Sensitivity of two-Higgs-doublet models on Higgs-pair production via bb¯bb¯ final state

Abstract

Higgs boson pair production is a well-known probe of the structure of the electroweak symmetry breaking sector. We illustrate this using the gluon-fusion processes $pp\ensuremath{\rightarrow}H\ensuremath{\rightarrow}hh\ensuremath{\rightarrow}(b\overline{b})(b\overline{b})$ in the framework of two-Higgs-doublet models and show how a machine learning approach (three-stream convolutional neural network) can substantially improve the signal-background discrimination and thus improve the sensitivity coverage of the relevant parameter space. We further show that such $gg\ensuremath{\rightarrow}hh\ensuremath{\rightarrow}b\overline{b}b\overline{b}$ processes can probe the parameter space currently allowed by higgssignals and higgsbounds at the HL-LHC. Results are presented for 2HDM types I through IV.