Higgs pair production: choosing benchmarks with cluster analysis

A bstract New physics theories often depend on a large number of free parameters. The phenomenology they predict for fundamental physics processes is in some cases drastically affected by the precise value of those free parameters, while in other cases is left basically invariant at the level of det...

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Veröffentlicht in:The journal of high energy physics 2016-04, Vol.2016 (4), p.1-28
Hauptverfasser: Carvalho, Alexandra, Dall’Osso, Martino, Dorigo, Tommaso, Goertz, Florian, Gottardo, Carlo A., Tosi, Mia
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Sprache:eng
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Zusammenfassung:A bstract New physics theories often depend on a large number of free parameters. The phenomenology they predict for fundamental physics processes is in some cases drastically affected by the precise value of those free parameters, while in other cases is left basically invariant at the level of detail experimentally accessible. When designing a strategy for the analysis of experimental data in the search for a signal predicted by a new physics model, it appears advantageous to categorize the parameter space describing the model according to the corresponding kinematical features of the final state. A multi-dimensional test statistic can be used to gauge the degree of similarity in the kinematics predicted by different models; a clustering algorithm using that metric may allow the division of the space into homogeneous regions, each of which can be successfully represented by a benchmark point. Searches targeting those benchmarks are then guaranteed to be sensitive to a large area of the parameter space. In this document we show a practical implementation of the above strategy for the study of non-resonant production of Higgs boson pairs in the context of extensions of the standard model with anomalous couplings of the Higgs bosons. A non-standard value of those couplings may significantly enhance the Higgs boson pair-production cross section, such that the process could be detectable with the data that the LHC will collect in Run 2.
ISSN:1029-8479
1029-8479
DOI:10.1007/JHEP04(2016)126