We introduce a framework for exploiting local central limit theorems as algorithmic tools. As applications, for general graphs $G$ with bounded maximum degree $\Delta$, we provide a deterministic fully polynomial time approximation scheme (FPTAS) (respectively, a quasi-linear time randomized algorithm) to count (respectively, sample from the uniform distribution on):
(i) matchings of a given...