Differentiation spherical coordinates

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Discussion Overview

The discussion revolves around the differentiation of spherical coordinates, particularly in the context of inverting a mass matrix. Participants explore the mathematical expressions involved and the challenges faced when certain conditions are met, such as when the vector aligns with specific axes.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant seeks clarification on the expression \(\dfrac{q}{\partial \mathbf{r}}\) and whether it should be \(\dfrac{\partial q}{\partial \mathbf{r}}\), questioning the implications of the notation.
  • Another participant notes that when differentiating both sides, they arrive at \(\dfrac{\partial q}{\partial \mathbf{r}} - \sin q = \dfrac{\hat{\mathbf{k}}}{L}\) and expresses difficulties when \(q=0\).
  • A different participant suggests transforming the gradient to spherical coordinates and provides a detailed derivation of the gradient in spherical coordinates, emphasizing the importance of using the correct expression for covariant differential operators.
  • There is a mention of the relationship between the vectors \(\hat{\mathbf{k}}\) and \(\mathbf{r}\) when \(\mathbf{r} = \hat{\mathbf{k}}\) or \(-\hat{\mathbf{k}}\), raising questions about the implications of these conditions on the calculations.

Areas of Agreement / Disagreement

Participants express differing views on the correct approach to differentiation in spherical coordinates, and there is no consensus on how to resolve the issues presented, particularly regarding the behavior of the expressions when certain conditions are met.

Contextual Notes

Limitations include potential misunderstandings of notation, the dependence on the correct transformation to spherical coordinates, and unresolved mathematical steps related to the differentiation process.

ebrattr
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Hi ! I'm trying to inverse a mass matrix so I need to do something like this

[itex]\dfrac{q}{\partial \mathbf{r}}[/itex] where [itex]\cos q = \dfrac{\mathbf{r}\cdot \hat{\mathbf{k}}}{r}[/itex]

However, when [itex]\mathbf{r} = \hat{\mathbf{k}} \text{ or } -\hat{\mathbf{k}}[/itex] I have problems.

¿What can I do?

Thanks !
 
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ebrattr said:
Hi ! I'm trying to inverse a mass matrix so I need to do something like this

[itex]\dfrac{q}{\partial \mathbf{r}}[/itex] where [itex]\cos q = \dfrac{\mathbf{r}\cdot \hat{\mathbf{k}}}{r}[/itex]
What does ##\dfrac{q}{\partial \mathbf{r}} ## mean?
Did you mean to write this?
##\dfrac{\partial q}{\partial \mathbf{r}}##
ebrattr said:
However, when [itex]\mathbf{r} = \hat{\mathbf{k}} \text{ or } -\hat{\mathbf{k}}[/itex] I have problems.

¿What can I do?
Isn't k##\cdot##k = 1, and similarly, isn't -k##\cdot##k = -1? What problems are you having?
 
Yes, I mean [itex]\dfrac{\partial q}{\partial \mathbf{r}}[/itex] As you know if you do [itex]\dfrac{\partial}{\partial \mathbf{r}}[/itex] both sides you get [itex]\dfrac{\partial q}{\partial \mathbf{r}} -\sin q = \dfrac{\hat{\mathbf{k}}}{L}[/itex]. Solving for [itex]\dfrac{\partial q}{\partial \mathbf{r}}[/itex] you get [itex]\dfrac{\partial q}{\partial \mathbf{r}} = -\dfrac{\hat{\mathbf{k}}}{L\sin q}[/itex] So, when [itex]q=0[/itex] I'm having troubles.
 
You have to transform the gradient to spherical coordinates first. This you get with
[tex]\mathrm{d} f=\mathrm{d} \vec{r} \cdot \vec{\nabla} f = (\mathrm{d} r \vec{e}_r \cdot +\mathrm{d} \vartheta r \vec{e}_{\vartheta} + \mathrm{d} \varphi r \sin \vartheta \vec{e}_{\varphi}) \cdot \nabla{f}.[/tex]
Since [itex]\vec{e}_{r}[/itex], [itex]\vec{e}_{\vartheta}[/itex], and [itex]\vec{e}_{\varphi}[/itex] build a complete orthonormal system you immediately read off
[tex]\vec{\nabla} \cdot \vec{r}=\vec{e}_r \frac{\partial f}{\partial r} + \vec{e}_{\vartheta} \frac{1}{r} \frac{\partial f}{\partial \vartheta} + \vec{e}_{\varphi} \frac{1}{r \sin \vartheta} \frac{\partial f}{\partial \vartheta}.[/tex]
For [itex]f=\vartheta[/itex] you thus get
[tex]\vec{\nabla} \vartheta=\frac{1}{r} \vec{e}_{\vartheta}.[/tex]
You can of course do the whole thing in Cartesian coordinates:
[tex]f=\arccos \left (\frac{\vec{k} \cdot \vec{r}}{r} \right ).[/tex]
Using the chain rule gives
[tex]\vec{\nabla} f=-\frac{1}{\sin \vartheta} \vec{\nabla} \left (\frac{\vec{k} \cdot \vec{r}}{r} \right )=-\frac{1}{\sin \vartheta} \left (\frac{\vec{k}}{r}-\frac{(\vec{r} \cdot \vec{k}) \vec{r}}{r^3} \right ).[/tex]
Now we can simplify
[tex]\frac{\vec{k}}{r}-\frac{(\vec{r} \cdot \vec{k}) \vec{r}}{r^3}<br /> =\frac{1}{r} \left (\vec{k} - \frac{(\vec{r} \cdot \vec{k})<br /> \vec{r}}{r^2} \right )=-\frac{\sin \vartheta}{r} \begin{pmatrix}<br /> \cos \varphi \cos \vartheta \\ \sin \varphi \cos \vartheta \\ -\sin \vartheta<br /> \end{pmatrix}=-\frac{\vec{e}_{\vartheta} \sin \vartheta}{r}.[/tex]
Plugging this into the equation above you again get
[tex]\vec{\nabla} \vartheta=\frac{1}{r} \vec{e}_{\vartheta}.[/tex]
As you see you always must use the correct expression of the covariant differential operators to get the right result!
 

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