How do I calculate Lie derivation of a metric?

In summary, the author is trying to find the Lie derivative of a metric along a vector. He finds an example in a book and calculates it using the formula for each component.
  • #1
dingo_d
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Homework Statement



I've searched everywhere, and I cannot find an example of calculation of Lie derivation of a metric.

If I have some vector field [itex]\alpha[/itex], and a metric [itex]g[/itex], a lie derivative is (by definition, if I understood it):

[itex]\mathcal{L}_\alpha g=\nabla_\mu \alpha_\nu+\nabla_\nu \alpha_\mu[/itex]

So if my vector field is given in this form (polar coordinates for instance):

[itex]\alpha=r\sin^2\theta \partial_t+r\partial_\varphi[/itex]

(this is something I made up btw), so if I got this right (and I'm not sure, that's why I'm asking) I should find the Christoffel symbols from my metric, and use the definition of covariant derivative, and just calculate term by term (for [itex]\mu,\ \nu=t,\ r,\ \theta,\ \varphi[/itex])?

In that case, is [itex]\alpha_t=r\sin^2\theta[/itex] ? And so on? Or did I missed the point entirely, because I'm at loss :\
 
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  • #2
I think you more or less got it, although I agree it's pretty confusing to think about Lie derivatives of the metric. The definition of Lie derivative is I guess usually something like
[tex] \mathcal{L}_\alpha(g_{\mu \nu}) = V^\lambda \nabla_\lambda g_{\mu \nu} + g_{\nu \lambda} \nabla_\mu \alpha^\lambda + g_{\mu \lambda} \nabla_\nu \alpha^\lambda [/tex] and using the fact that covariant derivative of the metric vanishes, you get the form [itex] \mathcal{L}_\alpha(g_{\mu \nu}) = \nabla_\mu \alpha_\nu + \nabla_\nu \alpha_\mu [/itex]
 
  • #3
The reason that is confusing me is that I have a vector field given in the form I've mentioned, and I have a nondiagonal metric, and I'm trying to get the same result that I found in one article, and I can't.

Here: http://arxiv.org/abs/0908.0184 he makes a Lie derivative along a diffeomorphism [itex]\xi[/itex] of the metric, and he gets a 4x4 matrix. I tried my 'reasoning' and I got a scalar, so I must be doing something wrong :\
 
  • #4
I think the indices are the confusing part here -- you forgot them on the left side on your expression, but it's clear when you write it out, that the Lie derivative of a rank n tensor is also a rank n tensor. Not sure what you mean by your reasoning giving you a scalar. [itex] \nabla_\mu \alpha_\nu + \nabla_\nu \alpha_\mu [/itex] is very manifestly a tensor.
 
  • #5
Hmmm then I definitely did something wrong :\

I found an example of Lie derivative of a metric of 3 sphere, along some vector... I'll try to follow that, and see that I'll get...
 
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  • #6
Ok, I am in a bit of a problem here. I found one example of Lie derivative of a vector, along another vector on a sphere. And there was given the formula for each of the component. Here I would have (if I'm correct):

[itex]\mathcal{L}_\xi g_{\mu \nu}=\nabla_\mu \xi_\nu+\nabla_nu\xi_\mu=\frac{\partial \xi_\nu}{\partial x^\mu}-\Gamma^\rho_{\mu\nu}\xi^\rho+\frac{\partial \xi_\mu}{\partial x^\nu}-\Gamma^\sigma_{\nu\mu}\xi^\sigma[/itex]

right?

So I say, that that new tensor I get by doing a Lie derivative, let's call it a, with components [itex]a_{\mu\nu}[/itex] is given by above formula, by putting all the possible combinations for [itex]\mu\nu[/itex] ([itex]\tau,\ r,\ \theta,\ \varphi[/itex])?

EDIT:

I tried with one component, and I didn't get the answer like in article :\ so I must be doing something wrong... again :(
 
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  • #7
Found it! Finally! I did some digging and found a great book called Geometrical methods of
mathematical physics by Bernard Shutz, and in it a proper way to calculate the Lie derivative of a metric, and I am getting good results ^^

I'm so happy right now! Thanks for all the help :)
 

1. What is the concept of Lie derivation of a metric?

Lie derivation of a metric is a mathematical process used to calculate how a metric tensor, which is a mathematical object that describes the geometry of a space, changes along a given direction. It involves the use of Lie brackets, which measure the difference between two vector fields, and can be used to determine how the metric tensor changes under a given flow.

2. Why is Lie derivation of a metric important in science?

Lie derivation of a metric is important in science because it helps us understand the behavior of physical systems in curved spaces. This is particularly useful in fields such as general relativity, where the concept of spacetime curvature is central to understanding the behavior of massive objects.

3. How does Lie derivation of a metric relate to differential geometry?

Lie derivation of a metric is a fundamental concept in differential geometry, which is the branch of mathematics that studies the properties of geometric objects such as curves and surfaces. It provides a way to determine how the curvature of a space changes in different directions, which is important in understanding the overall geometry of a space.

4. Can Lie derivation of a metric be applied to any type of space?

Yes, Lie derivation of a metric can be applied to any type of space, including Euclidean spaces, curved spaces, and spaces with non-Euclidean geometries. It is a general concept that can be used to study the behavior of metric tensors in any type of space.

5. What are some real-world applications of Lie derivation of a metric?

Lie derivation of a metric has numerous real-world applications, particularly in fields such as physics and engineering. It is used to describe the behavior of physical systems in curved spaces, such as the motion of planets in the solar system. It is also used in the study of black holes and other astrophysical phenomena, as well as in the design of advanced technologies such as GPS systems.

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