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Register a new userQuark jet rates and quark/gluon discrimination in multi-jet final states
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Authors
Yasuhito Sakaki
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We estimate the number of quark jets in QCD multi-jet final states at hadron colliders. In the estimation, we develop the calculation of jet rates into that of quark jet rates. From the calculation, we estimate the improvement on the signal-to-background ratio for a signal semi-analytically by applying quark/gluon discrimination, where the signal predicts many quark jets. We introduce a variable related to jet flavors in multi-jet final states and propose a data-driven method using the variable to reduce systematic uncertainties of analysis results. As the same with the semi-analytical result, the improvements on the signal-to-background ratio using the variable in Monte-Carlo analysis are estimated.
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We show that in studies of light quark- and gluon-initiated jet discrimination, it is important to include the information on softer reconstructed jets (associated jets) around a primary hard jet. This is particularly relevant while adopting a small radius parameter for reconstructing hadronic jets. The probability of having an associated jet as a function of the primary jet transverse momentum ($p_T$) and radius, the minimum associated jet $p_T$ and the association radius is computed upto next-to-double logarithmic accuracy (NDLA), and the predictions are compared with results from Herwig++, Pythia6 and Pythia8 Monte Carlos (MC). We demonstrate the improvement in quark-gluon discrimination on using the associated jet rate variable with the help of a multivariate analysis. The associated jet rates are found to be only mildly sensitive to the choice of parton shower and hadronization algorithms, as well as to the effects of initial state radiation and underlying event. In addition, the number of $k_T$ subjets of an anti-$k_T$ jet is found to be an observable that leads to a rather uniform prediction across different MCs, broadly being in agreement with predictions in NDLA, as compared to the often used number of charged tracks observable.
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We study the phenomenon of jet quenching utilizing quark and gluon jet substructures as independent probes of heavy ion collisions. We exploit jet and subjet features to highlight differences between quark and gluon jets in vacuum and in a medium with the jet-quenching model implemented in JEWEL. We begin with a physics-motivated, multivariate analysis of jet substructure observables including the jet mass, the radial moments, the $p_T^D$ and the pixel multiplicity. In comparison, we employ state-of-the-art image-recognition techniques by training a deep convolutional neutral network on jet images. To systematically extract jet substructure information, we introduce the telescoping deconstruction framework exploiting subjet kinematics at multiple angular scales. We draw connections to the soft-drop subjet distribution and illuminate medium-induced jet modifications using Lund diagrams. We find that the quark gluon discrimination performance worsens in heavy ion jets due to significant soft event activity affecting the soft jet substructure. Our work suggests a systematically improvable framework for studying modifications to quark and gluon jet substructures and facilitating direct comparisons between theoretical calculations, simulations and measurements in heavy ion collisions.
Whether quark- and gluon-initiated jets are modified differently by the quark-gluon plasma produced in heavy-ion collisions is a long-standing question that has thus far eluded a definitive experimental answer. A crucial complication for quark-gluon discrimination in both proton-proton and heavy-ion collisions is that all measurements necessarily average over the (unknown) quark-gluon composition of a jet sample. In the heavy-ion context, the simultaneous modification of both the fractions and substructure of quark and gluon jets by the quark-gluon plasma further obscures the interpretation. Here, we demonstrate a fully data-driven method for separating quark and gluon contributions to jet observables using a statistical technique called topic modeling. Assuming that jet distributions are a mixture of underlying quark-like and gluon-like distributions, we show how to extract quark and gluon jet fractions and constituent multiplicity distributions as a function of the jet transverse momentum. This proof-of-concept study is based on proton-proton and heavy-ion collision events from the Monte Carlo event generator Jewel with statistics accessible in Run 4 of the Large Hadron Collider. These results suggest the potential for an experimental determination of quark and gluon jet modifications.
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