Covariant derivative transformation

In summary, the problem concerns transforming a covariant differentiation into a (1,1) tensor by using the formula for covariant differentiation and demanding that it is a (1,1) tensor. This can be proven by transforming the primed coordinates using the given equations and solving for the transformation of the Christoffel symbol. The dummy variables in the equations do not affect the final result.
  • #1
faklif
18
0

Homework Statement


The problem concerns how to transform a covariant differentiation. Using this formula for covariant differentiation and demanding that it is a (1,1) tensor:
[tex]
\nabla_cX^a=\partial_cX^a+\Gamma^a_{bc}X^b
[/tex]
it should be proven that
[tex]
\Gamma'^a_{bc}=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^e}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}
-
\frac{{\partial}x^d}{{\partial}x'^b}
\frac{{\partial}x^e}{{\partial}x'^c}
\frac{{\partial}^2x'^a}{{{\partial}x^d}{{\partial}x^e}}
[/tex]

Homework Equations


[tex]
\partial'_cX'^a=
\frac{{\partial}x^f}{{\partial}x'^c}\frac{\partial}{{\partial}x^f}
(
\frac{{\partial}x'^a}{{\partial}x^d}X^d
)=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\frac{\partial}{{\partial}x^f}
X^d
+
\frac{{\partial}^2x'^a}{{\partial}x^f{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
X^d
[/tex]

[tex]
X^d
=
\frac{{\partial}x^d}{{\partial}x'^b}
\frac{{\partial}x'^b}{{\partial}x^d}
X^d
=
\frac{{\partial}x^d}{{\partial}x'^b}
X'^b
[/tex]
[tex]
X^e
=
\frac{{\partial}x^e}{{\partial}x'^b}
X'^b
[/tex]

The Attempt at a Solution


I thought I'd simply look at the primed coordinates from two directions and that that should do it... didn't quite happen as planned though.

In primed coordinates
[tex]
\nabla_cX^a'
=
{\partial}'_cX'^a
+
\Gamma^a_{bc}'X'^b
[/tex]

Transformed using the equations under 2.
[tex]
\nabla_cX^a'
=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\frac{\partial}{{\partial}x^f}
X^d
+
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}X^e
=
{\partial}'_cX'^a
-
\frac{{\partial}^2x'^a}{{\partial}x^f{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
X^d
+
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}X^e
=
{\partial}'_cX'^a
-
\frac{{\partial}^2x'^a}{{\partial}x^f{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\frac{{\partial}x^d}{{\partial}x'^b}
X'^b
+
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}
\frac{{\partial}x^e}{{\partial}x'^b}
X'^b
[/tex]

So my thought was that anything related to X'^b would be the what I seek which gives

[tex]
\Gamma'^a_{bc}=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^e}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}
-
\frac{{\partial}x^d}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\frac{{\partial}^2x'^a}{{\partial}x^f{\partial}x^d}
[/tex]

This i kind of close but it's different in the last part where I have f:s instead of e:s. I would really appreciate some help, I've been stuck for a long time.
 
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  • #2
faklif said:
Using this formula for covariant differentiation and demanding that it is a (1,1) tensor:
[tex]
\nabla_cX^a=\partial_cX^a+\Gamma^a_{bc}X^b
[/tex]
it should be proven that
[tex]
\Gamma'^a_{bc}=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^e}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}
-
\frac{{\partial}x^d}{{\partial}x'^b}
\frac{{\partial}x^e}{{\partial}x'^c}
\frac{{\partial}^2x'^a}{{{\partial}x^d}{{\partial}x^e}}
[/tex]

[tex]
\Gamma'^a_{bc}=
\frac{{\partial}x'^a}{{\partial}x^d}
\frac{{\partial}x^e}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\Gamma^d_{ef}
-
\frac{{\partial}x^d}{{\partial}x'^b}
\frac{{\partial}x^f}{{\partial}x'^c}
\frac{{\partial}^2x'^a}{{\partial}x^f{\partial}x^d}
[/tex]

This i kind of close but it's different in the last part where I have f:s instead of e:s. I would really appreciate some help, I've been stuck for a long time.

Hi faklif! :smile:

Do you mean you're worried about having ∂xf and /∂xf instead of ∂xe and /∂xe ?

They're "dummy variables" … it doesn't matter what they are! :wink:
 
  • #3
tiny-tim said:
Hi faklif! :smile:

Do you mean you're worried about having ∂xf and /∂xf instead of ∂xe and /∂xe ?

They're "dummy variables" … it doesn't matter what they are! :wink:

Hi and thank you!

Now that I think some more about it (should have done that before spending the better part of the weekend :wink:, having to much spare time makes me stupid...) it makes sense. For a given a,b,c you'd still get the same implied summations. Thanks again for rescuing my monday!
 

1. What is a covariant derivative transformation?

A covariant derivative transformation is a mathematical concept used in differential geometry and tensor calculus to describe how a tensor field changes as we move along a given path. It takes into account the curvature of the space in which the tensor field is defined.

2. How is a covariant derivative transformation different from a regular derivative?

While a regular derivative measures the change of a function with respect to a single variable, a covariant derivative transformation takes into account the change of a tensor field with respect to multiple variables and the curvature of the space in which it is defined. It is a more general and powerful concept than a regular derivative.

3. What is the mathematical notation for a covariant derivative transformation?

The notation for a covariant derivative transformation varies depending on the context and the type of tensor field being considered. In general, it is denoted by the symbol ∇ and may include subscripts and superscripts to indicate the type of derivative being taken.

4. What are some real-world applications of covariant derivative transformations?

Covariant derivative transformations are used in various fields of physics and engineering, such as general relativity, fluid mechanics, and electromagnetism. They are essential for understanding the behavior of objects in curved spaces and for making accurate predictions in these fields.

5. How do covariant derivative transformations relate to the concept of parallel transport?

Covariant derivative transformations are closely related to parallel transport, which describes how a vector or tensor field changes when transported along a given path without rotating or deforming. The covariant derivative can be thought of as a measure of the failure of parallel transport to preserve the tensor field along the given path.

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