Directional covariant derivative

In summary, the covariant derivative of a type (a,b) tensor is a type (a,b+1) tensor, but the directional covariant derivative is still type (a,b) due to the inner product with the directional vector. The geodesic equation can be written as \nabla _{\vec{p}} \vec{p} = 0, where \nabla _{\vec{p}} \vec{p} is defined as the covariant derivative of the tangent vector along the curve. This can also be derived by setting the integrated proper time along the curve to be extremal. The relationship between parallel transport, geodesics and curvature is given by \nabla _ {\vec U
  • #1
snoopies622
840
28
Is this correct?

[tex]

\nabla _{\vec{p}} \vec{p} = (\nabla_a \vec{p} ) p^a

=< (\nabla_a p^0 ) p^a, (\nabla_a p^1 ) p^a , (\nabla_a p^2 ) p^a, (\nabla_a p^3 ) p^a >

[/tex]

(where the a's are summed from 0 to 3)
 
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  • #2
  • #3
Hi again, atyy. Perhaps I should re-formulate; I think this is right but I was hoping for confirmation:

The covariant derivative of a type (a,b) tensor is a type (a,b+1) tensor, but the directional covariant derivative is still type (a,b), since one takes the inner product of the covariant derivative and the directional vector, thereby losing the extra lower rank.

I was wondering about this because somewhere in Schutz's First Course he writes the geodesic equation simply as [tex]\nabla _{\vec{p}} \vec{p} = 0[/tex], and I wasn't certain what [tex]\nabla _{\vec{p}} \vec{p}[/tex] meant.
 
  • #4
I think it's something like this.

Expand u in basis vectors (linearity):
[tex]
\nabla _{\bold{u}} \bold{v}
= \nabla _{{u^i}\bold{e_i}} \bold{v}
={u^i} \nabla _{i} \bold{v}
[/tex]

Expand v in basis vectors (product rule or Leibniz property):
[tex]
{u^i} \nabla _{i} \bold{v}
={u^i} \nabla _{i} v^j\bold{e_j}
={u^i} (v^j\nabla _{i} \bold{e_j}+\bold{e_j}\nabla _{i} v^j})
[/tex]

Use definition of Christoffel symbols and covariant derivative of a scalar field:
[tex]
\begin{equation*}
\begin{split}
\{}{u^i} (v^j\nabla _{i} \bold{e_j}+\bold{e_j}\nabla _{i} v^j}) \\
&={u^i} (v^j\Gamma^{k}_{ij} \bold{e_k}+\bold{e_j}{\frac {\partial v^j}{\partial x_i}}) \\
&=({u^i}v^j\Gamma^{k}_{ij} \bold{e_k}+{u^i}\bold{e_j}{\frac {\partial v^j}{\partial x_i}}) \\
&=({u^i}v^j\Gamma^{k}_{ij} \bold{e_k}+{u^i}\bold{e_k}{\frac {\partial v^k}{\partial x_i}}) \\
&=({u^i}v^j\Gamma^{k}_{ij} \bold+{u^i}{\frac {\partial v^k}{\partial x_i}}){\bold{e_k}}
\end{equation*}
\end{split}
[/tex]

For Schutz's equation, let the unknown coordinates of the curve be [tex]x_i=x_i(\tau)[/tex].

Set [tex]u^i=v^i=({\frac {dx(\tau)}{d\tau}})^i={\frac {dx{_i}(\tau)}{d\tau}}[/tex] as the tangent vector along the curve.

For a geodesic, set the covariant derivative of the tangent vector along the curve to zero (ie. no acceleration):
[tex]{\frac {dx{_i}}{d\tau}}{\frac {dx{_j}}{d\tau}}\Gamma^{k}_{ij} \bold+{\frac {dx{_i}}{d\tau}}({\frac {d^2x{_k}}{d\tau^2}}{\frac {d\tau}{dx{_i}}})}={\frac {dx{_i}}{d\tau}}{\frac {dx{_j}}{d\tau}}\Gamma^{k}_{ij} \bold+{\frac {d^2x{_k}}{d\tau^2}}}=0[/tex]

We can also get the same differential equation by requiring the integrated proper time along the curve to be extremal. A given metric fixes the Christoffel symbols. Solving the differential equation will give you the coordinates of a geodesic [tex]x_i=x_i(\tau)[/tex].
 
  • #5
Need a day to process...
 
  • #6
Thanks, atyy; I follow now. And it turns out that the relationship I was looking for is right here in Schutz's section 6.4, "Parallel-transport, geodesics and curvature":

[tex]

\nabla _ {\vec U} \vec U = 0 \Rightarrow [/tex] "in component notation" [tex] U^{\beta} U^{\alpha} _{;\beta}=...=0[/tex]

I guess in general it pays to read page 166 before page 186.
 

What is a directional covariant derivative?

A directional covariant derivative is a mathematical tool used in differential geometry and vector calculus to measure the rate of change of a function in a particular direction. It takes into account the curvature and orientation of a surface, and is commonly used in fields such as physics and engineering.

How is a directional covariant derivative different from a regular derivative?

A directional covariant derivative is a more generalized form of a regular derivative. While a regular derivative measures the rate of change of a function in a specific direction, a directional covariant derivative takes into account the changes in direction and orientation of the surface on which the function is defined.

What is the notation used for a directional covariant derivative?

The notation used for a directional covariant derivative is ∇vf, where ∇ is the covariant derivative operator, v is the direction vector, and f is the function being differentiated.

When is a directional covariant derivative used in practical applications?

A directional covariant derivative is commonly used in fields such as physics and engineering to calculate the change of a physical quantity in a particular direction. It is also used in differential geometry to study the curvature and smoothness of surfaces.

What are some examples of applications of directional covariant derivatives?

Some examples of applications of directional covariant derivatives include calculating the rate of change of temperature in a particular direction on a curved surface, determining the flow of a fluid in a specific direction, and studying the curvature of a surface in differential geometry.

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