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Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia, 2022, Volume 506, Pages 45–48
DOI: https://doi.org/10.31857/S2686954322050101
(Mi danma296)
 

MATHEMATICS

Odd-distance sets and right-equidistant sequences in the maximum and Manhattan metrics

A. I. Golovanova, A. B. Kupavskiiab, A. A. Sagdeeva

a Moscow Institute of Physics and Technology, Moscow, Russia
b G-SCOP, Université Grenoble Alpes, CNRS, Франция
References:
Abstract: We solve two related extremal-geometric questions in the $n$-dimensional space $\mathbb{R}^n_\infty$ equipped with the maximum metric. First, we prove that the maximum size of a right-equidistant sequence of points in $\mathbb{R}^n_\infty$ equals 2$^{n+1}$–1. A sequence is right-equidistant if each of the points is at the same distance from all the succeeding points. Second, we prove that the maximum number of points in $\mathbb{R}^n_\infty$ with pairwise odd distances equals 2$^n$. We also obtain partial results for both questions in the $n$-dimensional space $\mathbb{R}^n_1$ with the Manhattan distance.
Keywords: maximum metric, Manhattan metric, equilateral dimension, odd-distance sets, right-equidistant sequences.
Funding agency Grant number
Russian Science Foundation 22-21-00368
This work was supported by the Russian Science Foundation, grant no. 22-21-00368.
Presented: V. V. Kozlov
Received: 17.05.2022
Revised: 25.06.2022
Accepted: 27.07.2022
English version:
Doklady Mathematics, 2022, Volume 106, Issue 2, Pages 340–342
DOI: https://doi.org/10.1134/S106456242205012X
Bibliographic databases:
Document Type: Article
UDC: 514.177.2
Language: Russian
Citation: A. I. Golovanov, A. B. Kupavskii, A. A. Sagdeev, “Odd-distance sets and right-equidistant sequences in the maximum and Manhattan metrics”, Dokl. RAN. Math. Inf. Proc. Upr., 506 (2022), 45–48; Dokl. Math., 106:2 (2022), 340–342
Citation in format AMSBIB
\Bibitem{GolKupSag22}
\by A.~I.~Golovanov, A.~B.~Kupavskii, A.~A.~Sagdeev
\paper Odd-distance sets and right-equidistant sequences in the maximum and Manhattan metrics
\jour Dokl. RAN. Math. Inf. Proc. Upr.
\yr 2022
\vol 506
\pages 45--48
\mathnet{http://mi.mathnet.ru/danma296}
\crossref{https://doi.org/10.31857/S2686954322050101}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=4531982}
\elib{https://elibrary.ru/item.asp?id=49787600}
\transl
\jour Dokl. Math.
\yr 2022
\vol 106
\issue 2
\pages 340--342
\crossref{https://doi.org/10.1134/S106456242205012X}
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