Measurements of jet substructure describing the composition of quark- and gluon-initiated jets are presented. Proton-proton (pp) collision data at $$ \sqrt{s} $$
s
= 13 TeV collected with the CMS detector are used, corresponding to an integrated luminosity of 35.9 fb−1. Generalized angularities are measured that characterize the jet substructure and distinguish quark- and gluon-initiated jets. These observables are sensitive to the distributions of transverse momenta and angular distances within a jet. The analysis is performed using a data sample of dijet events enriched in gluon-initiated jets, and, for the first time, a Z+jet event sample enriched in quark-initiated jets. The observables are measured in bins of jet transverse momentum, and as a function of the jet radius parameter. Each measurement is repeated applying a “soft drop” grooming procedure that removes soft and large angle radiation from the jet. Using these measurements, the ability of various models to describe jet substructure is assessed, showing a clear need for improvements in Monte Carlo generators.
The first evidence for X(3872) production in relativistic heavy ion collisions is reported. The X(3872) production is studied in lead-lead (Pb-Pb) collisions at a center-of-mass energy of ffiffiffiffiffiffiffi ffi s NN p ¼ 5.02 TeV per nucleon pair, using the decay chain Xð3872ÞThe data were recorded with the CMS detector in 2018 and correspond to an integrated luminosity of 1.7 nb −1 . The measurement is performed in the rapidity and transverse momentum ranges jyj < 1.6 and 15 < p T < 50 GeV=c. The significance of the inclusive X(3872) signal is 4.2 standard deviations. The prompt X(3872) to ψ2S yield ratio is found to be ρ Pb-Pb ¼ 1.08 AE 0.49ðstatÞ AE 0.52ðsystÞ, to be compared with typical values of 0.1 for pp collisions. This result provides a unique experimental input to theoretical models of the X(3872) production mechanism, and of the nature of this exotic state.
Many measurements at the LHC require efficient
identification of heavy-flavour jets, i.e. jets originating from
bottom (b) or charm (c) quarks. An overview of the algorithms used
to identify c jets is described and a novel method to calibrate them
is presented. This new method adjusts the entire distributions of
the outputs obtained when the algorithms are applied to jets of
different flavours. It is based on an iterative approach exploiting
three distinct control regions that are enriched with either b jets,
c jets, or light-flavour and gluon jets. Results are presented in
the form of correction factors evaluated using proton-proton
collision data with an integrated luminosity of 41.5 fb-1 at
√s = 13 TeV, collected by the CMS experiment in 2017. The
closure of the method is tested by applying the measured correction
factors on simulated data sets and checking the agreement between
the adjusted simulation and collision data. Furthermore, a
validation is performed by testing the method on pseudodata, which
emulate various mismodelling conditions. The calibrated results
enable the use of the full distributions of heavy-flavour
identification algorithm outputs, e.g. as inputs to
machine-learning models. Thus, they are expected to increase the
sensitivity of future physics analyses.
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