Covariance in Equations: How to Identify and Understand It

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Homework Help Overview

The discussion revolves around identifying and understanding covariance in equations, particularly in the context of tensor analysis. Participants are exploring criteria for determining whether an equation is covariant based on its structure and the types of indices involved.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants discuss criteria for covariance, including the need for balanced tensor ranks and the same tensor quality on both sides of an equation. Questions arise regarding specific examples, particularly the equation A^{i}=F^{\mu i}B_{\mu}, and the implications of tensor behavior under coordinate transformations.

Discussion Status

The discussion is active, with participants providing explanations and seeking further clarification on specific examples. Some guidance has been offered regarding the criteria for covariance, but there is an ongoing exploration of the example equation and its implications.

Contextual Notes

Participants express a lack of understanding related to tensors and covariance, indicating that foundational knowledge may be a constraint in the discussion.

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How can you tell if an equation is covariant just by looking at it. Please try and keep explaniation to text more than equations.
 
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tiger_striped_cat said:
How can you tell if an equation is covariant just by looking at it. Please try and keep explaniation to text more than equations.

There are basically two criteria:
1.The equation must contain only quantities with the same type of greek/spacetime indices summed over.Wrt to indices,the equation must be 'balanced',that is the tensor rank of the RHS must be equal to the tensor rank of the LHS.
2.The sides of the equation must have the same 'tensor quality' (i made it up).You cannot have an equality between a tensor (e.g.in the LHS) and a nontensor (in the LHS).

Daniel.

PS.The equation
[tex]A^{i}=F^{\mu i}B_{\mu}[/tex]
is not covariant.
 
Thank you for your great explaniation. But could you explain the example:

[tex]A^{i}=F^{\mu i}B_{\mu}[/tex]


I think I'm having problems due to my lack of understanding with tensors and covariance, no fault of your explaniation.
 
It's basically the "F" 'animal'.The way it's given,it's not a tensor because:
a) one index takes 4 values and the other only 3.
b) both indices should behave the same at a general coordinate transformation,but the trouble is that one index transforms with the normal matrix (4*4),while the other with another one,which has only (3*3) components.

Daniel.
 

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