Div and curl in other coordinate systems

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SUMMARY

This discussion focuses on the application of divergence and curl in various coordinate systems, specifically Cartesian, spherical, and cylindrical coordinates. The divergence and curl definitions are derived from the divergence and Stokes' theorems, with specific formulations provided for each coordinate system. The conversation highlights the complexities that arise when applying vector methods in curvilinear coordinates, emphasizing that the del operator (\vec \nabla) behaves differently across these systems. The participants clarify that while the notation remains consistent, the underlying calculations involve additional terms in non-Cartesian coordinates.

PREREQUISITES
  • Understanding of vector calculus concepts, including divergence and curl
  • Familiarity with coordinate systems, particularly Cartesian, spherical, and cylindrical
  • Knowledge of the del operator (\vec \nabla) and its applications
  • Basic grasp of the divergence theorem and Stokes' theorem
NEXT STEPS
  • Study the derivation of divergence and curl in spherical coordinates
  • Learn about the implications of using the del operator in curvilinear coordinates
  • Explore advanced vector calculus techniques in cylindrical coordinates
  • Review applications of divergence and curl in physics, particularly in electromagnetism
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Students and professionals in mathematics, physics, and engineering who are working with vector calculus and need to understand the implications of different coordinate systems on divergence and curl operations.

Jezza
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My question is mostly about notation. I know the general definitions for divergence and curl, which can be derived from the divergence and Stokes' theorems respectively, are:

\mathrm{div } \vec{E} \bigg| _P = \lim_{\Delta V \to 0} \frac{1}{\Delta V} \iint_{S} \vec{E} \cdot \mathrm{d} \vec{S}

Where S is the closed surface bounding V, and V is a volume whose limit contains the point P.

\left(\mathrm{curl } \vec{E}\right) \cdot \vec{n} \bigg|_P= \lim_{\Delta S \to 0} \frac{1}{\Delta S} \iint_{\ell} \vec{E} \cdot \mathrm{d} \vec{\ell}.

Where \vec n is the unit normal to the closed contour \ell which bounds the surface S whose limit surrounds the point P.I also know that in cartesian coordinates, when we define the del operator \vec \nabla, these definitions are equivalent to: (Including \mathrm{grad} \phi where \phi is a scalar field.)
<br /> \begin{align}<br /> &amp;&amp;\vec \nabla &amp;= \left(\frac{\partial}{\partial x}, \frac{\partial}{\partial y}, \frac{\partial}{\partial z}\right) \nonumber \\ \nonumber \\<br /> <br /> \mathrm{grad} \phi &amp;=&amp; \vec \nabla \phi &amp;= \left(\frac{\partial \phi}{\partial x}, \frac{\partial \phi}{\partial y}, \frac{\partial \phi}{\partial z}\right) \nonumber \\ \nonumber \\<br /> <br /> \mathrm{div } \vec{E} &amp;=&amp; \vec\nabla \cdot \vec E &amp;= \frac{\partial E_x}{\partial x} + \frac{\partial E_y}{\partial y} + \frac{\partial E_z}{\partial z} \nonumber \\ \nonumber \\<br /> <br /> \mathrm{curl } \vec{E} &amp;=&amp; \vec\nabla \times \vec E &amp;= \left(\frac{\partial E_z}{\partial y} - \frac{\partial E_y}{\partial z}, \frac{\partial E_x}{\partial z} - \frac{\partial E_z}{\partial x}, \frac{\partial E_y}{\partial x} - \frac{\partial E_x}{\partial y}\right) \nonumber<br /> \end{align}<br />
In this case, the right hand sides can be reached from the left hand sides simply by applying vector methods, which (at least as I was led to believe) is the beauty of the \vec \nabla notation. I'm also perfectly happy and understand that the definition of \vec \nabla changes with coordinate system. For example, in spherical polar coordinates (r, \theta, \varphi):
<br /> \vec \nabla = \left(\frac{\partial}{\partial r}, \frac{1}{r} \frac{\partial}{\partial \theta}, \frac{1}{r \sin\theta} \frac{\partial}{\partial \varphi}\right)<br />
The problem as I see it comes when you try and work out div, grad and curl in other coordinate systems. grad can be reached using standard vector methods, but the divergence in spherical polars is:

<br /> \mathrm{div } \vec{E} = \frac{1}{r^2} \frac{\partial}{\partial r}\left(E_r r^2\right) + \frac{1}{r \sin \theta} \frac{\partial}{\partial \theta}\left(E_\theta \sin \theta \right) + \frac{1}{r \sin \theta}\frac{\partial E_\varphi}{\partial \varphi}<br />

Which clearly cannot be reached simply using vector methods. What I'm trying to get at is that despite \vec \nabla \cdot \vec E \neq \mathrm{div} \vec E (in traditional vector notation), we still write it! It's a similar story for curl.

It's a similar situation with cylindrical coordinates, so I assume the ability to blindly apply vector methods when calculating div and curl in cartesian coordinates is a special case. I suppose my question is why do we use this notation for general coordinate systems? How can we call del on its own an operator when actually there's more going on for the div and curl operations? Am I just missing something about how the del operator works?

Thanks for any help!
 
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I think the point that you are missing is the following:
In rectangular coordinates, \vec{E} = E_x \vec{e_x} + E_y \vec{e_y} + E_z \vec{e_z}. When you take \frac{\partial}{\partial x}(E_x \vec{e_x}), you just get \frac{\partial E_x}{\partial x} because \vec{e_x} is constant. However, in curvilinear coordinate systems, like spherical coordinates, you have \vec{E} = E_r \vec{e_r} + E_\theta \vec{e_\theta} + E_\phi \vec{e_\phi}. When you take \frac{\partial}{\partial r}(E_r \vec{e_r}), you get one term which is \frac{\partial E_r}{\partial r}, but you get a second term that includes E_r \frac{\partial \vec e_r}{\partial r}, because \vec e_r changes from point to point. Does this help?
 
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It does help, thank you :)
 

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