Improved Lower Bound for Estimating the Number of Defective Items

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Abstract

Let X be a set of items of size n that contains some defective items, denoted by I, where I⊆ X. In group testing, a test refers to a subset of items Q⊂ X. The outcome of a test is 1 if Q contains at least one defective item, i.e., Q∩ I≠ ∅, and 0 otherwise. We give a novel approach to obtaining lower bounds in non-adaptive randomized group testing. The technique produced lower bounds that are within a factor of 1 / log log ⋯ klog n of the existing upper bounds for any constant k. Employing this new method, we can prove the following result. For any fixed constants k, any non-adaptive randomized algorithm that, for any set of defective items I, with probability at least 2/3, returns an estimate of the number of defective items |I| to within a constant factor requires at least$$\varOmega \left(\frac{\log n}{\log \log {\mathop {\cdots }\limits ^{k}}\log n}\right) $$Ω(lognloglog⋯klogn) tests. Our result almost matches the upper bound of O(log n) and solves the open problem posed by Damaschke and Sheikh Muhammad in [8, 9]. Additionally, it improves upon the lower bound of Ω(log n/ log log n) previously established by Ron and Tsur [21] and independently by Bshouty [2].

Original languageEnglish
Title of host publicationCombinatorial Optimization and Applications - 16th International Conference, COCOA 2023, Proceedings
EditorsWeili Wu, Jianxiong Guo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages303-315
Number of pages13
ISBN (Print)9783031496103
DOIs
StatePublished - 2024
Event16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023 - Hawai, United States
Duration: 15 Dec 202317 Dec 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14461 LNCS

Conference

Conference16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023
Country/TerritoryUnited States
CityHawai
Period15/12/2317/12/23

Keywords

  • Estimation
  • Group Testing
  • Randomized Algorithm

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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