Tensors and vector derivatives

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Discussion Overview

The discussion revolves around the concepts of covariant derivatives, Christoffel symbols, and the nature of tensor derivatives, particularly focusing on the relationship between covariant vectors and second-order tensors. Participants explore the implications of taking derivatives in curvilinear coordinates and the conditions under which certain mathematical objects can be classified as tensors.

Discussion Character

  • Technical explanation, Conceptual clarification, Debate/contested

Main Points Raised

  • Some participants express confusion regarding how the derivative of a covariant vector (first-order tensor) can be considered a second-order tensor.
  • One participant clarifies that the definition implies each component of the rank-2 tensor can be computed in a specific coordinate system, where the covariant vector components are functions of the coordinates.
  • Another participant argues that the partial derivative of a vector with respect to spatial position is not a tensor but a vector, emphasizing the need to account for changes in unit vectors in curvilinear coordinates.
  • It is noted that while the partial derivative of a vector is not a tensor, applying the gradient operator to a vector results in a second-order tensor.
  • Some participants discuss the implications of covariant derivatives in general manifolds, stating that the covariant derivative of a vector field with respect to another vector field yields another vector field.
  • There is mention of specific cases where the partial derivative of a vector field can be considered a tensor, particularly in inertial frames with standard coordinates in special relativity.
  • One participant introduces the concept of a linear operator mapping a vector to another vector, questioning whether this object can be classified as a tensor due to its transformation properties.
  • A reference to the tidal tensor is made, illustrating its application in gravitational contexts.

Areas of Agreement / Disagreement

Participants express differing views on the classification of derivatives as tensors, with some agreeing that the covariant derivative is a rank-2 tensor while others maintain that partial derivatives do not meet tensor criteria. The discussion remains unresolved regarding the classification of certain mathematical objects and their properties.

Contextual Notes

Participants highlight the importance of coordinate systems and the behavior of unit vectors in curvilinear coordinates, which complicates the classification of derivatives. There are also references to specific mathematical conditions under which certain derivatives can be considered tensors.

nigelscott
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I am trying to understand the notion of a covariant derivative and Christoffel symbols. The proof I am looking at starts out with defining a tensor, Tmn = ∂Vm/∂xn where V is a covariant vector. I am having a mental block with regard to the indeces. How is it that the derivative of a covariant vector (1st order tensor) be consider to be a 2nd order tensor?
 
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[tex] T_{mn} = \left[ \begin{array}{cc} \frac{\partial V_0}{\partial x^0} & \frac{\partial V_0}{\partial x^1} & \frac{\partial V_0}{\partial x^2} & \frac{\partial V_0}{\partial x^3} \\<br /> \frac{\partial V_1}{\partial x^0} & \frac{\partial V_1}{\partial x^1} & \frac{\partial V_1}{\partial x^2} & \frac{\partial V_1}{\partial x^3} \\<br /> \frac{\partial V_2}{\partial x^0} & \frac{\partial V_2}{\partial x^1} & \frac{\partial V_2}{\partial x^2} & \frac{\partial V_2}{\partial x^3} \\<br /> \frac{\partial V_3}{\partial x^0} & \frac{\partial V_3}{\partial x^1} & \frac{\partial V_3}{\partial x^2} & \frac{\partial V_3}{\partial x^3} \end{array} \right][/tex]
 
Last edited:
nigelscott said:
I am trying to understand the notion of a covariant derivative and Christoffel symbols. The proof I am looking at starts out with defining a tensor, Tmn = ∂Vm/∂xn where V is a covariant vector. I am having a mental block with regard to the indeces. How is it that the derivative of a covariant vector (1st order tensor) be consider to be a 2nd order tensor?

It's not. The definition is saying that each of the 16 components of this rank-2 tensor can be calculated in a given coordinate system by applying this rule for computing them. That works fine because in that coordinate system each of the Vm can be written as a function of the xn.
 
nigelscott said:
I am trying to understand the notion of a covariant derivative and Christoffel symbols. The proof I am looking at starts out with defining a tensor, Tmn = ∂Vm/∂xn where V is a covariant vector. I am having a mental block with regard to the indeces. How is it that the derivative of a covariant vector (1st order tensor) be consider to be a 2nd order tensor?

The partial derivative of a vector wrt spatial position is not a tensor, it's a vector. In curvilinear coordinates, the coordinate directions change with spatial position. Unit vectors (or coordinate basis vectors) therefore change with spatial position. Since a vector can be expressed as a linear sum of components times unit vectors (or coordinate basis vectors), if you are taking the partial derivative of a vector wrt to spatial position, you need to account for the changes in direction of the unit vectors (or coordinate basis vectors) as well as the changes in magnitude of the coordinate basis vectors. This is where the christoffel symbols come in. While the partial derivative of a vector wrt spatial position is not a tensor, the gradient vector operator applied to a vector yields a second order tensor.
 
Chestermiller said:
The partial derivative of a vector wrt spatial position is not a tensor, it's a vector. In curvilinear coordinates, the coordinate directions change with spatial position. Unit vectors (or coordinate basis vectors) therefore change with spatial position. Since a vector can be expressed as a linear sum of components times unit vectors (or coordinate basis vectors), if you are taking the partial derivative of a vector wrt to spatial position, you need to account for the changes in direction of the unit vectors (or coordinate basis vectors) as well as the changes in magnitude of the coordinate basis vectors. This is where the christoffel symbols come in. While the partial derivative of a vector wrt spatial position is not a tensor, the gradient vector operator applied to a vector yields a second order tensor.

In general manifolds or general coordinates, the partial of a vector field with respect coordinates is a 'nothing'. The covariant derivative with respect to coordinates is rank two tensor. The covariant derivative of one vector field with respect to another vector field is yet another vector field.

In coordinates on a flat manifold chosen such that the connection vanishes globally, partial derivative of vector by coordinates is tensor. This is obviously the case in all inertial frames (with standard coordinates) in SR.
 
Chestermiller said:
The partial derivative of a vector wrt spatial position is not a tensor, it's a vector.

True, but irrelevant. [itex]\nabla_a[/itex], the covariant derivative operator, is a different notation for the gradient operator [itex]\nabla[/itex]

The major difference is the added subscript - this makes it clearer that the covariant derivative operator [itex]nabla_a[/itex] adds one rank to any tensor it operates on.

The gradient of a vector field is a rank 2 tensor aka a matrix, sometimes called the Jacobian matrix, see for instance http://en.wikipedia.org/w/index.php?title=Gradient&oldid=508417646#Gradient_of_a_vector

For a specific gravity related example, consider the "tidal tensor". The tidal tensor is useful for getting the tidal stress on a rigid body, for instance.

http://en.wikipedia.org/w/index.php?title=Tidal_tensor&oldid=332450104

Thus if U is a scalar valued potential function , the Newtonian potential one can write

[tex]F_b = \nabla_b U[/tex]
[tex]T_{ab} = \nabla_a F_b = \nabla_a \nabla_b U[/tex]

where T is the tidal tensor.

Note that
[itex]\nabla_a = \partial_a[/itex] only in Cartesian coordinates.
 
Indeed, in this case, there is a well-defined (though not covariant) linear operator mapping a vector to a vector [itex]\underline T(a) = \partial [V(x) \cdot a][/itex] where [itex]\partial[/itex] is the vector partial derivative operator. This operator has components [itex]\underline T(e_m) \cdot e_n \equiv T_{mn}[/itex]. It should be clear that to fully describe this linear operator, there are two free vectors (or, just using the basis, there are two indices).

Edit: for exactly the reasons described, though, I wouldn't call this object a tensor because it does not obey the tensor transformation laws. But that's not a difficult fix, either. Just replace [itex]\partial[/itex] with [itex]\nabla[/itex], the covariant derivative.
 
Last edited:
Thanks for all your replies. I think I understand it now. pervect's first response cleared up the confusion.
 

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