Covariant derivative of the gradient

In summary, the covariant derivative is a vector that adds one to the covariant valence of a tensor. Its components can be calculated using the gradient and a connection, and it can be used to calculate the covariant derivative of a vector.
  • #1
eljose
492
0
If we define the Gradient of a function:

[tex] \uparrow u= Gra(f) [/tex]

wich is a vector then what would be the covariant derivative:

[tex] \nabla _{u}u [/tex]

where the vector u has been defined above...i know the covariant derivative is a vector but i don,t know well how to calculate it...thank you.
 
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  • #2
If u is defined as the gradient of a scalar, then u is a one-form. The components of the covariant derivative of u is, in a coordinate basis,

[tex]\nabla_iu_j=\partial_ju_j-\Gamma^k_{ij}u_k[/tex]

Where [itex]\Gamma[/itex] is your connection (Levi-Civita or whatever). To actually work it out you need (1) your components in some coordinate system and (2) a connection.

The covariant derivative adds one to your covariant valence. The covariant derivative of a (1 0) tensor, a vector, its covariant derivative is a (1 1) tensor.
 
  • #3


The covariant derivative of the gradient of a function can be written as:

\nabla _{u}u = \nabla _{u}(\nabla f)

This can be understood as the directional derivative of the gradient vector with respect to the vector u. In other words, it measures how the gradient changes in the direction of the vector u.

To calculate this, we can use the formula for the covariant derivative of a vector field:

\nabla _{u}v = \frac{\partial v}{\partial u} + \Gamma _{ij}^{k}u^{i}\frac{\partial v^{j}}{\partial x^{k}}

where \Gamma _{ij}^{k} are the Christoffel symbols and u^{i} and v^{j} represent the components of the vectors u and v respectively.

In this case, since the gradient vector is defined as \nabla f = \frac{\partial f}{\partial x^{i}}, we can substitute this into the formula above to get:

\nabla _{u}u = \frac{\partial (\frac{\partial f}{\partial x^{i}})}{\partial u} + \Gamma _{ij}^{k}u^{i}\frac{\partial (\frac{\partial f}{\partial x^{j}})}{\partial x^{k}}

Simplifying this, we get:

\nabla _{u}u = \frac{\partial ^{2}f}{\partial u\partial x^{i}}u^{i} + \Gamma _{ij}^{k}u^{i}\frac{\partial ^{2}f}{\partial x^{j}\partial x^{k}}

This is the covariant derivative of the gradient vector u with respect to the vector u. It is a vector field that measures the rate of change of the gradient vector in the direction of u.
 

Related to Covariant derivative of the gradient

1. What is the definition of covariant derivative of the gradient?

The covariant derivative of the gradient is a mathematical concept used in differential geometry to measure how a vector field changes as it moves along a curved surface. It is a way to generalize the traditional notion of differentiation to non-Euclidean spaces.

2. How is the covariant derivative of the gradient calculated?

The covariant derivative of the gradient is calculated using the Levi-Civita connection, which is a mathematical tool used to define parallel transport and measure the change of vectors along a curve or surface. The formula for the covariant derivative of the gradient involves the metric tensor and the Christoffel symbols.

3. What is the significance of the covariant derivative of the gradient in physics?

The covariant derivative of the gradient is used extensively in the field of general relativity, where it is used to describe the curvature of spacetime. It is also used in other areas of physics, such as fluid dynamics, electromagnetism, and quantum mechanics, to describe how physical quantities change in curved spaces.

4. How does the covariant derivative of the gradient relate to the concept of parallel transport?

The covariant derivative of the gradient is closely related to parallel transport, which is the process of moving a vector or tensor along a curve while keeping it parallel to its original orientation. The covariant derivative of the gradient is used to define parallel transport and measure the change of vectors along a curve or surface.

5. Can the covariant derivative of the gradient be extended to higher dimensions?

Yes, the concept of covariant derivative of the gradient can be extended to higher dimensions, such as in the case of manifolds with more than three dimensions. In these cases, the formula for the covariant derivative becomes more complex, but the underlying principles remain the same.

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