Double-charming Higgs identification using machine-learning assisted jet shapes

Abstract

We study the possibility of identifying a boosted resonance that decays into a charm pair against different sources of background using QCD event shapes, which are promoted to jet shapes. Using a set of jet shapes as input to a boosted decision tree, we find that observables utilizing the simultaneous presence of two charm quarks can access complementary information compared to approaches relying on two independent charm tags. Focusing on Higgs associated production with subsequent $H\to c\bar{c}$ decay and on a CP-odd scalar $A$ with $m_A\le 10$ GeV we obtain the limits $\mathcal{B}r(H\to c\bar{c})\le 6.09\%$ and $\mathcal{B}r(H\to A(\to c\bar{c})Z)\le 0.01\%$ at $95\%$ C. L..

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• Solving differential equations with neural networks: Applications to the calculation of cosmological phase transitions