Consider switch to a max norm

[patrick-kidger]

At the moment, padding the state with constant values (zero vector field) means that rms_norm(state) -> 0 as this padding increases. This can cause issues with steady state detection, and with the nonlinear solve inside implicit stages, which end up producing less-meaningful estimates for being close to zero. Switching to a max norm, which is invariant to the number of dimensions, would fix this.

On the other hand there are classically good reasons for using an average norm, so it's not clear which is best.

Worth noting that whilst this padding is weird from the point of view of a numerical diffeq solver, it is a thing that users do in practice.