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Electronic Journal of Combinatorics
Article . 2025 . Peer-reviewed
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2024
License: CC BY
Data sources: Datacite
DBLP
Article . 2025
Data sources: DBLP
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Exponential Odd-Distance Sets under the Manhattan Metric

Authors: Alberto Espuny Díaz; Emma Hogan; Freddie Illingworth; Lukas Michel; Julien Portier; Jun Yan;

Exponential Odd-Distance Sets under the Manhattan Metric

Abstract

We construct a set of $2^n$ points in $\mathbb{R}^n$ such that all pairwise Manhattan distances are odd integers, which improves the recent linear lower bound of Golovanov, Kupavskii and Sagdeev. In contrast to the Euclidean and maximum metrics, this shows that the odd-distance set problem behaves very differently to the equilateral set problem under the Manhattan metric. Moreover, all coordinates of the points in our construction are integers or half-integers, and we show that our construction is optimal under this additional restriction.

Keywords

Mathematics - Metric Geometry, FOS: Mathematics, Mathematics - Combinatorics, Metric Geometry (math.MG), Combinatorics (math.CO)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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