It may be _possible_ to have a verbose variable that makes it obvious what it corresponds to in the paper, but I've never seen it. That really rings like a No True Scotsman argument to my ear. I much prefer the creole of latex style naming that most researchers tend towards. For example, take this code/paper pair
https://www.web.stanford.edu/~boyd/l1_ls/
The first line in the main loop is
z = A*x-y;
Yes, they could have written residual = dictionary_matrix * optimization_variable - sensed_data
or some such nonsense, but it is just exhausting to read. Further, it's actually more confusing because it conflates an application (compressed sensing) with what is actually a generic algorithm for l1 regularized least squares. This is a persistent problem with verbose names. In the search for an expressive name, people reach for names from a specific problem. This is a violation of separation of concerns.I don't find your second example exhausting to read at all - in fact I find it far _easier_ to read, especially to an astute reader (who is trying to make sense of a particular scientific literature).
No person will have any idea what `z = A*x-y` could mean 'in context', when it's so damn abstract of a reference.
Brevity in variable names is horrendous when cross-checking against papers. It is also a waste of time for scientists to reiterate what the legends/variable names mean, especially when their code could have used clear, unambiguous, verbose names instead.
A verbose name makes which variable it corresponds to in the paper immediately obvious, and makes the code understandable.