Hi deal.ii community,

I also have a little question about postprocessing in different spaces. I 
am post processing two solutions of the same problem but solved in two 
different (pairs of) spaces. One quantity, for example, is called u and is 
either in H(curl) or in H(div) depending on the form of the problem. 
Another is sigma and it is either in H^1 or in H(curl), respectively.

I need to compute things that involve the divergence of u when u is in 
H(div) or the curl when u is in H(curl). Both things I do using the 
DataPostprocessor class with entries of the (matrix valued) gradient of u 
but I don't know the internals.

My problem ist that when comparing quantities that should be similar 
according to the math then I get differences that are too large 
(intuitively). 

The thing is that when I have a quantity that is in H(curl) using Nedelec 
approximation then I can nicely take the curl but divergence will be zero 
by construction. Same if u is in H(div) with Raviart-Thomas approximation 
(then the curl is zero by construction). How is the computation of the 
gradient done internally?

Best,
Konrad

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