Transformation matrix derivation problem

In summary, the conversation discusses the process of deriving a transformation matrix to convert a vector in cartesian coordinates to spherical coordinates. The matrix, denoted as T, is a linear transformation and is used to convert "local" vectors at a specific point in space. The conversation also touches on finding the coefficients a, b, c, etc. which are necessary for constructing the transformation matrix T.
  • #1
Fryderyk
1
0

Homework Statement



As part of an assignment, I need to derive a transformation matrix to convert a vector in cartesian coordinates to spherical coordinates.

Homework Equations



What I've got so far is:

For an arbitrary vector V,

[tex]
\textbf{V}=\left[\begin {array}{ccc}V_{x}&V_{y}&V_{z}\end{array}\right]\left[\begin{array}{c}\textbf{i}\\\textbf{j}\\\textbf{k}\end{array}\right] = \left[\begin{array}{ccc}V_{R}&V_{\theta}&V_{\phi}\end{array}\right]\left[\begin{array}{c}\textbf{e}_{R}\\\textbf{e}_{\theta}\\\textbf{e}_{\phi}\end{array}\right]
[/tex]

Knowing that VR is the component of V in the eR direction, then:

[tex]
V_{R}=aV_{x}+bV_{y}+cV_{z}
[/tex]

where a, b and c are some transformation coefficients to be derived from geometry.

Similarly,

[tex]
V_{\theta}=dV_{x}+eV_{y}+fV_{z}
[/tex]
and
[tex]
V_{\phi}=gV_{x}+hV_{y}+iV_{z}
[/tex]

From this, a transformation matrix T exists such that:

[tex]
\left[\begin{array}{ccc}V_{x}&V_{y}&V_{z}\end{array}\right]\textit{T}=\left[\begin{array}{ccc}aV_{x}+bV_{y}+cV_{z}&dV_{x}+eV_{y}+fV_{z}&gV_{x}+hV_{y}+iV_{z}\end{array}\right]=\left[\begin{array}{ccc}V_{R}&V_{\theta}&V_{\phi}\end{array}\right]
[/tex]

The Attempt at a Solution



My problem is finding this matrix T.
It's obvious from inspection that:

[tex]
T=\left[\begin{array}{ccc}a&d&g\\b&e&h\\c&f&i\end{array}\right]
[/tex]

But, I'm not sure that just stating 'it's obvious that' will be sufficient.
I'm wondering if and how the below equation can be rearranged and solved to give T.

[tex]
\left[\begin{array}{ccc}V_{x}&V_{y}&V_{z}\end{array}\right]\textit{T}=\left[\begin{array}{ccc}V_{R}&V_{\theta}&V_{\phi}\end{array}\right]
[/tex]

After this point, finding the coefficients shouldn't be a problem.

Thank you
 
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  • #2
Welcome to PF!

Hi Fryderyk! Welcome to PF! :smile:

(have a theta: θ and a phi: φ :wink:)
Fryderyk said:
My problem is finding this matrix T.
It's obvious from inspection that:

[tex]
T=\left[\begin{array}{ccc}a&d&g\\b&e&h\\c&f&i\end{array}\right]
[/tex]

But, I'm not sure that just stating 'it's obvious that' will be sufficient.
I'm wondering if and how the below equation can be rearranged and solved to give T.

[tex]
\left[\begin{array}{ccc}V_{x}&V_{y}&V_{z}\end{array}\right]\textit{T}=\left[\begin{array}{ccc}V_{R}&V_{\theta}&V_{\phi}\end{array}\right]
[/tex]

Yes, you're really just stating the obvious …

Finding T and finding a b c etc are the same thing.

Try it this way … you have two sets of axes, with angles between them, and you first need to find the angles …

do the two-dimensional case first (it's easier! :wink:) …

er and eθ are at angle θ to i and j, so the matrix is … ? :smile:
After this point, finding the coefficients shouldn't be a problem.
:smile: :smile:
 
  • #3
hi, I am new to PF and i have a very similer problem to this. I am also having trouble finding the T matrix. so far i hav found:
R= (x^2+y^2+z^2)^1/2
theta= sin-1(y/(x^2+y^2)^1/2)
phi =??

hope some one can help...
thanks
 
  • #4
Welcome to PF!

Hi demha! Welcome to PF! :smile:

(have a square-root: √ and try using the X2 tag just above the Reply box :wink:)
demha said:
hi, I am new to PF and i have a very similer problem to this. I am also having trouble finding the T matrix. so far i hav found:
R= (x^2+y^2+z^2)^1/2
theta= sin-1(y/(x^2+y^2)^1/2)
phi =??

You seem to be trying to find a matrix that transforms "global" coordinates.

A matrix is linear, and only gives linear transformations, but Cartesian to polar vectors isn't linear.

The matrix T isn't intended to convert vectors which start at the origin … it's only for converting "local" vectors at a particular point (x,y,z) = (r,θ,φ) … so you're converting from i j and k at that point to er eθ and eφ at that point.

For that, you don't need √ or sin-1, you just use the angles. :wink:

As I said to Fryderyk, try the two-dimensional case first. :smile:
 

Related to Transformation matrix derivation problem

1. What is a transformation matrix and why is it important in mathematics?

A transformation matrix is a mathematical tool used to represent the transformation of a vector or point from one coordinate system to another. It is important in mathematics because it allows for the simplification and standardization of transformations, making it easier to perform calculations and analyze data.

2. How is a transformation matrix derived?

A transformation matrix is derived by considering the transformation of a standard basis vector in the original coordinate system and expressing it in terms of the basis vectors in the new coordinate system. This process is repeated for each basis vector, resulting in a matrix that represents the transformation.

3. What is the difference between a 2D and 3D transformation matrix?

The main difference between a 2D and 3D transformation matrix is the number of dimensions it operates in. A 2D transformation matrix has 3 rows and 3 columns, while a 3D transformation matrix has 4 rows and 4 columns. This allows a 3D transformation matrix to account for translation in addition to rotation and scaling.

4. How do you use a transformation matrix in practical applications?

A transformation matrix is often used in computer graphics, robotics, and physics simulations to represent the movement and orientation of objects. It can also be used in data analysis to transform data from one coordinate system to another for easier analysis and comparison.

5. Are there any limitations to using a transformation matrix?

One limitation of using a transformation matrix is that it can only accurately represent linear transformations. Non-linear transformations, such as shearing or bending, cannot be accurately represented using a transformation matrix. Additionally, the order of transformations matters when using a transformation matrix, as the order in which they are applied can affect the final result.

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