English

Efficiently Decodable Non-Adaptive Threshold Group Testing

Information Theory 2018-09-25 v8 math.IT

Abstract

We consider non-adaptive threshold group testing for identification of up to dd defective items in a set of nn items, where a test is positive if it contains at least 2ud2 \leq u \leq d defective items, and negative otherwise. The defective items can be identified using t=O((du)u(ddu)du(ulogdu+log1ϵ)d2logn)t = O \left( \left( \frac{d}{u} \right)^u \left( \frac{d}{d - u} \right)^{d-u} \left(u \log{\frac{d}{u}} + \log{\frac{1}{\epsilon}} \right) \cdot d^2 \log{n} \right) tests with probability at least 1ϵ1 - \epsilon for any ϵ>0\epsilon > 0 or t=O((du)u(ddu)dud3lognlognd)t = O \left( \left( \frac{d}{u} \right)^u \left( \frac{d}{d -u} \right)^{d - u} d^3 \log{n} \cdot \log{\frac{n}{d}} \right) tests with probability 1. The decoding time is t×poly(d2logn)t \times \mathrm{poly}(d^2 \log{n}). This result significantly improves the best known results for decoding non-adaptive threshold group testing: O(nlogn+nlog1ϵ)O(n\log{n} + n \log{\frac{1}{\epsilon}}) for probabilistic decoding, where ϵ>0\epsilon > 0, and O(nulogn)O(n^u \log{n}) for deterministic decoding.

Keywords

Cite

@article{arxiv.1712.07509,
  title  = {Efficiently Decodable Non-Adaptive Threshold Group Testing},
  author = {Thach V. Bui and Minoru Kuribayashi and Mahdi Cheraghchi and Isao Echizen},
  journal= {arXiv preprint arXiv:1712.07509},
  year   = {2018}
}