Tensor differentiation. Help with a step.

In summary, the conversation revolves around the confusion of the use of covariant and ordinary derivatives in general relativistic formalism. The speaker is trying to understand how a covariant derivative appeared in the equation and whether it is the same as an ordinary derivative when applied to a scalar quantity. The expert provides a summary of the steps to get from equation (32) to equation (34) using the product rule and the properties of tensors. The expert also explains that there is no difference between an ordinary and covariant derivative when applied to a scalar quantity.
  • #1
Sagar_C
30
1
I am not very used to jugglery of tensors...I am learning it all now-a-days...I am trying to read a paper...and stuck at a point..:( ...It will be of great help if someone could help me get at eqn (34) from eqn (32) (cf. attached.) d/d\tau=u^\alpha\partial_\alpha (I think) and semi-colon is for covariant derivative and "[]" are for cyclic permutation of indices just like in Bianci relation.

P.S.: Hope I am not breaking any forum rules as this probably doesn't count as homework.
 

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  • #2
Sagar_C said:
I am not very used to jugglery of tensors...I am learning it all now-a-days...I am trying to read a paper...and stuck at a point..:( ...It will be of great help if someone could help me get at eqn (34) from eqn (32) (cf. attached.) d/d\tau=u^\alpha\partial_\alpha (I think) and semi-colon is for covariant derivative and "[]" are for cyclic permutation of indices just like in Bianci relation.

P.S.: Hope I am not breaking any forum rules as this probably doesn't count as homework.

Hmm. It doesn't seem to be a very big gap.

If [itex]Q[/itex] is a function of coordinates, then [itex]\dfrac{d}{d\tau} Q = \dfrac{dx^{\gamma}}{d\tau} \nabla_{\gamma} Q[/itex]. So in the particular case [itex]Q = w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}[/itex], we use the product rule to get
[itex]\dfrac{d}{d\tau}(w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}) =
((\nabla_{\gamma} w_{\alpha \beta}) \xi^{\alpha}\eta^{\beta}
+ w_{\alpha \beta} (\nabla_{\gamma} \xi^{\alpha}) \eta^{\beta}
+ w_{\alpha \beta} \xi^{\alpha} (\nabla_{\gamma} \eta^{\beta})) \dfrac{dx^{\gamma}}{d\tau}[/itex]

Using the semicolon notation, and using [itex]\dfrac{dx^{\gamma}}{d\tau}= u^{\gamma}[/itex], this becomes:

[itex]\dfrac{d}{d\tau}(w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}) =
(w_{\alpha \beta ; \gamma}\ \xi^{\alpha}\ \eta^{\beta}
+ w_{\alpha \beta}\ \xi^{\alpha}_{; \gamma}\ \eta^{\beta}
+ w_{\alpha \beta}\ \xi^{\alpha}\ \eta^{\beta}_{; \gamma}) u^{\gamma}[/itex]

The last step doesn't have anything to do with differentiation; it's just a fact about tensors: If [itex]w_{\alpha \beta ; \gamma}[/itex] is anti-symmetric in the first two indices, then [itex]w_{\alpha \beta ; \gamma} = 3 w_{[\alpha \beta ; \gamma]} - w_{\gamma \alpha ; \beta} - w_{\beta \gamma ; \alpha}[/itex]
 
  • #3
stevendaryl said:
Hmm. It doesn't seem to be a very big gap.

If [itex]Q[/itex] is a function of coordinates, then [itex]\dfrac{d}{d\tau} Q = \dfrac{dx^{\gamma}}{d\tau} \nabla_{\gamma} Q[/itex]. So in the particular case [itex]Q = w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}[/itex], we use the product rule to get
[itex]\dfrac{d}{d\tau}(w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}) =
((\nabla_{\gamma} w_{\alpha \beta}) \xi^{\alpha}\eta^{\beta}
+ w_{\alpha \beta} (\nabla_{\gamma} \xi^{\alpha}) \eta^{\beta}
+ w_{\alpha \beta} \xi^{\alpha} (\nabla_{\gamma} \eta^{\beta})) \dfrac{dx^{\gamma}}{d\tau}[/itex]

Using the semicolon notation, and using [itex]\dfrac{dx^{\gamma}}{d\tau}= u^{\gamma}[/itex], this becomes:

[itex]\dfrac{d}{d\tau}(w_{\alpha \beta} \xi^{\alpha}\eta^{\beta}) =
(w_{\alpha \beta ; \gamma}\ \xi^{\alpha}\ \eta^{\beta}
+ w_{\alpha \beta}\ \xi^{\alpha}_{; \gamma}\ \eta^{\beta}
+ w_{\alpha \beta}\ \xi^{\alpha}\ \eta^{\beta}_{; \gamma}) u^{\gamma}[/itex]

The last step doesn't have anything to do with differentiation; it's just a fact about tensors: If [itex]w_{\alpha \beta ; \gamma}[/itex] is anti-symmetric in the first two indices, then [itex]w_{\alpha \beta ; \gamma} = 3 w_{[\alpha \beta ; \gamma]} - w_{\gamma \alpha ; \beta} - w_{\beta \gamma ; \alpha}[/itex]

Many thanks. Actually, I should have been more specific. What I am really confused with is how covariant derivative appeared. The source of my confusion is that earlier in the text it seemed to be defined that "d/d\tau" is for simple derivative (see attachment 1) and "D/d\tau" is for the covariant one (attachment 2)! And all the time they are in general relativistic formalism...

P.S.: Is it because the term which is being differentiated is actually a scalar and so ordinary or covariant derivatives are just the same?
 

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Last edited:
  • #4
Sagar_C said:
Many thanks. Actually, I should have been more specific. What I am really confused with is how covariant derivative appeared. The source of my confusion is that earlier in the text it seemed to be defined that "d/d\tau" is for simple derivative (see attachment 1) and "D/d\tau" is for the covariant one (attachment 2)! And all the time they are in general relativistic formalism...

P.S.: Is it because the term which is being differentiated is actually a scalar and so ordinary or covariant derivatives are just the same?

Right. If you are taking the derivative of a scalar quantity, then there is no difference between an ordinary derivative and a covariant derivative.
 
  • #5
Edited: Wrong post! Sorry!
 
Last edited:

Related to Tensor differentiation. Help with a step.

1. What is tensor differentiation?

Tensor differentiation is a mathematical operation that allows us to find the rate of change of a tensor, which is a multi-dimensional object, with respect to one or more independent variables.

2. How is tensor differentiation different from scalar differentiation?

Tensor differentiation involves finding the derivative of a tensor, which is a multi-dimensional object, while scalar differentiation involves finding the derivative of a single variable. Tensor differentiation also requires the use of special rules and formulas that are different from those used in scalar differentiation.

3. Why is tensor differentiation important in scientific research?

Tensor differentiation is important in scientific research because tensors are commonly used to represent physical quantities in fields such as physics, engineering, and computer science. By finding the rate of change of these tensors, we can better understand the behavior of complex systems and make more accurate predictions.

4. How can I differentiate a tensor step by step?

To differentiate a tensor step by step, you first need to determine the independent variables and the dependent tensors. Then, you can use the appropriate tensor differentiation rules, such as the product rule or chain rule, to find the derivatives of each component of the tensor. Finally, you can combine the derivatives to obtain the final tensor derivative.

5. Are there any tools or software that can help with tensor differentiation?

Yes, there are various tools and software that can assist with tensor differentiation, such as Mathematica, MATLAB, and TensorFlow. These programs have built-in functions and algorithms for performing tensor differentiation, making the process more efficient and accurate.

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