Jet-parton assignment in t(t)over-barH events using deep learning

The direct measurement of the top quark-Higgs coupling is one of the important questions in understanding the Higgs boson. The coupling can be obtained through measurement of the top quark pair-associated Higgs boson production cross-section. Of the multiple challenges arising in this cross-section measurement, we investigate the reconstruction of the partons originating from the hard scattering process using the measured jets in simulated t (t) over barH events. The task corresponds to an assignment challenge of m objects (jets) to n other objects (partons), where m >= n. We compare several methods with emphasis on a concept based on deep learning techniques which yields the best results with more than 50% of correct jet-parton assignments.