This may be a rather naive question, as I've never seriously considered a modern take on analog computers with differentiable signals, but intuitively it's easy to see qualitative advantages in algorithms based on differential calculus, Fourier analysis, etc. What's less obvious to me is how such machines would do at fundamentally discrete tasks.
For a trivially simple concrete example, consider the task of computing the results of the SHA-256 hashing algorithm, which is primarily bottlenecked by bit shifts and rotates on integers. How would your analog machine compare to conventional digital computers? Is there any literature on this?
> What's less obvious to me is how such machines would do at fundamentally discrete tasks.
I might be talking out of my butt but fundamentally I think that eventually we'll realize that a lot of the currently supposedly solved problems might need to be rethought. I'm inclined to believe that hashing falls under these but don't quote me on that.
As for literature, I can't recommend anything in particular. But there's something on amazon, arxiv etc. I'm not sure what part of this are you most interested in, I guess what you are talking about could be complexity?
For a trivially simple concrete example, consider the task of computing the results of the SHA-256 hashing algorithm, which is primarily bottlenecked by bit shifts and rotates on integers. How would your analog machine compare to conventional digital computers? Is there any literature on this?