Divergence in Spherical Coordinate System by Metric Tensor

In summary, the conversation discusses the reason for a discrepancy in the result equation for vector components in electrodynamics. The professor mentions the use of transformation of components and the distinction between covariant and contravariant components. The conversation also mentions the use of holonomic and normalized basis vectors, as well as the expression for the divergence in both cases. The summary concludes that the difference in the results is due to the use of different basis vectors and metric components.
  • #1
Astrocyte
12
2
Homework Statement
I want to get a familiar form of spherical coordinate system's divergence formula from the metric tensor.
Relevant Equations
metric tensor, covariant derivative
1620289371095.png

The result equation doesn't fit with the familiar divergence form that are usually used in electrodynamics.
I want to know the reason why I was wrong.
My professor says about transformation of components.
1620289527170.png

But I cannot close to answer by using this hint, because I don't have any idea about "x".
Even I'm confused whether covariant component is correct or contravariant one does.
 
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  • #2
In your setting all the three components of A have same dimension on L or not? In familiar case you showed their components have same dimension on L and distinction of covariant and contravariant components are not clear to me there.

For an instance a special case of ##\mathbf{A}=d\mathbf{r}## you may take
[tex]A_r=dr,A_\theta =d\theta,A_\phi=d\phi[/tex]
[tex]A^r=dr,A^\theta =r^2 d\theta,A^\phi=r^2 \sin^2\theta\ d\phi[/tex]
In familiar vector analysis vector components are somewhat between, i.e.
[tex]A_r=dr,A_\theta =r\ d\theta,A_\phi=r\ sin\theta \ d\phi[/tex]
All the components have dimension of L. You see the coefficient ##r## differ between them.
 
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  • #3
The difference between your results and the ones usually found in textbooks on electrodynamics simply is that in the above calculuation you use the holonomic (in this case orthogonal) basis vectors, while in the textbooks they use the corresponding normalized (i.e., orthonormal) basis vectors (3-beins).

It's easier to see calculating the vectors explicitly in terms Carstesian components:
$$\vec{x}=\begin{pmatrix} r \sin \vartheta \cos \varphi \\ r \sin \vartheta \sin \varphi \\ r \sin \vartheta \end{pmatrix}.$$
The holnomous basis is simply given as the partial derivatives wrt. the spherical coordinates,
$$\vec{b}_r = \partial_r \vec{x} = \begin{pmatrix} \sin \vartheta \cos \varphi \\ \sin \vartheta \sin \varphi \\ \sin \vartheta \end{pmatrix}.$$
$$\vec{b}_{\vartheta}=\partial_{\vartheta} \vec{x} = \begin{pmatrix} r \cos \vartheta \cos \varphi \\ r \sin \vartheta \sin \varphi \\ -r \cos \vartheta \end{pmatrix}.$$
$$\vec{b}_{\varphi} = \partial_{\varphi} \vec{x}= \begin{pmatrix} -r \sin \vartheta \sin \varphi \\ r \sin \vartheta \cos \varphi \\ 0 \end{pmatrix}.$$
The vectors are orthogonal but not normalized. In your standard Ricci calculus these are the basis vectors you use.

In the E&M textbooks you usually use the corresponding normalized vectors. The norms are
$$|\vec{b}_r|=1=\sqrt{g_{rr}}, \quad |\vec{b}_{\vartheta}|=r=\sqrt{g_{\vartheta \vartheta}}, \quad |\vec{b}_{\varphi}|=r \sin \vartheta=\sqrt{g_{\varphi \varphi}}.$$

So your vector fields are decomposed as
$$\vec{A}=A^r \vec{b}_r + A^{\vartheta} \vec{b}_{\vartheta} + A^{\varphi} \vec{b}_{\varphi}.$$
In the textbooks it's
$$\vec{A}=\tilde{A}^r \vec{e}_r + \tilde{A}^{\vartheta} \vec{e}_{\vartheta} + \tilde{A}^{\varphi} \vec{e}_{\varphi}.$$
To get the "textbook expression" for the divergence you simply have to express the ##A_j## by the ##\tilde{A}_j##. That's easy: Just express the ##\vec{e}_j## with the ##\vec{b}_j##:
$$\vec{A}=\tilde{A}^r \vec{b}_r + \frac{\tilde{A}^{\vartheta}}{r} \vec{b}_{\vartheta} + \frac{\tilde{A}^{\varphi}}{r \sin \vartheta} \vec{b}_{\varphi}.$$
So you have
$$A^r=\tilde{A}^r, \quad A_{\vartheta}=\frac{\tilde{A}^{\vartheta}}{r}, \quad A^{\varphi}=\frac{\tilde{A}_{\varphi}}{r \sin \vartheta}.$$
In your expression you rather use the covariant components, i.e., using your covariant metric components,
$$A^r=A_r=\tilde{A}^r, \quad A_{\vartheta}=r^2 A^{\vartheta}=r \tilde{A}^{\vartheta}, \quad A_{\varphi}=r^2 \sin^2 \vartheta A^{\varphi}=r \sin \vartheta \tilde{A}^{\varphi}.$$

Plug this in your equation for the divergence, you get
$$\vec{\nabla} \cdot \vec{A}=\frac{1}{r^2}(r^2 \tilde{A}_r) + \frac{1}{r \sin \vartheta} \partial_{\vartheta}(\sin \vartheta \tilde{A}^{\vartheta}) + \frac{1}{r \sin \vartheta} \partial_{\varphi} \tilde{A}^{\varphi},$$
as it should be.

Also note that in the "textbook formalism" ##\tilde{A}^{j}=\tilde{A}_{j}##, because here your basis is orthonormal ("3-bein formalism") and thus ##\tilde{g}_{jk}=\delta_{jk}##.
 
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1. What is divergence in a spherical coordinate system?

Divergence is a mathematical concept that describes the flow or spread of a vector field. In a spherical coordinate system, divergence measures the rate at which a vector field is expanding or contracting at a particular point in space.

2. How is divergence calculated in a spherical coordinate system?

In a spherical coordinate system, divergence is calculated using the metric tensor, which is a mathematical object that describes the relationship between coordinate systems. The metric tensor contains information about the distance and angle measurements in a particular coordinate system, and it is used to calculate the divergence of a vector field.

3. What is the significance of divergence in a spherical coordinate system?

Divergence is an important concept in physics and engineering, as it helps us understand the behavior of vector fields in different coordinate systems. In a spherical coordinate system, divergence can tell us about the flow of fluid or the distribution of electric charge, among other things.

4. How does the metric tensor affect divergence in a spherical coordinate system?

The metric tensor plays a crucial role in calculating divergence in a spherical coordinate system. It contains information about the curvature and geometry of the coordinate system, which directly affects the calculation of divergence. Therefore, the metric tensor must be carefully considered when analyzing divergence in a spherical coordinate system.

5. Can divergence be negative in a spherical coordinate system?

Yes, divergence can be negative in a spherical coordinate system. This indicates that the vector field is contracting at a particular point in space. However, it is also possible for divergence to be zero, which means that the vector field is neither expanding nor contracting at that point.

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