## Constrained Transport Electric Fields

I fixed some bugs in the CT electric fields kernel, added documentation to everything I’ve added over the last few weeks, and wrote tests for the CT electric fields kernel. While writing those tests I discovered an issue with which flags are used to compile the tests.

## Tests Compilation Issue

The tests were being compiled with the `-Ofast`

flag which in turn uses the `--ffinite-math-only`

. This flag caused all calls to `std::isnan`

and `std::isinf`

to be undefined. In practice they always returned false which effectively broke the handling of `Nans`

and `infs`

in `testingUtilities::ulpsDistanceDblwhich`

in turn is call by all of our FP64 comparison utilities. This has been fixed by settting `BUILD = DEBUG`

when building the tests.

Also, I refactored the `testingUtilities::nearlyEqualDbl`

function so that it always returns proper values of of `absoluteDiff`

and `ulpsDiff`

. Before it would only compute some of those values and then exit early if they were found to be passing. This could cause `ulpsDiff`

to be undefined when comparing small numbers. Now both `absoluteDiff`

and `ulpsDiff`

are computed first and then the results are checked. This is somewhat less efficient but will lead to more correct and expected behavior. This issue has been resolved with PR #144

## VL+CT Integrator

I finished the Van Leer + Constrained Transport integrator. Currently it only supports first order reconstruction of the conserved variables but with this done I should be able to run a fully functional MHD simulation. I’ll start on fixing bugs once I get finish the kernel for tracking magnetic field divergence.

## Magnetic Field Divergence Tracking & GPU Reductions

While Constrained Transport should be entirely divergence free the numerical approximations are not perfect and so we should regularly compute the divergence and check that it hasn’t risen above some negligible amount. The divergene is calculated with this equation

\[\begin{aligned} \left( \nabla \cdot B \right)^{n}_{i,j,k} = \frac{B^{n}_{x,i+1/2,j,k} - B^{n}_{x,i-1/2,j,k}}{\delta x} \\ + \frac{B^{n}_{y,i,j+1/2,k} - B^{n}_{y,i,j-1/2,k}}{\delta y} \\ + \frac{B^{n}_{z,i,j,k+1/2} - B^{n}_{z,i,j,k-1/2}}{\delta z}. \end{aligned}\]This is easy to calculate however the real value we need is the maximum divergence in the entire grid. MPI has a function for this and Cholla has a suitable wrapper to use once we’ve reduced the local grid to a single value. However, reducing the local grid to a single value isn’t easy. Next week I’m going to work on a parallel GPU reduction kernel/tools based off of this NVIDIA blog post. I should be able to write a couple of device functions that make it trivial to do a parallel reduction either on its own or at the end of a transform-reduce kernel.

## Other

- I added some utility functions for computing indices along with tests for those functions. PR #143
- Finished Beck 2015
- Read Morton et al. 2022