Abstract
Experimentally, jet physics studies face an unavoidable task: distinguishing, at the detector level, the particles produced in the hard partonic scattering from the ones created in unrelated soft processes such as pileup interactions in high-luminosity proton-proton scattering or the underlying event in heavy-ion collisions. The fluctuating nature of the background constitutes the main source of uncertainty for any subtraction algorithm. Aiming at mitigating the effect of such fluctuations, we present a new method to estimate the background contribution to the transverse momentum on a jet-by-jet basis. Our approach is based on estimating the median background momentum density stored above a $p_{\rm T}$-cut applied at the constituent level and an experimentally accessible correction term related to the signal contribution below the cut. This allows to trade part of the uncertainty due to background contamination for that of the signal below the cut, similarly to SoftKiller method. We propose to reduce the fluctuations of the latter by exploiting intrinsic correlations among the soft and hard sectors of QCD jets. Our data-driven approach is tested against PYTHIA8 and JEWEL di-jet events embedded in a thermal background and compared to the area-median and SoftKiller methods. The main result of this study is a $\sim 5\!-\!40\%$ improvement on the resolution of the reconstructed jet $p_T$ compared to previous methods in a high-luminosity proton-proton scenario. Its applicability in a heavy-ion context is also discussed.
Highlights
The study of jets in ultrarelativistic hadronic collisions has decisively contributed to our understanding of the perturbative and nonperturbative aspects of quantum chromodynamics (QCD)
At the Large Hadron Collider (LHC), events with jets in the final state are being extensively exploited to search for signatures of new physics
The virtuality of the hard partonic scattering is set to p T 1⁄4 100 GeV=c and the number of pileup interactions is set to nPU 1⁄4 200 for the high-luminosity LHC [19]
Summary
The study of jets in ultrarelativistic hadronic collisions has decisively contributed to our understanding of the perturbative and nonperturbative aspects of quantum chromodynamics (QCD). To perform meaningful theory-to-data comparisons, jet physics relies on two main ingredients: jet reconstruction algorithms and background subtraction methods The former provide an operational definition of a jet by clustering the particles in the event following an infrared and collinear-safe method based on the notion of a distance between them either in momentum (kT) or angular space [7,8,9]. Several methods are used to estimate the background transverse momentum contribution on a jet-by-jet basis in p þ p and A þ A collisions [14,15,16,17]. We pinpoint the underlying mechanisms driving the mean and standard deviation of the reconstructed jet momentum distribution This systematic study leads to the design of a new background estimator that improves the jet pT reconstruction resolution.
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