Just looking for a simple example of why Differential Equations can be NP hard
Edit:
It appears that the answer below may be what I was looking for, but I am clarifying just in case:
Slides 58--72 here show a SAT reduction.
Background:
I remember reading somewhere that improving the approximated solutions to NP hard problems would lead to better approximate numeric solutions. (e.g. weather predictions via Differential Equations)
Is this true? and if so, then in a very general sense, I am trying to understand where the "NP hardness" arises in solving Differential Equations and other numeric problem solving algorithms, if at all.
here is a related link although it does not mention Differential Equations directly