English

Favourite distances in high dimensions

Combinatorics 2015-02-02 v1 Metric Geometry

Abstract

Let SS be a set of nn points in dd-dimensional Euclidean space. Assign to each xSx\in S an arbitrary distance r(x)>0r(x)>0. Let er(x,S)e_r(x,S) denote the number of points in SS at distance r(x)r(x) from xx. Avis, Erd\"os and Pach (1988) introduced the extremal quantity fd(n)=maxxSer(x,S)f_d(n)=\max\sum_{x\in S}e_r(x,S), where the maximum is taken over all nn-point sets SS in dd-dimensional space and all assignments r ⁣:S(0,)r\colon S\to(0,\infty) of distances. We give a quick derivation of the asymptotics of the error term of fd(n)f_d(n) using only the analogous asymptotics of the maximum number of unit distance pairs in a set of nn points, which improves on previous results of Avis, Erd\"os and Pach (1988) and Erd\"os and Pach (1990). Then we prove a stability result for d4d\geq 4, asserting that if (S,r)(S,r) with S=n|S|=n satisfies er(S)=fd(n)o(n2)e_r(S)=f_d(n)-o(n^2), then, up to o(n)o(n) points, SS is a Lenz construction with rr constant. Finally we use stability to show that for nn sufficiently large (depending on dd) the pairs (S,r)(S,r) that attain fd(n)f_d(n) are up to scaling exactly the Lenz constructions that maximise the number of unit distance pairs with r1r\equiv 1, with some exceptions in dimension 4. Analogous results hold for the furthest neighbour digraph, where rr is fixed to be r(x)=maxySxyr(x)=\max_{y\in S} |xy| for xSx\in S.

Keywords

Cite

@article{arxiv.1108.4817,
  title  = {Favourite distances in high dimensions},
  author = {Konrad J. Swanepoel},
  journal= {arXiv preprint arXiv:1108.4817},
  year   = {2015}
}

Comments

17 pages

R2 v1 2026-06-21T18:54:36.465Z