Wing Sheung Chan

132 Distributions and modelling of the neural network input variables 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 Events / 20 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 1P τ e SR, 0 50 100 150 200 250 300 ) [GeV] l ( ∧ E 0.5 0.75 1 1.25 1.5 Data / pred. 0 5000 10000 15000 20000 25000 Events / 20 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 3P τ e SR, 0 50 100 150 200 250 300 ) [GeV] l ( ∧ E 0.5 0.75 1 1.25 1.5 Data / pred. 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 Events / 20 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 1P τ e SR, 100 − 50 − 0 50 100 150 200 250 300 ) [GeV] l ( z ∧ p 0.5 0.75 1 1.25 1.5 Data / pred. 0 2000 4000 6000 8000 10000 12000 Events / 20 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 3P τ e SR, 100 − 50 − 0 50 100 150 200 250 300 ) [GeV] l ( z ∧ p 0.5 0.75 1 1.25 1.5 Data / pred. 0 5000 10000 15000 20000 25000 30000 35000 Events / 2.5 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 1P τ e SR, 0 5 10 15 20 25 30 35 40 45 [GeV] miss T ∧ E 0.5 0.75 1 1.25 1.5 Data / pred. 0 2000 4000 6000 8000 10000 Events / 2.5 GeV Data fakes had-vis τ→ jet ττ→ Z ll → Z Others Total uncertainty ) 3 − = 10 Β ( τ e → Z -1 = 13 TeV, 139 fb s 3P τ e SR, 0 5 10 15 20 25 30 35 40 45 [GeV] miss T ∧ E 0.5 0.75 1 1.25 1.5 Data / pred. Figure C.1.: Expected and observed distributions of ˆ E ( ` ) , ˆ p z ( ` ) and ˆ E miss T in the SR of the eτ channel. In the lower panel of each plot, the ratios of the observed yields to the predicted background yields are shown. The hatched error bands represent the combined statistical and systematic uncertainties. The last bin in each plot includes overflow events.