Reconstructing a point set from a random subset of its pairwise distances

Let V be a set of n points on the real line. Suppose that each pairwise distance isknown independently with probability p. How much of V can be reconstructed up to isometry? Weprove that p = (log n)/n is a sharp threshold for reconstructing all of V , which improves a resultof Benjamini and Tzalik. This follows from a hitting time result for the random process where thepairwise distances are revealed one by one uniformly at random. We also show that 1/n is a weakthreshold for reconstructing a linear proportion of V.

Publication Details

Journal
UCL Discovery (University College London)
Published
2024-12-31
Primary Topic
Gene expression and cancer classification
Type
article
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article

Reconstructing a point set from a random subset of its pairwise distances

UCL Discovery (University College London)
Gene expression and cancer classification
article

Reconstructing a point set from a random subset of its pairwise distances

article en

Abstract

Let V be a set of n points on the real line. Suppose that each pairwise distance isknown independently with probability p. How much of V can be reconstructed up to isometry? Weprove that p = (log n)/n is a sharp threshold for reconstructing all of V , which improves a resultof Benjamini and Tzalik. This follows from a hitting time result for the random process where thepairwise distances are revealed one by one uniformly at random. We also show that 1/n is a weakthreshold for reconstructing a linear proportion of V.

UCL Discovery (University College London)
Openalex Percentile: Top 52%
Gene expression and cancer classification
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Reconstructing a point set from a random subset of its pairwise distances · UCL Discovery (University College London) (2024) | TGRS Research Map | TGRS