Dimensionally Exponential Lower Bounds on the Lp Norms of the Spherical Maximal Operator for Cartesian Powers of Finite Trees and Related Graphs
Abstract
Let T be a finite tree graph, TN be the Cartesian power graph of T, and dN be the graph distance metric on TN. Also let \[ SrN(x) := \v ∈ TN: dN(x,v) = r\ \] be the sphere of radius r centered at x and M be the spherical maximal averaging operator on TN given by \[ Mf(x) := r ≥ 0 \\ SrN(x) ≠ 1| SrN(x)| |Σ SrN(x) f(y)|. \] We will show that for any fixed 1 ≤ p ≤ ∞, the Lp operator norm of M, i.e. \[ \|M\|p := \|f\|p = 1 \|Mf\|p, \] grows exponentially in the dimension N. In particular, if r is the probability that a random vertex of T is a leaf, then \|M\|p ≥ r-N/p, 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 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 Lp bounds (for p > 1) are dimension-independent for finite cliques.
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