Strength in numbers: Optimal and scalable combination of LHC newphysics searches
Abstract
To gain a comprehensive view of what the LHC tells us about physics beyond the Standard Model (BSM), it is crucial that different BSMsensitive analyses can be combined. But in general searchanalyses are not statistically orthogonal, so performing comprehensive combinations requires knowledge of the extent to which the same events copopulate 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 BSMmodel crosssections. The gain in exclusion power relative to singleanalysis limits is demonstrated with models with varying degrees of complexity, ranging from simplified models to a 19dimensional supersymmetric model.
 Publication:

SciPost Physics
 Pub Date:
 April 2023
 DOI:
 10.21468/SciPostPhys.14.4.077
 arXiv:
 arXiv:2209.00025
 Bibcode:
 2023ScPP...14...77A
 Keywords:

 High Energy Physics  Phenomenology;
 High Energy Physics  Experiment
 EPrint:
 35 pages, 15 figures. Updated version for SciPost submission