Small-Error Cascaded Group Testing

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: McMorrow, Daniel, Karamchandani, Nikhil, Jaggi, Sidharth
Format: Preprint
Publié: 2026
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866909034569793536
author McMorrow, Daniel
Karamchandani, Nikhil
Jaggi, Sidharth
author_facet McMorrow, Daniel
Karamchandani, Nikhil
Jaggi, Sidharth
contents Group testing concerns itself with the accurate recovery of a set of "defective" items from a larger population via a series of tests. While most works in this area have considered the classical group testing model, where tests are binary and indicate the presence of at least one defective item in the test, we study the cascaded group testing model. In cascaded group testing, tests admit an ordering, and test outcomes indicate the first defective item in the test under this ordering. Under this model, we establish various achievability bounds for several different recovery criteria using both non-adaptive and adaptive test designs when assuming both unconstrained and constrained test sizes. In the constrained test size setting, we also provide a lower bound showing our achievability result is optimal up to logarithmic factors.
format Preprint
id arxiv_https___arxiv_org_abs_2601_11945
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Small-Error Cascaded Group Testing
McMorrow, Daniel
Karamchandani, Nikhil
Jaggi, Sidharth
Information Theory
Group testing concerns itself with the accurate recovery of a set of "defective" items from a larger population via a series of tests. While most works in this area have considered the classical group testing model, where tests are binary and indicate the presence of at least one defective item in the test, we study the cascaded group testing model. In cascaded group testing, tests admit an ordering, and test outcomes indicate the first defective item in the test under this ordering. Under this model, we establish various achievability bounds for several different recovery criteria using both non-adaptive and adaptive test designs when assuming both unconstrained and constrained test sizes. In the constrained test size setting, we also provide a lower bound showing our achievability result is optimal up to logarithmic factors.
title Small-Error Cascaded Group Testing
topic Information Theory
url https://arxiv.org/abs/2601.11945