,but if look @ entries (t11 and t13 are will never be reduced and this is similar to the other entries in the matrix ,HENCE this matrix can not be reduced to row echelon form. 4 an advice try and use trigonometry identites and see if u r goinn to find U. or u can try and use (sin) as the scalar multiple of T.
 

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