SciPost Submission Page
Strength in numbers: optimal and scalable combination of LHC new-physics searches
by Jack Y. Araz, Andy Buckley, Benjamin Fuks, Humberto Reyes-Gonzalez, Wolfgang Waltenberger, Sophie L. Williamson, Jamie Yellen
|Authors (as Contributors):||Jack Araz · Andy Buckley · Benjamin Fuks · Humberto Reyes-González|
|Arxiv Link:||https://arxiv.org/abs/2209.00025v3 (pdf)|
|Date submitted:||2022-12-23 20:45|
|Submitted by:||Reyes-González, Humberto|
|Submitted to:||SciPost Physics|
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.
For Journal SciPost Physics: Publish
(status: Editorial decision fixed and (if required) accepted by authors)
Submission & Refereeing History
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Reports on this Submission
Report 1 by Andrew Fowlie on 2023-1-2 (Invited Report)
I would like to thank the authors for considering my comments and addressing my concerns. I now strongly recommend publication.