Application-oriented mathematical algorithms for group testing
E Csóka - arXiv preprint arXiv:2005.02388, 2020 - arxiv.org
arXiv preprint arXiv:2005.02388, 2020•arxiv.org
We have a large number of samples and we want to find the infected ones using as few
number of tests as possible. We can use group testing which tells about a small group of
people whether at least one of them is infected. Group testing is particularly efficient if the
infection rate is low. The goal of this article is to summarize and extend the mathematical
knowledge about the most efficient group testing algorithms, focusing on real-life
applications instead of pure mathematical motivations and approaches.
number of tests as possible. We can use group testing which tells about a small group of
people whether at least one of them is infected. Group testing is particularly efficient if the
infection rate is low. The goal of this article is to summarize and extend the mathematical
knowledge about the most efficient group testing algorithms, focusing on real-life
applications instead of pure mathematical motivations and approaches.
We have a large number of samples and we want to find the infected ones using as few number of tests as possible. We can use group testing which tells about a small group of people whether at least one of them is infected. Group testing is particularly efficient if the infection rate is low. The goal of this article is to summarize and extend the mathematical knowledge about the most efficient group testing algorithms, focusing on real-life applications instead of pure mathematical motivations and approaches.
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