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Group testing is a useful method that has broad applications in medicine, engineering, and even in airport security control. Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to…

Other Statistics · Statistics 2017-04-17 Yaakov Malinovsky

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applications such as medical testing, communication protocols, pattern…

Information Theory · Computer Science 2018-10-05 Jonathan Scarlett

In probabilistic nonadaptive group testing (PGT), we aim to characterize the number of pooled tests necessary to identify a random $k$-sparse vector of defectives with high probability. Recent work has shown that $n$ tests are necessary…

Information Theory · Computer Science 2021-06-15 Larkin Flodin , Arya Mazumdar

We consider a generalization of group testing where the potentially contaminated sets are the members of a given hypergraph ${\cal F}=(V,E)$. This generalization finds application in contexts where contaminations can be conditioned by some…

Data Structures and Algorithms · Computer Science 2023-11-28 Annalisa De Bonis

We examine the following version of a classic combinatorial search problem introduced by R\'enyi: Given a finite set $X$ of $n$ elements we want to identify an unknown subset $Y \subset X$ of exactly $d$ elements by testing, by as few as…

Combinatorics · Mathematics 2015-09-02 Fabrício S. Benevides , Dániel Gerbner , Cory T. Palmer , Dominik K. Vu

We consider Bernoulli nonadaptive group testing with $k = \Theta(n^\theta)$ defectives, for $\theta \in (0,1)$. The practical definite defectives (DD) detection algorithm is known to be optimal for $\theta \geq 1/2$. We give a new upper…

Information Theory · Computer Science 2017-11-27 Matthew Aldridge

We consider adaptive group testing in the linear regime, where the number of defective items scales linearly with the number of items. We analyse an algorithm based on generalized binary splitting. Provided fewer than half the items are…

Information Theory · Computer Science 2020-04-07 Matthew Aldridge

In this paper, we derive mutual information based upper and lower bounds on the number of nonadaptive group tests required to identify a given number of "non defective" items from a large population containing a small number of "defective"…

Information Theory · Computer Science 2016-03-01 Abhay Sharma , Chandra R. Murthy

We consider the problem of non-adaptive noiseless group testing of $N$ items of which $K$ are defective. We describe four detection algorithms: the COMP algorithm of Chan et al.; two new algorithms, DD and SCOMP, which require stronger…

Information Theory · Computer Science 2014-05-20 Matthew Aldridge , Leonardo Baldassini , Oliver Johnson

Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to identify all items by means of group testing. This is the generalized group testing problem (hereafter GGTP). In the case of…

Other Statistics · Statistics 2020-02-28 Yaakov Malinovsky

In this paper, we study the problem of non-adaptive group testing, in which one seeks to identify which items are defective given a set of suitably-designed tests whose outcomes indicate whether or not at least one defective item was…

Information Theory · Computer Science 2025-09-26 Lan V. Truong , Matthew Aldridge , Jonathan Scarlett

Group testing with inhibitors (GTI) introduced by Farach at al. is studied in this paper. There are three types of items, $d$ defectives, $r$ inhibitors and $n-d-r$ normal items in a population of $n$ items. The presence of any inhibitor in…

Information Theory · Computer Science 2014-12-16 Abhinav Ganesan , Javad Ebrahimi , Sidharth Jaggi , Venkatesh Saligrama

Accurate detection of infected individuals is one of the critical steps in stopping any pandemic. When the underlying infection rate of the disease is low, testing people in groups, instead of testing each individual in the population, can…

The goal of group testing is to identify a small number of defective items within a large population. In the non-adaptive setting, tests are designed in advance and represented by a measurement matrix $\mM$, where rows correspond to tests…

Information Theory · Computer Science 2025-09-10 Trung-Khang Tran , Thach V. Bui

In order to identify the infected individuals of a population, their samples are divided in equally sized groups called pools and a single laboratory test is applied to each pool. Individuals whose samples belong to pools that test negative…

Statistics Theory · Mathematics 2021-10-06 Inés Armendáriz , Pablo A. Ferrari , Daniel Fraiman , José M. Martínez , Silvina Ponce Dawson

We introduce a novel probabilistic group testing framework, termed Poisson group testing, in which the number of defectives follows a right-truncated Poisson distribution. The Poisson model has a number of new applications, including…

Information Theory · Computer Science 2023-07-19 Amin Emad , Olgica Milenkovic

In the group testing problem we aim to identify a small number of infected individuals within a large population. We avail ourselves to a procedure that can test a group of multiple individuals, with the test result coming out positive iff…

Discrete Mathematics · Computer Science 2021-05-14 Amin Coja-Oghlan , Oliver Gebhard , Max Hahn-Klimroth , Philipp Loick

This paper considers the problem of Quantitative Group Testing (QGT) where there are some defective items among a large population of $N$ items. We consider the scenario in which each item is defective with probability $K/N$, independently…

Information Theory · Computer Science 2019-10-16 Esmaeil Karimi , Fatemeh Kazemi , Anoosheh Heidarzadeh , Krishna R. Narayanan , Alex Sprintson

Given $d$ defective items in a population of $n$ items with $d \ll n$, in threshold group testing without gap, the outcome of a test on a subset of items is positive if the subset has at least $u$ defective items and negative otherwise,…

Information Theory · Computer Science 2024-05-10 Thach V. Bui , Yeow Meng Chee , Van Khu Vu

Recent advances in noiseless non-adaptive group testing have led to a precise asymptotic characterization of the number of tests required for high-probability recovery in the sublinear regime $k = n^{\theta}$ (with $\theta \in (0,1)$), with…

Data Structures and Algorithms · Computer Science 2021-12-24 Oliver Gebhard , Max Hahn-Klimroth , Olaf Parczyk , Manuel Penschuck , Maurice Rolvien , Jonathan Scarlett , Nelvin Tan
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