glancing at it, it seems good for nearby timepoints, but not so great
   for very distant timepoints.

   for distant timepoints, transformation of the described discrete
   brownian motion into a smooth distribution seems meaningful. this is
   probably pretty important in general.
   basically there are crux timeline junctures, where interaction between
   simulation components need to be handled as trees because they interact
   e.g. two asteroids colliding, but between them huge swaths of solvable
   timelines where sentient beings appear basically brownian.
   i'm feeling doing the trees of individual decisions anyway, but keeping
   the larger brownian ideas present and important.