Back when Genetic Algorithms were a hot topic I discovered that a large number of papers discussion optimal parameterisation of the the approach (mutation rate, cross-over, populations etc) were written using '1-Max' as the "problem" to be solved by the GA. (1-Max being attempting to make every bit of the candidate string a 1 rather than 0)

This literally made the GA encoding exactly the same as the solution and also very, very obviously favoured techniques that would MAKE ALL THE BITS 1!

This reminds me of this paper:

https://link.springer.com/article/10.1007/s10710-021-09425-5

They do the convergence analysis on the linear system Ax = 0, which means any iteration matrix (including a zero matrix) that produces shrinking numbers will converge to the obvious solution x = 0 and the genetic program just happens to produce iteration matrices with lots of zeros.