Given an infinite connected graph $G$ of bounded degree with vertex set $X$, let $P_x^n$ the time $n$ distribution of the simple random walk started at the vertex $x$ (so $P^n_x(y)$ is the probability that a simple random walk started at $x$ ends at $y$ after $n$ steps). Let further $$ H_n :=\displaystyle \sup_{x \in X} h(P_x^n), \qquad \eta_n := \displaystyle \inf_{x \in X} h(P_x^n) \quad \text{ and } \quad r_n := \displaystyle \sup_{x,y \in X} P_x^n(y). $$ Here $h(\mu) = \sum_y -\mu(y) \ln \mu(y)$ is the entropy of $\mu$. Given that for any measure $\mu$ one has $\displaystyle \sup_{y \in X} \mu(y) \geq e^{-h(\mu)}$, one gets the bound $r_n \geq e^{-H_n}$. One question is:
Question 1: what are upper bounds on $r_n$ in terms of $H_n$ and $h_n$?
Note that in the case of [Cayley graphs of] groups, there is such a bound (the sharpest version known to me is by Peres & Zheng). My question is for "generic" [infinite connected] graphs [of bounded degree].
There is a natural counterpart to the question (which is hopefully easier to get):
Question 2: what are [family of] examples where upper bounds of $r_n$ in terms of $H_n$ and $\eta_n$ are "bad"?
Of course "bad" is not well-defined, but in Cayley graphs it may happen that $r_n$ behaves roughly like $C_1e^{-C_2\sqrt{H_n}}$. I would expect much worse for a graph.
PS: if "generic" needed to be made explicit, then I would say something like: "no finitely generated subgroup of the subgroup of self quasi-isometries of the graph acts co-compactly".
PPS: any result with "lazy random walk" in place of "simple random walk" is also OK.