Gradient and curvilinear coordinates

Incand
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Homework Statement


Show that ##\nabla u_i \cdot \frac{\partial \vec r}{\partial u_i} = \delta_{ij}##.

(##u_i## is assumed to be a generalized coordinate.)

Homework Equations


Gradient in curvilinear coordinates
##\nabla \phi = \sum_{i=1}^3 \vec e_i \frac{1}{h_i} \frac{\partial \phi}{\partial u_i}##

The Attempt at a Solution


So what I need to show is that the gradient is orthogonal to the (other two) partial derivatives (but it doesn't have to be parallel to the third since the system doesn't have to be orthogonal!).
The expression can then be written as
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k} \frac{\partial u_i}{\partial u_k} \right) \cdot \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \frac{1}{h_k}\frac{\partial u_i}{\partial u_k}\frac{\partial r_k}{\partial u_j} ##.
I'm thinking I could use the chain rule here but I don't seem to get anywhere. Another thing of note is that ##\frac{1}{h_k}\frac{\partial \vec r}{\partial u_k} = \vec e_k## which may be of use somewhere.
 
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You can substitue ##\partial \vec{r}/\partial u_j = h_j \vec{e}_j## in your expression.
 
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fzero said:
You can substitue ##\partial \vec{r}/\partial u_j = h_j \vec{e}_j## in your expression.
Thanks!
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot \frac{h_j}{h_j} \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot h_j \vec e_j = \frac{\partial u_i}{\partial u_j}##.
Which is obviously ##1## for ##i=j## but how do I know that it's zero when ##i\ne j##? For me this isn't obvious. In a cylindrical coordinate system the unit vector ##\hat \rho## is dependent on ##\hat \phi## and the other way around so I don't see why the coordinates them self can't be dependent.
 
Incand said:
Thanks!
##\sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot \frac{h_j}{h_j} \frac{\partial \vec r}{\partial u_j} = \sum_{k=1}^3 \left( \vec e_k \frac{1}{h_k}\frac{\partial u_i}{\partial u_k} \right) \cdot h_j \vec e_j = \frac{\partial u_i}{\partial u_j}##.
Which is obviously ##1## for ##i=j## but how do I know that it's zero when ##i\ne j##? For me this isn't obvious. In a cylindrical coordinate system the unit vector ##\hat \rho## is dependent on ##\hat \phi## and the other way around so I don't see why the coordinates them self can't be dependent.

The partial derivative ##\partial/\partial u_j## is defined so that ##u_{i\neq j}## are treated as constants for the purpose of taking the derivative.
 
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fzero said:
The partial derivative ##\partial/\partial u_j## is defined so that ##u_{i\neq j}## are treated as constants for the purpose of taking the derivative.
Right, I wasn't thinking clearly, Thanks!
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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