Individual testing is optimal for nonadaptive group testing in the linear regime

Matthew Aldridge

公開日: 2018/1/25

Abstract

We consider nonadaptive probabilistic group testing in the linear regime, where each of n items is defective independently with probability p in (0,1), and p is a constant independent of n. We show that testing each item individually is optimal, in the sense that with fewer than n tests the error probability is bounded away from zero.

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