How to apply tensor transformation rule

In summary, the tensor transformation rule dictates how tensors change under coordinate transformations. To apply this rule, identify the type of tensor (covariant, contravariant, or mixed), determine the transformation matrix for the coordinates, and use the appropriate equations to compute the new components of the tensor. Covariant components transform with the inverse of the transformation matrix, while contravariant components transform directly with the matrix. Mixed tensors require a combination of both methods. It is essential to maintain consistency in how indices are raised or lowered throughout the transformation process.
  • #1
guv
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TL;DR Summary
how is the tensor transformation rule applied on a position vector? $$v^\alpha = v^{*\beta} \frac{\partial u^\alpha}{\partial u^{* \beta}}$$
Suppose I have a Cartesian Coordinate system (x,y) and a polar coordinate system (##r, \theta##). The position vector (3,4) and (5, ##\arctan \frac{4}{3}##) are the same except the representation. The position vector is a tensor, how does the position vector follow the tensor transformation rule? Surely I cannot write ##x = r \frac{\partial x}{\partial r} + \theta \frac{\partial x}{\partial \theta}##

It's clear for a function ##f(x(r, \theta),y(r, \theta))##, its derivative ##\frac{\partial f}{\partial r}## which is the gradient vector follows the transformation rule.

Does the transformation rule apply to a position vector?
 
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  • #2
guv said:
Surely I cannot write ##x = r \frac{\partial x}{\partial r} + \theta \frac{\partial x}{\partial \theta}##
You can obviously write it (you just did), but it would be very wrong in general.

guv said:
Does the transformation rule apply to a position vector?
Yes! Try it in polar coordinates on the Euclidean plane!

$$
x = r \cos(\theta), \quad y = r\sin(\theta)
$$
 
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  • #3
Thanks, I know how ##x = r \cos \theta , y = r \sin \theta## works. What makes me wonder is why you can't use the tensor transformation rule on the position as I initially wrote.
 
  • #4
You can if you do it correctly.
 
  • #5
Would you mind showing how that works, I am very curious to see how. Thanks!
 
  • #6
For example, the position vector in polar coordinates is ##X = r\partial_r##. In other words, the only non-zero component is ##X^r##. Hence
$$
X^x = X^r \frac{\partial x}{\partial r}
= r \cos(\theta) = x
$$
Similarly for the y-component.
 
  • #7
Don't you need to include both ##r## and ##\theta##? i.e. exactly what I wrote initially? :cool: Why is ##r## non-zero but ##\theta## is zero? ##\theta## is not necessarily zero? Sorry I am not getting it.
 
  • #8
guv said:
Don't you need to include both ##r## and ##\theta##? i.e. exactly what I wrote initially? :cool: Why is ##r## non-zero but ##\theta## is zero? ##\theta## is not necessarily zero? Sorry I am not getting it.
I did include the ##\theta## component (it is zero).

The position vector in polar coordinates does not have ##r## and ##\theta## as its components. It only has a radial component with value ##r##. Whatever point you pick, its position vector is fully in the radial direction.
 
  • #9
If it makes you feel better we can always write
$$
X^x = X^r \frac{\partial x}{\partial r} +
\underbrace{X^\theta}_{= 0}\frac{\partial x}{\partial \theta}
= r \cos(\theta) = x
$$
 
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  • #10
Silly me. I get it now. Thanks!
 
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