Dimensionally Exponential Lower Bounds on the Norms of the Spherical Maximal Operator for Cartesian Powers of Finite Trees and Related Graphs
arXiv:1509.02843
Abstract
Let be a finite tree graph, be the Cartesian power graph of , and be the graph distance metric on . Also let \[ \mathbb S_r^N(x) := \{v \in T^N: d^N(x,v) = r\} \] be the sphere of radius centered at and be the spherical maximal averaging operator on given by \[ Mf(x) := \sup_{\substack{r \geq 0 \\ \mathbb S_r^N(x) \neq \emptyset}} \frac{1}{|\mathbb S_r^N(x)|} |\sum_{\mathbb S_r^N(x)} f(y)|. \] We will show that for any fixed , the operator norm of , i.e. \[ \|M\|_p := \sup_{\|f\|_p = 1} \|Mf\|_p, \] grows exponentially in the dimension . In particular, if is the probability that a random vertex of is a leaf, then , although this is not a sharp bound. This exponential growth phenomenon extends to a class of graphs strictly larger than trees, which we will call \emph{global antipode graphs}. This growth result stands in contrast to the work of Greenblatt, Harrow, Kolla, Krause, and Schulman that proved that the spherical maximal bounds (for ) are dimension-independent for finite cliques.