No abstract

A: The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic τ decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8 TeV show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions. 3 Reconstruction of the particle-flow elements 9 3.1 Charged-particle tracks and vertices 9 3.1.

Improved jet energy scale corrections, based on a data sample corresponding to an integrated luminosity of 19.7 fb −1 collected by the CMS experiment in proton-proton collisions at a center-of-mass energy of 8 TeV, are presented. The corrections as a function of pseudorapidity η and transverse momentum p T are extracted from data and simulated events combining several channels and methods. They account successively for the effects of pileup, uniformity of the detector response, and residual data-simulation jet energy scale differences. Further corrections, depending on the jet flavor and distance parameter (jet size) R, are also presented. The jet energy resolution is measured in data and simulated events and is studied as a function of pileup, jet size, and jet flavor. Typical jet energy resolutions at the central rapidities are 15-20% at 30 GeV, about 10% at 100 GeV, and 5% at 1 TeV. The studies exploit events with dijet topology, as well as photon+jet, Z+jet and multijet events. Several new techniques are used to account for the various sources of jet energy scale corrections, and a full set of uncertainties, and their correlations, are provided.The final uncertainties on the jet energy scale are below 3% across the phase space considered by most analyses (p T > 30 GeV and |η| < 5.0). In the barrel region (|η| < 1.3) an uncertainty below 1% for p T > 30 GeV is reached, when excluding the jet flavor uncertainties, which are provided separately for different jet flavors. A new benchmark for jet energy scale determination at hadron colliders is achieved with 0.32% uncertainty for jets with p T of the order of 165-330 GeV, and |η| < 0.8.

2018 JINST 13 P05011 8.5 Measurement of the data-to-simulation scale factors as a function of the discriminator value 76 8.6 Comparison of the measured data-to-simulation scale factors 79 9 Measurement of the tagging efficiency for boosted topologies 82 9.1 Comparison of data with simulation 82 9.2 Efficiency for subjets 83 9.2.1 Misidentification probability 83 9.2.2 Measurement of the b tagging efficiency 84 9.3 Efficiency of the double-b tagger 86 9.3.1 Measurement of the double-b tagging efficiency 86 9.3.2 Measurement of the misidentification probability for top quarks 87

New sets of parameters (“tunes”) for the underlying-event (UE) modelling of the pythia8, pythia6 and herwig++ Monte Carlo event generators are constructed using different parton distribution functions. Combined fits to CMS UE proton–proton () data at and to UE proton–antiproton () data from the CDF experiment at lower , are used to study the UE models and constrain their parameters, providing thereby improved predictions for proton–proton collisions at 13. In addition, it is investigated whether the values of the parameters obtained from fits to UE observables are consistent with the values determined from fitting observables sensitive to double-parton scattering processes. Finally, comparisons are presented of the UE tunes to “minimum bias” (MB) events, multijet, and Drell–Yan ( lepton-antilepton+jets) observables at 7 and 8, as well as predictions for MB and UE observables at 13.