Strength in numbers: Optimal and scalable combination of LHC new-physics searches
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 th...
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| Format: | Article |
| Language: | English |
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SciPost
2023-04-01
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| Series: | SciPost Physics |
| Online Access: | https://scipost.org/SciPostPhys.14.4.077 |
| _version_ | 1797843480468258816 |
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| author | Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen |
| author_facet | Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen |
| author_sort | Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T17:05:55Z |
| format | Article |
| id | doaj.art-f74282201c3f4580b302b7e128fa7719 |
| institution | Directory Open Access Journal |
| issn | 2542-4653 |
| language | English |
| last_indexed | 2024-04-09T17:05:55Z |
| publishDate | 2023-04-01 |
| publisher | SciPost |
| record_format | Article |
| series | SciPost Physics |
| spelling | doaj.art-f74282201c3f4580b302b7e128fa77192023-04-20T15:21:17ZengSciPostSciPost Physics2542-46532023-04-0114407710.21468/SciPostPhys.14.4.077Strength in numbers: Optimal and scalable combination of LHC new-physics searchesJack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie YellenTo 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.https://scipost.org/SciPostPhys.14.4.077 |
| spellingShingle | Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen Strength in numbers: Optimal and scalable combination of LHC new-physics searches SciPost Physics |
| title | Strength in numbers: Optimal and scalable combination of LHC new-physics searches |
| title_full | Strength in numbers: Optimal and scalable combination of LHC new-physics searches |
| title_fullStr | Strength in numbers: Optimal and scalable combination of LHC new-physics searches |
| title_full_unstemmed | Strength in numbers: Optimal and scalable combination of LHC new-physics searches |
| title_short | Strength in numbers: Optimal and scalable combination of LHC new-physics searches |
| title_sort | strength in numbers optimal and scalable combination of lhc new physics searches |
| url | https://scipost.org/SciPostPhys.14.4.077 |
| work_keys_str_mv | AT jackyarazandybuckleybenjaminfukshumbertoreyesgonzalezwolfgangwaltenbergersophielwilliamsonjamieyellen strengthinnumbersoptimalandscalablecombinationoflhcnewphysicssearches |