Deriving the Spherical Unit Vectors

In summary, the conversation discusses the conversion from rectangular to spherical coordinates and the derivation of spherical unit vectors in the cartesian basis. The process is similar for cylindrical coordinates. The unit vectors are obtained by taking partial derivatives of the position vector with respect to each coordinate while holding the other coordinates constant. These expressions can be simplified using scale factors or metric coefficients. A link to a more detailed explanation is also provided.
  • #1
Shock
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Does anyone know how to derive the spherical unit vectors in the cartesian basis? Or a good link that might show how its done?

I would also like to see it done for the cylindrical coordinates. I have tried to do it, especially for the spherical case, but i can only get r-hat.

It would be a great help!
 
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  • #2
Well, I have written an article about it (its not typed though). If you could wait for a week or so, I can type it, put it on PlanetMath, publish it and then give you the link (I can't do it now because my Final exams are approaching soon).

Anyways, the basic idea is as follows:

You know that the conversion from rectangular to spherical coordinates goes like this:
[tex]x = r\sin(\theta)\cos(\phi), \qquad y = r\sin(\theta)\sin(\phi), \qquad z = r\cos(\theta)[/tex]

Now we can represent any point in space in terms of the position vector [tex]\vec{R} = x\ha{i} + y\hat{j} + z\hat{k}[/tex] or in spherical coordinates as:
[tex]\vec{R} = r\sin(\theta)\cos(\phi)\hat{i} + r\sin(\theta)\sin(\phi)\hat{j} + r\cos(\theta)\hat{k}[/tex].

So far so good! Now, what does it mean for something to be a unit vector?? Take for example the vector [tex]\hat{r}[/tex]. What's special about it? Its not really its length because all unit vectors have the length of 1. That's BORING! BUT its DIRECTION is special, because that is what separates one unit vector from another. Our unit vector [tex]\hat{r}[/tex], for example, points in the direction where the coordinate [tex]r[/tex] increases while the rest of the coordinates are held constant.

Well, this is the same thing as taking the PARTAL derivative of the position vector [tex]\vec{R}[/tex] with respect to [tex]r[/tex] while holding [tex]\theta[/tex] and [tex]\phi [/tex] constant (think about it, it'll make sense).

So therefore:
[tex]\hat{r} = \frac{\partial \vec{R}}{\partial r} \qquad \hat{\theta} = \frac{\partial\vec{R}}{\partial\theta} \qquad \hat{\phi} = \frac{\partial\vec{R}}{\partial\phi}[/tex]

Warning: What I have given you are not exactly unit vectors. You still have to divide them by their respective lengths but they do have the right direction which is the more important thing.

edit: Here's is the more accurate forumulation:

[tex]\mathbf{ \hat{r} = \frac{\frac{\partial \vec{R}}{\partial r}}{\Big| \frac{\partial \vec{R}}{\partial r} \Big|} \qquad \hat{\theta} = \frac{\frac{\partial\vec{R}}{\partial\theta}}{\Big| \frac{\partial\vec{R}}{\partial\theta} \Big|} \qquad \hat{\phi} = \frac{\frac{\partial\vec{R}}{\partial\phi}}{\Big| \frac{\partial\vec{R}}{\partial\phi} \Big|} }[/tex]

You can derive the unit vectors for cylindrical coordinates in a similar way by changing the position vecotor [tex]\vec{R}[/tex] accordingly.

Hope this helps. :smile:
 
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Likes M Saad, ZeroDegrees, Gopal Mailpalli and 1 other person
  • #3
Swapnil said:
[tex]\mathbf{ \hat{r} = \frac{\frac{\partial \vec{R}}{\partial r}}{\Big| \frac{\partial \vec{R}}{\partial r} \Big|} \qquad \hat{\theta} = \frac{\frac{\partial\vec{R}}{\partial\theta}}{\Big| \frac{\partial\vec{R}}{\partial\theta} \Big|} \qquad \hat{\phi} = \frac{\frac{\partial\vec{R}}{\partial\phi}}{\Big| \frac{\partial\vec{R}}{\partial\phi} \Big|} }[/tex]
BTW, we can write the above expression more concisely as:

[tex] \hat{r} = \frac{\frac{\partial \vec{R}}{\partial r}}{h_r} \qquad \hat{\theta} = \frac{\frac{\partial\vec{R}}{\partial\theta}}{h_{\theta}} \qquad \hat{\phi} = \frac{\frac{\partial\vec{R}}{\partial\phi}}{h_{\phi}}[/tex]

where

[tex]h_r = \Big| \frac{\partial \vec{R}}{\partial r} \Big|, \quad h_{\theta} = \Big| \frac{\partial\vec{R}}{\partial\theta} \Big|, \quad h_{\phi} = \Big| \frac{\partial\vec{R}}{\partial\phi} \Big|[/tex]

and [itex]h_r, h_{\theta}, h_{\phi}[/itex] are collectively know as scale factors or metric coefficients of the spherical coordinate system. They are also denoted as [itex]h_1, h_2, h_3[/itex] or simply as [itex]h_i[/itex] sometimes (especially in General relativity) when working with any arbitrary curvilinear coordinate system.
 
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  • #5
Thank you sooooooo much for this.
Simple but the idea of direction made it so easy!
 

FAQ: Deriving the Spherical Unit Vectors

1. What are spherical unit vectors?

Spherical unit vectors, also known as direction cosines, are three unit vectors that define the orientation of a point on the surface of a sphere in three-dimensional space. They are commonly denoted by i, j, and k and correspond to the x, y, and z axes, respectively.

2. How are spherical unit vectors derived?

Spherical unit vectors can be derived using trigonometric functions and the spherical coordinate system. The i, j, and k unit vectors are calculated based on the angles of the point on the sphere in relation to the x, y, and z axes.

3. What is the importance of spherical unit vectors in science?

Spherical unit vectors are used in many scientific fields, including physics, astronomy, and engineering. They are particularly useful for describing the direction and orientation of objects in three-dimensional space and are essential for solving complex problems involving spherical coordinates.

4. Can spherical unit vectors be converted to Cartesian coordinates?

Yes, spherical unit vectors can be converted to Cartesian coordinates using the following equations:

x = r sinθ cosφ

y = r sinθ sinφ

z = r cosθ

where r is the distance from the origin to the point, θ is the angle from the positive z-axis, and φ is the angle from the positive x-axis.

5. Are there any real-world applications of spherical unit vectors?

Yes, spherical unit vectors have many practical applications in fields such as navigation, satellite tracking, and computer graphics. They are also used in the study of celestial bodies and in the development of 3D models and simulations.

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