Araz, J. Y. , Buckley, A. , Fuks, B., Reyes-González, H., Waltenberger, W., Williamson, S. L. and Yellen, J. (2023) Strength in numbers: Optimal and scalable combination of LHC new-physics searches. SciPost Physics, 14(4), 077. (doi: 10.21468/scipostphys.14.4.077)
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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.
Item Type: | Articles |
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Additional Information: | AB and JY thank the Royal Society for studentship funding under URF Enhancement Grant RGF\EA\180252, and STFC for support under Consolidated Grant ST/S000887/1. The research of HRG is funded by the Italian PRIN grant 20172LNEEZ. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Buckley, Professor Andy and Araz, Mr Jack and Yellen, Jamie |
Authors: | Araz, J. Y., Buckley, A., Fuks, B., Reyes-González, H., Waltenberger, W., Williamson, S. L., and Yellen, J. |
College/School: | College of Science and Engineering > School of Physics and Astronomy |
Journal Name: | SciPost Physics |
Publisher: | SciPost Foundation |
ISSN: | 2542-4653 |
ISSN (Online): | 2542-4653 |
Copyright Holders: | Copyright © 2023 J. Y. Araz et al. |
First Published: | First published in SciPost Phys. 14, 077 (2023) |
Publisher Policy: | Reproduced under a Creative Commons licence |
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