Measurement of the transverse momentum distribution of Drell–Yan lepton pairs in proton–proton collisions at $$\sqrt{s}=13\,$$TeV with the ATLAS detector

Abstract

This paper describes precision measurements of the transverse momentum $$p_\mathrm {T}^{\ell \ell }$$ p T ℓ ℓ ($$\ell =e,\mu $$ ℓ = e , μ ) and of the angular variable $$\phi ^{*}_{\eta }$$ ϕ η ∗ distributions of Drell–Yan lepton pairs in a mass range of 66–116 GeV. The analysis uses data from 36.1 fb$$^{-1}$$ - 1 of proton–proton collisions at a centre-of-mass energy of $$\sqrt{s}=13\,$$ s = 13 TeV collected by the ATLAS experiment at the LHC in 2015 and 2016. Measurements in electron-pair and muon-pair final states are performed in the same fiducial volumes, corrected for detector effects, and combined. Compared to previous measurements in proton–proton collisions at $$\sqrt{s}=7$$ s = 7 and $$8\,$$ 8 TeV, these new measurements probe perturbative QCD at a higher centre-of-mass energy with a different composition of initial states. They reach a precision of 0.2$$\%$$ % for the normalized spectra at low values of $$p_\mathrm {T}^{\ell \ell }$$ p T ℓ ℓ . The data are compared with different QCD predictions, where it is found that predictions based on resummation approaches can describe the full spectrum within uncertainties.

Measurement of the Drell-Yan differential cross-section d(sigma)/d(pT) at high dilepton mass in proton-proton collisions at sqrt(s) = 7 TeV with the ATLAS detector

“…Muons from light mesons (kaon or pion) decays in flights have high p T (> 20 GeV) in the ID, while their MS tracks have low p T (< 10 GeV) [73]. These muons are removed by the p µ T (MS) cut.…”

“…The efficiency ratio between data and MC instead of the isolation efficiency in data has been used to avoid the data and MC inconsistencies in the isolation efficiency, which causes systematic uncertainties. The following isolation cut related to muon p µ T is chosen because it provides the flattest efficiency ratio over the full p µµ T range [73].…”

“…Other backgrounds are estimated from Monte Carlo simulation and their uncertainty is the quadrature sum of Monte Carlo statistical uncertainty and systematic uncertainties. high-mass region 0 -3 0.424 ± 0.988 0.022 ± 0.022 0.001 ± 0.009 0.000 ± 0.000 0.015 ± 0.006 0.002 ± 0.001 0.001 ± 0.000 0.464 ± 0.989 3 -6 0.424 ± 0.988 0.000 ± 0.000 0.065 ± 0.020 0.000 ± 0.000 0.048 ± 0.012 0.006 ± 0.002 0.001 ± 0.000 0.545 ± 0.989 6 -9 0.283 ± 0.659 0.010 ± 0.010 0.052 ± 0.022 0.000 ± 0.000 0.082 ± 0.015 0.011 ± 0.004 0.002 ± 0.001 0.440 ± 0.660 9 -12 0.424 ± 0.988 0.039 ± 0.023 0.146 ± 0.030 0.000 ± 0.000 0.085 ± 0.016 0.024 ± 0.005 0.003 ± 0.001 0.721 ± 0.989 12 -15 0.707 ± 1.647 0.000 ± 0.000 0.191 ± 0.036 0.000 ± 0.000 0.080 ± 0.015 0.019 ± 0.004 0.005 ± 0.001 1.001 ± 1.648 15 -18 0.141 ± 0.329 0.015 ± 0.015 0.150 ± 0.032 0.000 ± 0.000 0.142 ± 0.022 0.014 ± 0.004 0.008 ± 0.001 0.471 ± 0.332 18 -21 0.424 ± 0.988 0.000 ± 0.000 0.197 ± 0.038 0.000 ± 0.000 0.111 ± 0.018 0.021 ± 0.005 0.006 ± 0.001 0.760 ± 0.989 21 -24 0.141 ± 0.329 0.000 ± 0.000 0.333 ± 0.052 0.062 ± 0.062 0.117 ± 0.020 0.024 ± 0.005 0.008 ± 0.001 0.686 ± 0.340 24 -27 0.283 ± 0.659 0.012 ± 0.012 0.355 ± 0.053 0.065 ± 0.065 0.141 ± 0.022 0.018 ± 0.004 0.012 ± 0.002 0.886 ± 0.665 27 -30 0.141 ± 0.329 0.000 ± 0.000 0.403 ± 0.058 0.000 ± 0.000 0.152 ± 0.024 0.031 ± 0.006 0.009 ± 0.002 0.736 ± 0.335 30 -36 0.141 ± 0.329 0.022 ± 0.022 0.823 ± 0.091 0.000 ± 0.000 0.267 ± 0.032 0.047 ± 0.007 0.019 ± 0.002 1.319 ± 0.344 36 -42 0.283 ± 0.659 0.016 ± 0.016 0.936 ± 0.101 0.000 ± 0.000 0.367 ± 0.040 0.060 ± 0.009 0.020 ± 0.002 1.682 ± 0.668 42 -48 0.424 ± 0.988 0.000 ± 0.000 0.706 ± 0.086 0.000 ± 0.000 0.284 ± 0.033 0.058 ± 0.009 0.014 ± 0.002 1.485 ± 0.993 48 -54 0.141 ± 0.329 0.000 ± 0.000 0.865 ± 0.094 0.000 ± 0.000 0.251 ± 0.030 0.054 ± 0.008 0.020 ± 0.002 1.331 ± 0.344 54 -60 0.141 ± 0.329 0.000 ± 0.000 0.911 ± 0.097 0.000 ± 0.000 0.236 ± 0.029 0.050 ± 0.008 0.015 ± 0.002 is the corresponding number of expected background events, C i is a correction factor to unfold detector effects, and ∆p µµ T i is the bin width [73]. The cross-section is differentiated by p µµ T because we use different bin width for each p µµ T bin.…”

“…The bin widths are chosen so that they correspond to roughly three times the p µµ T resolution. The binning ensures a signal purity above 60% in each bin and sufficient statistics in the high-p µµ T bins [73]. Bin purity is defined as the fraction of the Monte Carlo events where the p µµ T values reconstructed in a given p µµ T bin have a generated value of p µµ T in the same bin (see Eq.…”

“…If the bin-purity is above ∼ 60% (small bin migrations between bins), the systematic uncertainty introduced by the bin-by-bin method is usually considered small enough and the bin-by-bin method is sufficient [73]. However, for the low bin-purity (large bin migrations to neighboring bins), more advanced unfolding techniques become necessary.…”