I’ve worked in scientific computing for awhile now and there are countless subtle decisions often done in the implementation phase that, from a theoretical perspective, aren’t definitively answered by the science working behind the scenes. There’s often a gap in knowledge and implementers either hit those gaps by trial and error, luck, or insight. That’s my opinion, at least. So I don’t think it’s always “just an implementation problem” some will claim, as if the science is well understood and solved. Perhaps it is, but from my experience that tends to not be the case.