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Strength in numbers: Optimal and scalable combination of LHC new-physics searches

Araz, Jack Y.; Buckley, Andy; Fuks, Benjamin; Reyes-González, Humberto; Waltenberger, Wolfgang; Williamson, Sophie L. 1; Yellen, Jamie
1 Institut für Theoretische Physik (ITP), Karlsruher Institut für Technologie (KIT)

Abstract:

To gain a comprehensive view of what the LHC tells us about physics beyond the Standard Model (BSM), it is crucial that different BSM-sensitive analyses can be combined. But in general search-analyses are not statistically orthogonal, so performing comprehensive combinations requires knowledge of the extent to which the same events co-populate multiple analyses' signal regions. We present a novel, stochastic method to determine this degree of overlap, and a graph algorithm to efficiently find the combination of signal regions with no mutual overlap that optimises expected upper limits on BSM-model cross-sections. The gain in exclusion power relative to single-analysis limits is demonstrated with models with varying degrees of complexity, ranging from simplified models to a 19-dimensional supersymmetric model.


Verlagsausgabe §
DOI: 10.5445/IR/1000158601
Veröffentlicht am 31.05.2023
Originalveröffentlichung
DOI: 10.21468/SciPostPhys.14.4.077
Scopus
Zitationen: 4
Web of Science
Zitationen: 4
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Theoretische Physik (ITP)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 2542-4653
KITopen-ID: 1000158601
Erschienen in SciPost Physics
Verlag SciPost
Band 14
Heft 4
Seiten Art.-Nr.: 077
Vorab online veröffentlicht am 20.04.2023
Nachgewiesen in Dimensions
Scopus
Web of Science
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