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Global rigidity of random graphs in mathbb{R}

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arxiv 2401.10803 v2 pith:XB7RDIVU submitted 2024-01-19 math.CO

Global rigidity of random graphs in mathbb{R}

classification math.CO
keywords distancesmathbbpointsrandomgraphgraphsreconstructingalmost
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We investigate the problem of reconstructing a set $P\subseteq \mathbb{R}$ of distinct points, where the only information available about $P$ consists of the distances between some of the pairs of points. More precisely, we examine which properties of the graph $G$ of known distances, defined on the vertex set $P$, ensure that $P$ can be uniquely reconstructed up to isometry. We prove that as soon as the random graph process has minimum degree 2, with high probability it can reconstruct all distances within any point set in $\mathbb{R}$. This resolves a conjecture of Benjamini and Tzalik. We also study the feasibility and limitations of reconstructing the distances within almost all points using much sparser random graphs. In doing so, we resolve a question posed by Gir\~ao, Illingworth, Michel, Powierski, and Scott.

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  1. Sharp threshold for reconstructing points on the line

    math.CO 2026-04 unverdicted novelty 8.0

    In the supercritical random graph on points on the line, the largest reconstructible subset is asymptotically the full size of the giant 2-core component.