English

Hausdorff dimension of pinned distance sets and the $L^2$-method

Classical Analysis and ODEs 2019-11-06 v3 Combinatorics Metric Geometry

Abstract

We prove that for any ER2E\subset{\Bbb R}^2, dimH(E)>1\dim_{\mathcal{H}}(E)>1, there exists xEx\in E such that the Hausdorff dimension of the pinned distance set Δx(E)={xy:yE}\Delta_x(E)=\{|x-y|: y \in E\} is no less than min{43dimH(E)23,1}\min\left\{\frac{4}{3}\dim_{\mathcal{H}}(E)-\frac{2}{3}, 1\right\}. This answers a question recently raised by Guth, Iosevich, Ou and Wang, as well as improves results of Keleti and Shmerkin. (This version is already published on Proceeding AMS so I would like to leave it unchanged. However the statement in the abstract, which is the second part of Theorem 1.1, should be weakened a bit to: for any ϵ>0\epsilon>0 there exists xEx\in E such that the Hausdorff dimension of Δx(E)\Delta_x(E) is at least min{43dimH(E)23ϵ,1}\min\left\{\frac{4}{3}\dim_{\mathcal{H}}(E)-\frac{2}{3}-\epsilon, 1\right\}, and it implies the Hausdorff dimension of the distance set, Δ(E)={xy:x,yE}\Delta(E)=\{|x-y|:x,y\in E\}, is at least min{43dimH(E)23,1}\min\left\{\frac{4}{3}\dim_{\mathcal{H}}(E)-\frac{2}{3}, 1\right\}. There is no problem in the proof and the first part of Theorem 1.1. I apologize for being sloppy and would like to thank Yumeng Ou for pointing it out.)

Keywords

Cite

@article{arxiv.1810.08127,
  title  = {Hausdorff dimension of pinned distance sets and the $L^2$-method},
  author = {Bochen Liu},
  journal= {arXiv preprint arXiv:1810.08127},
  year   = {2019}
}