Corpus ID: 235458077

Optimal Non-Adaptive Probabilistic Group Testing in General Sparsity Regimes

@inproceedings{Bay2020OptimalNP,
  title={Optimal Non-Adaptive Probabilistic Group Testing in General Sparsity Regimes},
  author={Wei Heng Bay and Eric Price and J. Scarlett},
  year={2020}
}
In this paper, we consider the problem of noiseless non-adaptive probabilistic group testing, in which the goal is high-probability recovery of the defective set. We show that the smallest possible number of tests behaves as Θ(min{k logn, n}) in the case of n items among which k are defective, as well as providing the precise underlying constant factors. The algorithmic upper bound follows from a minor adaptation of an existing analysis of the Definite Defectives (DD) algorithm, and the… Expand

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