The rate for Higgs ( H ) bosons production in association with either one ( t H ) or two ( t t ¯ H ) top quarks is measured in final states containing multiple electrons, muons, or tau leptons decaying to hadrons and a neutrino, using proton-proton collisions recorded at a center-of-mass energy of 13 TeV by the CMS experiment. The analyzed data correspond to an integrated luminosity of 137 fb - 1 . The analysis is aimed at events that contain H → W W , H → τ τ , or H → Z Z decays and each of the top quark(s) decays either to lepton+jets or all-jet channels. Sensitivity to signal is maximized by including ten signatures in the analysis, depending on the lepton multiplicity. The separation among t H , t t ¯ H , and the backgrounds is enhanced through machine-learning techniques and matrix-element methods. The measured production rates for the t t ¯ H and t H signals correspond to 0.92 ± 0.19 (stat) - 0.13 + 0.17 (syst) and 5.7 ± 2.7 (stat) ± 3.0 (syst) of their respective standard model (SM) expectations. The corresponding observed (expected) significance amounts to 4.7 (5.2) standard deviations for t t ¯ H , and to 1.4 (0.3) for t H production. Assuming that the Higgs boson coupling to the tau lepton is equal in strength to its expectation in the SM, the coupling y t of the Higgs boson to the top quark divided by its SM expectation, κ t = y t / y t SM , is constrained to be within - 0.9 < κ t < - 0.7 or 0.7 < κ t < 1.1 , at 95% confidence level. This result is the most sensitive measurement of the t t ¯ H production rate to date.
We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯ .