Derivative consisting Levi-Civita

In summary, the last line of the equation states that the derivative of the function with respect to the indices on the left-hand side is negative.
  • #1
vahdaneh
6
0
5.jpg

I've got here so far, but first of all I'm not sure if i did it right till the last line and second, if I've been right, i do not know what to do with the rest.

should i consider each of levi-civita parentheses in the last line zero?

and one additional question about the term in the first line parentheses, i wrote it to replace E.B, are the indices in their right place? i mean, should both of them be down indices?

i'll be really grateful
 
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  • #2
vahdaneh said:
View attachment 253290
I've got here so far, but first of all I'm not sure if i did it right till the last line and second, if I've been right, i do not know what to do with the rest.

should i consider each of levi-civita parentheses in the last line zero?

and one additional question about the term in the first line parentheses, i wrote it to replace E.B, are the indices in their right place? i mean, should both of them be down indices?

i'll be really grateful

I'd write

##\epsilon^{\alpha\beta\gamma\sigma} F_{\alpha\beta}F_{\gamma\sigma} = \epsilon^{\alpha\beta\gamma\sigma} \partial_{\alpha}A_{\beta} \partial_{\gamma}A_{\sigma} ## because the contraction with epsilon already takes into account the antisymmetrization. Doing the differentiation then leads to two terms,

##\epsilon^{\alpha\beta\gamma\sigma} \delta_{\alpha}^{\mu} \delta^{\theta}_{\beta} \partial_{\gamma}A_{\sigma} + \epsilon^{\alpha\beta\gamma\sigma} \partial_{\alpha}A_{\beta} \delta_{\gamma}^{\mu} \delta^{\theta}_{\beta} ##

From there on you can simplify.
 
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  • #3
haushofer said:
I'd write

##\epsilon^{\alpha\beta\gamma\sigma} F_{\alpha\beta}F_{\gamma\sigma} = \epsilon^{\alpha\beta\gamma\sigma} \partial_{\alpha}A_{\beta} \partial_{\gamma}A_{\sigma} ##
Just to mention that there should be a factor of 4 here since ##F_{\mu\nu} = \partial_\mu A_\nu - \partial_\nu A_\mu## leads to two terms per insertion of ##F##.
 
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  • #4
haushofer said:
I'd write

##\epsilon^{\alpha\beta\gamma\sigma} F_{\alpha\beta}F_{\gamma\sigma} = \epsilon^{\alpha\beta\gamma\sigma} \partial_{\alpha}A_{\beta} \partial_{\gamma}A_{\sigma} ## because the contraction with epsilon already takes into account the antisymmetrization. Doing the differentiation then leads to two terms,

##\epsilon^{\alpha\beta\gamma\sigma} \delta_{\alpha}^{\mu} \delta^{\theta}_{\beta} \partial_{\gamma}A_{\sigma} + \epsilon^{\alpha\beta\gamma\sigma} \partial_{\alpha}A_{\beta} \delta_{\gamma}^{\mu} \delta^{\theta}_{\beta} ##

From there on you can simplify.

6.jpg

yet i do not know in what other forms i can use the last line...
 
  • #5
[tex]\frac{\partial}{\partial (\partial_{\alpha}A_{\beta})} \left( \epsilon^{\mu\nu\rho\sigma}F_{\mu\nu}F_{\rho\sigma} \right) = 2 \frac{\partial}{\partial F_{\alpha \beta}} \left( \epsilon^{\mu\nu\rho\sigma}F_{\mu\nu}F_{\rho\sigma} \right) ,[/tex]
[tex]\frac{\partial}{\partial (\partial_{\alpha}A_{\beta})} \left( \epsilon^{\mu\nu\rho\sigma}F_{\mu\nu}F_{\rho\sigma} \right) = 2 \epsilon^{\mu\nu\rho\sigma} \left( \delta^{\alpha}_{\mu}\delta^{\beta}_{\nu} F_{\rho\sigma} + \delta^{\alpha}_{\rho} \delta^{\beta}_{\sigma} F_{\mu\nu}\right) = 4 \epsilon^{\alpha\beta\mu\nu}F_{\mu\nu}.[/tex]
 
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  • #6
vahdaneh said:
View attachment 253294
yet i do not know in what other forms i can use the last line...
In the last line use [tex]\epsilon^{\alpha\beta\mu\theta} = \epsilon^{\mu\theta\alpha\beta} ,[/tex] then use [tex]\epsilon^{\mu\theta\gamma\sigma}\partial_{\gamma}A_{\sigma} = \epsilon^{\mu\theta\beta\alpha}\partial_{\beta}A_{\alpha} = - \epsilon^{\mu\theta\alpha\beta}\partial_{\beta}A_{\alpha} .[/tex]
 
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  • #7
Orodruin said:
Just to mention that there should be a factor of 4 here since ##F_{\mu\nu} = \partial_\mu A_\nu - \partial_\nu A_\mu## leads to two terms per insertion of ##F##.
Ah, yes, those pesky numerical factors became a bit rusty since I left academia :P Thanks!
 
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Related to Derivative consisting Levi-Civita

1. What is the Levi-Civita derivative?

The Levi-Civita derivative, also known as the covariant derivative, is a mathematical operation used in differential geometry to measure the rate of change of a vector field along a given direction. It takes into account the curvature of the underlying space and is an important tool in general relativity and other areas of physics.

2. How is the Levi-Civita derivative defined?

The Levi-Civita derivative is defined as the sum of the partial derivative of a vector field with respect to a given coordinate and the connection coefficients, which represent the curvature of the underlying space. It is a tensor operation that is used to generalize the concept of differentiation to curved spaces.

3. What is the relationship between the Levi-Civita derivative and the Christoffel symbols?

The Christoffel symbols are the connection coefficients used in the definition of the Levi-Civita derivative. They represent the components of the curvature of the underlying space and are used to calculate the rate of change of a vector field along a given direction. The Levi-Civita derivative can be written in terms of the Christoffel symbols, making them closely related.

4. How is the Levi-Civita derivative related to the Riemann curvature tensor?

The Riemann curvature tensor is a mathematical object that describes the intrinsic curvature of a space. It is related to the Levi-Civita derivative through the Bianchi identity, which states that the covariant derivative of the Riemann tensor is equal to zero. This relationship is crucial in general relativity and other areas of physics.

5. What are some applications of the Levi-Civita derivative?

The Levi-Civita derivative has many applications in mathematics, physics, and engineering. It is used in differential geometry to study curved spaces, in general relativity to describe the curvature of spacetime, and in fluid mechanics to model the motion of fluids. It is also used in computer graphics and computer vision to analyze and manipulate geometric data.

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