26-30 July 2021
Europe/Berlin timezone

Resurrecting bbh with Machine Learning Magic

26 Jul 2021, 15:57


Parallel session talk Higgs Physics T09: Higgs Physics


Zhuoni Qian (DESY)


The associated production of a $b\bar{b}$ pair with a Higgs boson could provide an important probe to both the size and the phase of the bottom-quark Yukawa coupling, $y_b$. However, the signal is shrouded by several irreducible background processes. We show that the analysis of kinematic shapes provides us with a concrete prescription for separating the $y_b$-sensitive production modes from both the irreducible and the QCD-QED backgrounds in the $b\bar{b}\gamma\gamma$ final state. We draw a page from game theory and use Shapley values to make Boosted Decision Trees interpretable in terms of kinematic measurables and provide physics insights into the variances in the kinematic shapes of the different channels that help us complete this feat. Adding interpretability to the machine learning algorithm opens up the black-box and allows us to pick and interpret upon kinematic variables that matter most in the analysis. We resurrect the hope of constraining the size and, possibly, the phase of $y_b$ using kinematic shape studies of $b\bar{b}h$ production with the full HL-LHC data and at FCC-hh.

Email Zhuoni.qian@desy.de
Collaboration / Activity DESY
First author Zhuoni Qian

Primary authors

Zhuoni Qian (DESY) Christophe Grojean (DESY) Ayan Paul (T (Phenomenology))

Presentation Materials