How to Simplify the Covariant Derivative Transformation?

In summary, In order to factor out the partials in the second expression, you need to swap the dummy indices and use the product rule.
  • #1
JTFreitas
18
3
Homework Statement
I need to prove that the covariant derivative of a vector is a tensor. In other words, I need to show that ##\nabla_{\mu} V^{\nu}## is a tensor.
Relevant Equations
I know by definition that ##\nabla_{\mu} V^{\nu} = \frac{\partial}{\partial x^{\mu}} V^{\nu} +\Gamma^{\nu}_{\mu \sigma} V^{\sigma}##
Apologies in advance if I mess up the LaTeX. If that happens I'll be editing it right away.

By starting off with ##\nabla^{'}_{\mu} V^{'\nu}## and applying multiple transformation laws, I arrive at the following expression
$$ \frac{\partial x^{\lambda}}{\partial x'^{\mu}} \frac{\partial x'^{\nu}}{\partial x^{\alpha}} (\nabla_{\lambda} V^{\alpha}) + \frac{\partial x^{\lambda}}{\partial x'^{\mu}} \frac{\partial^{2} x'^{\nu}}{\partial x^{\lambda} \partial x^{\alpha}} V^{\alpha} + \frac{\partial^{2} x^{\alpha}}{\partial x'^{\mu} \partial x'^{\sigma}} \frac{\partial x'^{\nu}}{\partial x^{\alpha}} \frac{\partial x'^{\sigma}}{\partial x^{\beta}} V^{\beta} $$

I know my next step is to prove that the last two factors in the expression add up to zero. I know I need to "factor out" the partials, but I'm unsure which indices I should do that in terms of, or in what way I can relabel the indices in my favor. (I'm not very clear on when I can/cannot relabel indices in general, which has become problematic.)

Thanks for any help in advance!
 
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  • #2
Yes, you just need a bit of index manipulation. First, if you swap the dummy indices ##\alpha## and ##\beta## in the second expression, you should get a common factor of ##V^{\alpha}##.

Then, in the second expression, you can take out the ##'\sigma## derivative:
$$\frac{\partial^{2} x^{\beta}}{\partial x'^{\mu} \partial x'^{\sigma}} \frac{\partial x'^{\nu}}{\partial x^{\beta}} \frac{\partial x'^{\sigma}}{\partial x^{\alpha}} V^{\alpha} = \frac{\partial x'^{\sigma}}{\partial x^{\alpha}}\frac{\partial}{\partial x'^{\sigma}}(\frac{\partial x^{\beta}}{\partial x'^{\mu}})\frac{\partial x'^{\nu}}{\partial x^{\beta}}V^{\alpha} = \frac{\partial}{\partial x^{\alpha}}(\frac{\partial x^{\beta}}{\partial x'^{\mu}})\frac{\partial x'^{\nu}}{\partial x^{\beta}}V^{\alpha} $$
Now, think about using the product rule on your alpha derivative.
 
  • #3
PS all I really used above was the chain rule: $$\frac{\partial}{\partial x^{\alpha}} = \frac{\partial x'^{\sigma}}{\partial x^{\alpha}}\frac{\partial}{\partial x'^{\sigma}}$$
 
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  • #4
PeroK said:
Yes, you just need a bit of index manipulation. First, if you swap the dummy indices ##\alpha## and ##\beta## in the second expression, you should get a common factor of ##V^{\alpha}##.

Then, in the second expression, you can take out the ##'\sigma## derivative:
$$\frac{\partial^{2} x^{\beta}}{\partial x'^{\mu} \partial x'^{\sigma}} \frac{\partial x'^{\nu}}{\partial x^{\beta}} \frac{\partial x'^{\sigma}}{\partial x^{\alpha}} V^{\alpha} = \frac{\partial x'^{\sigma}}{\partial x^{\alpha}}\frac{\partial}{\partial x'^{\sigma}}(\frac{\partial x^{\beta}}{\partial x'^{\mu}})\frac{\partial x'^{\nu}}{\partial x^{\beta}}V^{\alpha} = \frac{\partial}{\partial x^{\alpha}}(\frac{\partial x^{\beta}}{\partial x'^{\mu}})\frac{\partial x'^{\nu}}{\partial x^{\beta}}V^{\alpha} $$
Now, think about using the product rule on your alpha derivative.

God it makes complete sense now. I've been at this for days. My professor's notes weren't exactly very clear, but pulling out the ##\partial x'^{\sigma}## made everything work out nicely and made complete sense.

Thank you so much for the response, that was really helpful!

A quick follow-up question about relabelling: correct me if I'm wrong, but we're allowed to relabel indices if they're dummy indices, or we can also relabel true indices if we don't relabel them as some index that already exists in the expression? Is this a good way of going about it?

I try my best not to reuse indices in case I get them mixed up, and later I have to relabel them back into indices that make sense. Is this good practice?
 
  • #5
JTFreitas said:
A quick follow-up question about relabelling: correct me if I'm wrong, but we're allowed to relabel indices if they're dummy indices, or we can also relabel true indices if we don't relabel them as some index that already exists in the expression? Is this a good way of going about it?
Yes, dummy indices tend to come out any old way and generally you need to sort them out in one or more of your terms at some stage to make the terms manifestly equal. It's really just $$\sum_k a_kv^k - \sum_m a_mv^m = 0$$.
Your indexing looked good. You should always have the same free indices in each term. You can change these, of course, as long as you change them in every term. For example: $$A^k_m = B^k_m \equiv A^n_r = B^n_r$$ As they mean for all ##k, m = 0, 1, 2, 3## and all ##n, r = 0, 1, 2, 3## (which is the same thing).

You'll see quite a bit of that as well, when an equation has one set of free indices when first stated - but then when it's used later a different set of free indices is used.
 
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  • #6
Perfect, thank you so much!

We can close the thread now
 

FAQ: How to Simplify the Covariant Derivative Transformation?

1. What is the concept of a covariant derivative?

The covariant derivative is a mathematical operation that is used to measure the rate of change of a vector field along a given direction. It takes into account the curvature of the underlying space and adjusts the rate of change accordingly.

How is the covariant derivative related to the ordinary derivative?

The covariant derivative is a generalization of the ordinary derivative in Euclidean space. It takes into account the effects of curvature and is therefore more suitable for use in non-Euclidean spaces.

What is the formula for calculating the covariant derivative of a vector?

The formula for calculating the covariant derivative of a vector is given by: ∇vU = (∂U/∂t) + (∂U/∂xi)vi + ΓijkUjvk, where ∇vU is the covariant derivative of U along the direction v, ∂U/∂t is the ordinary time derivative, ∂U/∂xi is the ordinary spatial derivative, and Γijk is the Christoffel symbol of the second kind.

What are some applications of the covariant derivative in physics?

The covariant derivative is used in various fields of physics, such as general relativity, electromagnetism, and fluid dynamics. It is used to describe the motion of particles in curved space-time, the behavior of electric and magnetic fields in non-inertial frames, and the flow of fluids in curved space.

How does the covariant derivative transform under a change of coordinates?

The covariant derivative transforms in a specific way under a change of coordinates, known as the transformation law. This law ensures that the covariant derivative is a coordinate-independent quantity and remains consistent in different coordinate systems. It involves the use of the Christoffel symbols and the Jacobian matrix of the coordinate transformation.

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