Evaluate Covariant Derivative on Tensors

In summary, the author encountered a problem with a covariant derivative problem and does not know how to continue.
  • #1
Jonsson
79
0
Hello there,

Recently I encountered a type of covariant derivative problem that I never before encountered:

$$
\nabla_\mu (k^\sigma \partial_\sigma l_\nu)
$$

My goal: to evaluate this term

According to Carroll, the covariant derivative statisfies ##\nabla_\mu ({T^\lambda}_{\lambda \rho}) = {{\nabla(T)_\mu}^\lambda}_{\lambda \rho}\ \ (\dagger)## and also ## \nabla(T \otimes S) = (\nabla T)\otimes S + T \otimes (\nabla S) \ \ (\ddagger)##. We know that ##\partial \sigma## forms a basis, so therefore ##k^\sigma \partial_\sigma ## is a (1,0) tensor
$$
\nabla_\mu (\underbrace{k^\sigma \partial_\sigma}_{\equiv T} l_\nu) = \nabla_\mu (T l_\nu) \stackrel{(\dagger)}{=} \nabla(T l)_{\mu \nu} = [\nabla(T l)]_{\mu \nu} \stackrel{(\ddagger)}{=} [\nabla(T) \otimes l + T\otimes \nabla(l)]_{\mu \nu}
$$
But how do I continue from there? I want to distribute back the ## \mu \nu## and replace ## \otimes## with regular multiplication, but I don't know any algebra rules which applies, also my textbook doesn't help. I know that the tensors are multilinear, but its not quite what I need. How do I continue to evaluate ##\nabla_\mu (k^\sigma \partial_\sigma l_\nu)##?
 
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  • #2
Is ##k^\sigma\partial_\sigma## a scalar operator when applied to the tensor ##l_\nu##? I would think not?
 
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  • #3
Paul Colby said:
Is ##k^\sigma\partial_\sigma## a scalar operator when applied to the tensor ##l_\nu##? I would think not?
Great, I don't know. I am trying to understand how this all works. Would you like to explain some more?
 
  • #4
Jonsson said:
Would you like to explain some more?
This is the part I get in trouble with. The operator, ##\partial_\sigma##, I read as regular partial differentiation. When applied to a scalar ##\partial_\sigma \phi## yields a 4-vector. In fact ##\partial_\sigma = \nabla_\sigma## when acting on a scalar. If I wrote ##\nabla_\nu(k^\sigma\nabla_\sigma)l_\mu## I would just distribute chain rule the way one normally does with covariant derivatives.

##\nabla_\mu(k^\sigma\nabla_\sigma)l_\nu = (\nabla_\mu k^\sigma)(\nabla_\sigma l_\nu)+k^\sigma (\nabla_\mu\nabla_\sigma l_\nu)##
Now if I replace ##\nabla_\sigma = \partial_\sigma + \Gamma^._{\cdots}## where the ##\Gamma##'s are whatever that's needed to make things covariant, I could solve for the thing you are looking to evaluate.
 
  • #5
Jonsson said:
How do I continue to evaluate ##\nabla_\mu (k^\sigma \partial_\sigma l_\nu)##?
The simplest way is to treat the argument as a (covariant) vector with index ##\nu## and apply the rules found in the "examples" section of this Wiki page. I.e., $$\nabla_\mu (k^\sigma \partial_\sigma l_\nu) ~=~\partial_\mu (k^\sigma \partial_\sigma l_\nu) ~-~ \Gamma^\alpha_{~\mu\nu} k^\sigma \partial_\sigma l_\alpha ~.$$If you're a masochist, you could in fact evaluate it using the Leibniz product rule as
$$\nabla_\mu (k^\sigma \partial_\sigma l_\nu) ~=~ k^\sigma \nabla_\mu ( \partial_\sigma l_\nu) ~+~ (\nabla_\mu k^\sigma) ( \partial_\sigma l_\nu) ~=~ \dots$$ This is indeed equivalent to "treating the argument as a (covariant) vector with index ##\nu##".
(I've just now double-checked this, but if you want see my work you'll have to show me your attempt first. :oldbiggrin:)

If you're a truly psychotic masochist, you could even treat it as the covariant derivative of a 3-index quantity, provided you follow the rules carefully, and preserve ordering when using the Leibniz rule.

HTH.
 
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  • #6
strangerep said:
The simplest way is to treat the argument as a (covariant) vector with index
Adding to this, I think it is worth pointing out that the argument is not a covariant vector. To make it covariant, you would need ##k^\sigma\nabla_\sigma l_\nu## instead. As written, I am very sceptical regarding the origins of the expression itself. Of course, it might be a term in a larger covariant expression.
 
Last edited:
  • #7
Jonsson said:
Hello there,

Recently I encountered a type of covariant derivative problem that I never before encountered:

$$
\nabla_\mu (k^\sigma \partial_\sigma l_\nu)
$$

There is a problem with the expression [itex]k^\sigma \partial_\sigma l_\nu[/itex]. That isn't actually a tensor. This can be seen in two different ways:
  1. [itex]l_\nu[/itex] is a one-form, and you can't apply a partial derivative to a one-form. Partial derivatives can only apply to scalar fields.
  2. If you think of [itex]\partial_\sigma[/itex] as a basis vector, then [itex]k^\sigma \partial_\sigma[/itex] is just the vector [itex]\vec{k}[/itex] written in terms of components. So the expression [itex]k^\sigma \partial_\sigma l_\nu[/itex] is a vector acting on a one-form. How can a vector act on a one-form? Well, typically using covariant (or directional) derivatives: [itex]k^\sigma \nabla_\sigma l_\nu[/itex] makes sense, but [itex]k^\sigma \partial_\sigma l_\nu[/itex] doesn't.
 
  • #8
Shouldn't the title of this thread read "trying to understand covariant derivatives on non-tensors"? :P
 
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FAQ: Evaluate Covariant Derivative on Tensors

What is a covariant derivative on tensors?

A covariant derivative is a mathematical operation that extends the concept of differentiation to tensor fields. It takes into account the curvature of the space in which the tensors are defined and allows for the calculation of the change of tensors along a given path.

How is a covariant derivative calculated?

A covariant derivative is calculated using the Levi-Civita connection, which is a generalization of the usual derivative to curved spaces. This connection is defined by a set of coefficients that depend on the metric of the space in which the tensors are defined.

What is the difference between a covariant derivative and a partial derivative?

A partial derivative is a local operation that only takes into account the variation of a quantity in a specific direction. A covariant derivative, on the other hand, takes into account both the local variation and the curvature of the space in which the tensor is defined.

Why is the covariant derivative important in tensor calculus?

The covariant derivative is important because it allows for the formulation of equations that are invariant under coordinate transformations. This is essential in general relativity, where the laws of physics must hold in any coordinate system. It also allows for the calculation of quantities such as curvature and geodesic equations.

What are some applications of the covariant derivative in physics?

The covariant derivative has many applications in physics, particularly in the field of general relativity and differential geometry. It is used to define the curvature tensor, which describes the local curvature of spacetime, and to calculate geodesics, which are the paths that particles follow in curved space. It is also used in the study of fluid dynamics, where it can be used to describe the motion of fluids in curved spaces.

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