Contravariant derivative tensor problem

In summary, a covariant derivative is a derivative that transforms as a tensor. It is defined using a connection, which is a map that satisfies certain properties. The covariant derivative of a tensor is found by extending the definition for vector fields and covector fields. The covariant derivative of a scalar field is given by the usual partial derivative, and the covariant derivative of a covector field is defined using a modified Leibnitz rule.
  • #1
rafal_
2
0
Tensor [tex]\left (
\begin{array}{cc}
1\\1
\end{array}
\right )[/tex] is [tex]T=T^\alpha_\beta \omega^\beta \otimes \vec e_\alpha[/tex]Why is contravariant derivative tensor [tex]\left (\begin{array}{cc}1\\1 \end{array}
\right )[/tex]
[tex]V^\alpha_{;\beta}\vec {e_\alpha}[/tex] - contravariant derivative
 
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  • #2
I don't understand the question. What do you mean by contravariant derivative? Do you mean covariant? What do you mean by those matrices? Are you saying that the components of T in the basis you're considering are (1,1)?
 
  • #3
I made a mistake I meant covariant. T is general tensor. I don't understand why
[tex]\frac{\partial \vec V}{\partial x^\beta}=V^\alpha_{;\beta} \vec e_{\alpha}[/tex]
can be associated with a (1,1) tensor
 
  • #4
A covariant derivative is per definition a derivative which transforms as a tensor. Loosely, the covariant derivative of a tensor T adds another covariant index, so if T is type (k,l) then the covariant derivative of T is type (k+1, l) (I always forget the convention, but here the k is the number of covariant indices).

Here's a nice exercise: you know how the components of a vector V tranform:

[tex]
V^{\mu'}(x') = \frac{\partial x^{\mu'}}{\partial x^{\nu}}V^{\nu}(x)
[/tex]

You also know how a partial derivative transforms:

[tex]
\frac{\partial}{\partial x^{\lambda'}} = \frac{\partial x^{\alpha}}{\partial x^{\lambda '}}\frac{\partial}{\partial x^{\alpha}}
[/tex]

Now calculate the transformation the components of the partial derivative of a vector:

[tex]
\frac{\partial}{\partial x^{\lambda'}}V^{\mu'}(x') = \frac{\partial x^{\alpha}}{\partial x^{\lambda '}}\frac{\partial}{\partial x^{\alpha}} [\frac{\partial x^{\mu'}}{\partial x^{\nu}}V^{\nu}(x)]
[/tex]

If you write this out, you'll see that this doesn't transform as a (1,1) tensor as you would naively expect on basis of the index structure of the expression. However, in derivatives you compare tensors at different points on the manifold and you need a certain prescription to perform this comparison: the connection [itex] \Gamma [/itex].

If you want to write things down with a basis, you can define the connection and the covariant derivative as

[tex]
\nabla_{\mu}e_{\nu} \equiv \Gamma^{\lambda}_{\mu\nu}e_{\lambda}
[/tex]

Here [itex]\nabla_{\mu} [/itex] means covariant derivation with respect to the basis vector

[tex]e_{\mu} = \partial_{\mu}[/tex]

This second-last formula states that the covariant derivative of the basis vector should be expressible in terms of your basis vectors. If you then write down a tensor in a certain coordinate basis, you can act on this tensor with the covariant derivative. For instance,

[tex]
\nabla_{\mu} (V) = \nabla_{\mu}(V^{\alpha} e_{\alpha}) = [(\nabla_{\mu}V^{\alpha})e_{\alpha} + V^{\alpha}\nabla_{\mu}e_{\alpha}]
[/tex]

Demanding that the covariant derivative acting on scalar functions gives the same result as a partial derivative (and some basic rules such that it obeys Leibnitz), you arrive at the same answer as in a component-only treatment.

Hopefully this makes things a bit clear :)
 
  • #5
I like the approach to covariant derivatives that starts with a connection. I'll quote myself (and fix a couple of mistakes at the same time):

Fredrik said:
Let V be the set of smooth vector fields on a manifold M. A connection is a map [itex]\nabla:V\times V\rightarrow V[/itex] such that

(i) [tex]\nabla_{fX+gY}Z=f\nabla_X Z+g\nabla_YZ[/tex]

(ii) [tex]\nabla_X(Y+Z)=\nabla_XY+\nabla_XZ[/tex]

(iii) [tex]\nabla_X(fY)=(Xf)Y+f\nabla_XY[/tex]

[itex]\nabla_XY[/itex] is the covariant derivative of Y in the direction of X. The covariant derivative operator corresponding to a coordinate system x is

[tex]\nabla_{\frac{\partial}{\partial x^\mu}[/tex]

The notation is often simplified to

[tex]\nabla_{\partial_\mu}[/tex]

or just [itex]\nabla_\mu[/itex].
The above only defines the action of [itex]\nabla_X[/itex] on vector fields, but note that condition (iii) above suggests a way to extend the definition to scalar fields. If we define

[tex]\nabla_Xf=Xf[/tex]

condition (iii) looks like the Leibnitz rule for derivatives:

[tex]\nabla_X(fY)=(\nabla_Xf)Y+f\nabla_XY[/tex]

So we choose to define [itex]\nabla_Xf[/itex] that way. Can we do something similar for covector fields? It turns out we can. Suppose that [itex]\omega[/itex] is a covector field. The closest thing to a Leibnitz rule we can get is this:

[tex]\nabla_X(\omega(Y))=(\nabla_X\omega)(Y)+\omega(\nabla_XY)[/tex]

so we choose to define [itex]\nabla_X\omega[/itex] by

[tex](\nabla_X\omega)(Y)=\nabla_X(\omega(Y))-\omega(\nabla_XY)[/tex]

for all Y. Note that this means that we define [itex]\nabla_X\omega[/itex] to be a covector field.

The same idea can be used to find the appropriate definition of [itex]\nabla_X[/itex] acting on an arbitrary tensor field. You can probably figure it out on your own.

Don't forget that the covariant derivative you're used to is the special case [itex]X=\partial_\mu[/itex].
 

1. What is a contravariant derivative tensor?

A contravariant derivative tensor is a mathematical object used in the study of differential geometry and tensor calculus. It is a generalization of the concept of a derivative to higher-dimensional spaces.

2. What is the purpose of a contravariant derivative tensor?

The purpose of a contravariant derivative tensor is to describe how a tensor field changes as one moves along a given direction in a curved space. It allows for the calculation of directional derivatives and is essential in understanding the geometric properties of a space.

3. How is a contravariant derivative tensor calculated?

A contravariant derivative tensor is calculated using the Christoffel symbols, which represent the connection between the local coordinates of a space and the global coordinates. The formula for calculating the contravariant derivative tensor involves taking partial derivatives of the tensor field and adding terms involving the Christoffel symbols.

4. What are some real-world applications of contravariant derivative tensors?

Contravariant derivative tensors have numerous applications in physics, particularly in the study of general relativity. They are used to describe the curvature of space-time and the behavior of particles in a gravitational field. They are also used in fluid mechanics, electromagnetism, and other areas of theoretical physics.

5. Are there any limitations to using contravariant derivative tensors?

One limitation of using contravariant derivative tensors is that they can be difficult to calculate, especially in higher dimensions. Additionally, they are only defined for smooth spaces and may not be applicable in more complex or discontinuous systems. Other methods, such as numerical calculations, may be necessary in these cases.

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