# machine-readable table in parallel to the H1 publication # DESY-24-035 [arxiv:2403.10109] # # cross section tables have one row per bin, and multiple columns # describing the binninhg, cross sections, systematic uncertainties, # correction factors, predictions, ratios to predictions # # correlation coefficients apply to the statistical uncertainties only # they are given in the form of square matrices, the first row and # first column containing bin numbers. The correlation coefficients # are given in percent. # # The file is structured as follows # lines starting with # are comment lines # tables start with the keyword "table" followed by a table number. # next there is a table header, starting with "ibin", labelling the table columns # next there are table rows # next there is the keyword "Correlations" # followed by a table header starting with "ibin" # followed by correlation coefficient data # # # definition of the table columns # # ibin : bin number for use with statistical correlation coefficients # y_lo : lower bound on y for this bin # y_hi : upper bound on y for this bin # Q2_lo : lower bound on Q2 for this bin # Q2_hi : upper bound on Q2 for this bin # Sigma : measured cross section # stat[%] : statistical uncertainty # RCES[%] : RCES hadronic energy scale uncertainty # JES[%] : JES hadronic energy scale uncertainty # HadTh[%] : hadron polar angle uncertainty # ElEn[%] : electron energy scale uncertainty # ElTh[%] : electropn polar angle uncertainty # Model[%] : model uncertainty # MCstat[%] : Monte Carlo statistical uncertainty # Unfold[%] : unfolding uncertainty # ElecID[%] : electron identification uncertainty # Lumi[%] : luminosity uncertainty # Uncor[%] : uncorrelated systematic uncertainty # QEDerr[%] : QED correction uncertainty # c_QED : correction factor (already applied to sigma) # c_NoZ : optional correction factor # c_Born : optional correction factor # c_e+p : optional correction factor # c_Had : hadronisation correction for comparing to parton cross section predictions # HADerr[%] : uncertainty on c_Had # Django : Djanhoh prediction # Rapgap : Rapgap prediction table 38 # ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- # 2D cross sections d²σ/dQ²dy [pb/GeV²] # ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- ibin y_lo y_hi Q2_lo Q2_hi Sigma stat[%] RCES[%] JES[%] HadTh[%] ElEn[%] ElTh[%] Model[%] MCstat[%] Unfold[%] ElecID[%] Lumi[%] Uncor[%] QEDerr[%] c_QED c_NoZ c_Born c_e+p c_Had HADerr[%] Django Rapgap Pythia PyVinc PyDire Powheg Sherpa3 Sh2Stri Sh2Clus Herwig7 H7Merge H7Match NNLONLL CasSet1 CasSet2 # ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1 0.05 0.10 150 200 180.5 2.7 +2.2 +0.6 +0.9 +3.9 +1.3 -0.3 0.4 +0.0 0.2 2.7 0.5 0.2 1.070 0.996 0.924 1.000 1.000 0.0 181 182 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0.05 0.10 200 280 144.3 1.5 +1.7 +0.4 +0.3 -1.6 +0.7 +0.1 0.2 -0.1 0.2 2.7 0.5 0.2 1.070 0.994 0.923 1.000 1.000 0.0 143 143 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0.05 0.10 280 440 115.7 1.5 +1.6 +0.2 +0.3 -1.5 +0.7 +0.1 0.2 -0.0 0.2 2.7 0.5 0.2 1.064 0.998 0.919 1.000 1.000 0.0 116.1 116.6 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0.05 0.10 440 700 66.09 1.9 +1.3 +0.2 +0.1 -2.1 +0.4 -0.4 0.2 +0.1 0.2 2.7 0.5 0.2 1.063 0.997 0.919 1.000 1.000 0.0 65.79 65.87 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0.05 0.10 700 1100 35.45 2.1 +0.5 +0.1 -0.4 -1.2 +0.3 -1.0 0.2 -0.1 0.2 2.7 0.5 0.3 1.069 0.995 0.909 1.000 1.000 0.0 34.86 34.81 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0.10 0.20 150 200 222 1.4 +1.5 +0.4 +0.2 +1.8 +0.8 +0.8 0.2 -0.0 0.2 2.7 0.5 0.1 1.073 0.994 0.923 1.000 1.000 0.0 215.2 214.9 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0.10 0.20 200 280 175 1.1 +0.9 +0.1 -0.0 -1.4 +0.8 -0.0 0.1 +0.0 0.2 2.7 0.5 0.1 1.069 0.997 0.920 1.000 1.000 0.0 169.3 169.8 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0.10 0.20 280 440 140.6 1.2 +1.1 +0.1 +0.1 -1.2 +0.5 +0.1 0.1 -0.0 0.2 2.7 0.5 0.1 1.064 0.996 0.918 1.000 1.000 0.0 137.5 137.8 0 0 0 0 0 0 0 0 0 0 0 0 0 14 0.10 0.20 440 700 79.87 1.5 +1.3 +0.0 +0.0 -1.6 +0.5 -0.1 0.1 -0.0 0.2 2.7 0.5 0.2 1.066 0.997 0.916 1.000 1.000 0.0 77.51 77.72 0 0 0 0 0 0 0 0 0 0 0 0 0 15 0.10 0.20 700 1100 42.95 1.9 +1.3 -0.0 +0.0 -1.1 +0.4 +0.0 0.1 +0.0 0.2 2.7 0.5 0.2 1.062 0.996 0.915 1.000 1.000 0.0 41.08 41.32 0 0 0 0 0 0 0 0 0 0 0 0 0 16 0.10 0.20 1100 1700 22 2.5 +1.5 +0.1 -0.0 -1.6 +0.2 -0.9 0.1 -0.1 0.2 2.7 0.5 0.2 1.070 0.995 0.904 1.000 1.000 0.0 22.01 21.92 0 0 0 0 0 0 0 0 0 0 0 0 0 21 0.20 0.40 150 200 248 0.9 +0.8 +0.3 +0.0 -0.3 +0.7 +0.8 0.1 -0.0 0.2 2.7 0.5 0.1 1.074 0.997 0.923 1.000 1.000 0.0 240 240.4 0 0 0 0 0 0 0 0 0 0 0 0 0 22 0.20 0.40 200 280 196.6 1.0 +0.7 +0.0 -0.0 -1.0 +0.6 +0.7 0.1 -0.0 0.2 2.7 0.5 0.1 1.070 0.997 0.921 1.000 1.000 0.0 190.6 191.1 0 0 0 0 0 0 0 0 0 0 0 0 0 23 0.20 0.40 280 440 165.9 1.0 +0.8 +0.0 -0.0 -1.1 +0.5 +0.6 0.1 -0.0 0.2 2.7 0.5 0.1 1.068 0.998 0.919 1.000 1.000 0.0 155.3 155.8 0 0 0 0 0 0 0 0 0 0 0 0 0 24 0.20 0.40 440 700 96.09 1.3 +1.0 +0.0 -0.1 -1.4 +0.5 +0.4 0.1 -0.0 0.2 2.7 0.5 0.1 1.067 0.998 0.917 1.000 1.000 0.0 87.56 87.72 0 0 0 0 0 0 0 0 0 0 0 0 0 25 0.20 0.40 700 1100 51.72 1.6 +1.0 +0.0 -0.0 -0.9 +0.3 +0.6 0.1 -0.0 0.2 2.7 0.5 0.2 1.066 0.999 0.911 1.000 1.000 0.0 46.09 46.22 0 0 0 0 0 0 0 0 0 0 0 0 0 26 0.20 0.40 1100 1700 24.99 2.3 +1.4 -0.0 -0.0 -1.3 +0.3 -0.1 0.1 -0.0 0.2 2.7 0.5 0.2 1.062 1.000 0.912 1.000 1.000 0.0 24.33 24.44 0 0 0 0 0 0 0 0 0 0 0 0 0 27 0.20 0.40 1700 3500 19.34 2.7 +2.4 +0.0 +0.1 -2.1 +0.1 -0.9 0.1 -0.3 0.2 2.7 0.5 0.2 1.066 1.009 0.902 1.000 1.000 0.0 18.8 18.78 0 0 0 0 0 0 0 0 0 0 0 0 0 28 0.20 0.40 3500 8000 6.077 4.7 +4.0 -0.0 +0.6 -2.5 -0.0 -0.7 0.2 -0.3 1.0 2.7 0.5 0.4 1.068 1.029 0.905 1.000 1.000 0.0 6.969 6.957 0 0 0 0 0 0 0 0 0 0 0 0 0 29 0.20 0.40 8000 20000 0.8582 13.1 +4.7 +0.1 +1.1 -4.1 -0.5 -0.5 0.5 -0.1 1.0 2.7 0.5 1.0 1.076 1.072 0.889 1.000 1.000 0.0 1.186 1.171 0 0 0 0 0 0 0 0 0 0 0 0 0 31 0.40 0.70 150 200 203.2 1.2 -0.6 -1.2 -0.1 -0.6 +0.5 +2.6 0.1 -0.0 0.2 2.7 0.5 0.1 1.073 0.996 0.924 1.000 1.000 0.0 196.4 196.8 0 0 0 0 0 0 0 0 0 0 0 0 0 32 0.40 0.70 200 280 161.4 1.2 -0.4 -0.7 -0.1 -0.5 +0.4 +2.1 0.1 -0.0 0.2 2.7 0.5 0.1 1.069 0.996 0.922 1.000 1.000 0.0 157.2 157.7 0 0 0 0 0 0 0 0 0 0 0 0 0 33 0.40 0.70 280 440 132 1.3 -0.2 -0.4 -0.1 -0.7 +0.4 +1.7 0.1 -0.0 0.2 2.7 0.5 0.1 1.068 0.996 0.918 1.000 1.000 0.0 129.4 130 0 0 0 0 0 0 0 0 0 0 0 0 0 34 0.40 0.70 440 700 76.04 1.6 +0.3 -0.2 -0.1 -0.8 +0.3 +1.3 0.1 -0.0 0.2 2.7 0.5 0.1 1.071 0.997 0.914 1.000 1.000 0.0 73.58 73.8 0 0 0 0 0 0 0 0 0 0 0 0 0 35 0.40 0.70 700 1100 38.58 1.9 +0.4 -0.1 -0.1 -0.8 +0.3 +0.7 0.1 -0.0 0.2 2.7 0.5 0.2 1.066 1.002 0.912 1.000 1.000 0.0 38.68 38.86 0 0 0 0 0 0 0 0 0 0 0 0 0 36 0.40 0.70 1100 1700 21.12 2.7 +0.9 -0.0 -0.1 -1.1 +0.2 +0.5 0.2 -0.1 0.2 2.7 0.5 0.2 1.064 1.007 0.909 1.000 1.000 0.0 20.26 20.33 0 0 0 0 0 0 0 0 0 0 0 0 0 37 0.40 0.70 1700 3500 16.83 3.0 +1.7 -0.0 -0.0 -1.2 +0.1 +0.4 0.2 -0.1 0.2 2.7 0.5 0.3 1.072 1.016 0.899 1.000 1.000 0.0 15.51 15.36 0 0 0 0 0 0 0 0 0 0 0 0 0 38 0.40 0.70 3500 8000 6.128 4.3 +2.5 -0.0 +0.0 -1.9 -0.1 -0.9 0.2 -0.5 1.0 2.7 0.5 0.4 1.062 1.076 0.898 1.000 1.000 0.0 5.82 5.764 0 0 0 0 0 0 0 0 0 0 0 0 0 39 0.40 0.70 8000 20000 1.538 9.2 +4.7 -0.1 +0.4 -3.2 -0.3 -1.2 0.5 -0.8 1.0 2.7 0.5 0.9 1.066 1.206 0.898 1.000 1.000 0.0 1.49 1.497 0 0 0 0 0 0 0 0 0 0 0 0 0 45 0.70 0.94 700 1100 19.83 4.5 -1.8 -0.5 -0.1 +0.3 +0.1 +1.1 0.3 -0.0 0.2 2.7 0.5 0.2 1.071 0.999 0.913 1.000 1.000 0.0 20.8 20.87 0 0 0 0 0 0 0 0 0 0 0 0 0 46 0.70 0.94 1100 1700 10.73 4.7 -0.3 -0.2 -0.0 +0.1 +0.1 +2.3 0.3 -0.0 0.2 2.7 0.5 0.3 1.070 1.000 0.904 1.000 1.000 0.0 10.95 10.92 0 0 0 0 0 0 0 0 0 0 0 0 0 47 0.70 0.94 1700 3500 7.528 4.6 +0.3 -0.2 -0.1 -0.3 +0.2 +1.3 0.3 -0.3 0.2 2.7 0.5 0.4 1.063 1.024 0.900 1.000 1.000 0.0 8.237 8.156 0 0 0 0 0 0 0 0 0 0 0 0 0 48 0.70 0.94 3500 8000 3.205 6.6 +1.4 +0.3 -0.0 -1.1 +0.1 +4.8 0.5 -0.3 1.0 2.7 0.5 0.6 1.050 1.104 0.901 1.000 1.000 0.0 3.008 3.05 0 0 0 0 0 0 0 0 0 0 0 0 0 49 0.70 0.94 8000 20000 0.7364 14.5 +2.8 +0.4 +0.0 -2.3 -0.7 +6.3 1.1 -1.4 1.0 2.7 0.5 1.2 1.090 1.360 0.896 1.000 1.000 0.0 0.7962 0.7953 0 0 0 0 0 0 0 0 0 0 0 0 0 # ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Correlations ibin 1 2 3 4 5 11 12 13 14 15 16 21 22 23 24 25 26 27 28 29 31 32 33 34 35 36 37 38 39 45 46 47 48 49 1 100 -23 3 0 0 -23 5 -1 0 -0 0 4 -1 0 -0 0 -0 0 0 0 -0 0 -0 0 -0 -0 -0 0 0 0 -0 -0 -0 -0 2 -23 100 -11 1 0 4 -24 3 -0 -0 0 -0 4 -1 0 0 -0 0 0 0 0 -1 0 0 -0 0 -0 0 0 0 -0 -0 -0 -0 3 3 -11 100 -6 1 -0 2 -21 1 -0 0 1 -0 3 -0 0 -0 0 0 0 0 -0 -0 0 -0 0 -0 0 0 0 -0 -0 -0 -0 4 0 1 -6 100 -6 0 -0 1 -19 1 0 0 -0 -0 3 -0 -0 0 0 0 0 -0 0 -0 0 -0 -0 0 0 0 -0 -0 -0 -0 5 0 0 1 -6 100 0 -0 -0 1 -19 0 1 -0 0 -0 2 -0 0 0 0 0 -0 0 0 -0 0 -0 0 0 0 -0 -0 -0 -0 11 -23 4 -0 0 0 100 -19 2 -0 0 0 -19 3 -0 0 0 -0 0 0 0 3 -1 0 0 0 0 0 -0 0 0 0 0 0 0 12 5 -24 2 -0 -0 -19 100 -11 1 -0 -0 3 -18 2 -0 0 0 -0 -0 -0 -0 3 -0 0 0 0 0 -0 -0 -0 0 0 0 0 13 -1 3 -21 1 -0 2 -11 100 -7 0 -0 -0 1 -17 1 -0 0 -0 -0 -0 0 -0 2 -0 0 0 0 -0 -0 -0 0 0 0 0 14 0 -0 1 -19 1 -0 1 -7 100 -7 0 -0 -0 1 -15 1 -0 -0 -0 -0 -0 0 -0 2 -0 0 -0 -0 -0 0 0 0 0 0 15 -0 -0 -0 1 -19 0 -0 0 -7 100 -7 -0 0 -0 1 -14 1 -0 -0 -0 -0 0 -0 -0 1 -0 0 -0 -0 -0 0 0 0 0 16 0 0 0 0 0 0 -0 -0 0 -7 100 0 -0 0 -0 1 -12 0 0 0 0 -0 0 0 -0 1 -0 0 0 0 -0 -0 -0 -0 21 4 -0 1 0 1 -19 3 -0 -0 -0 0 100 -15 2 -0 0 -0 0 0 0 -15 3 -0 0 0 0 0 -0 0 0 0 0 1 0 22 -1 4 -0 -0 -0 3 -18 1 -0 0 -0 -15 100 -10 1 -0 0 -0 -0 -0 1 -15 2 -0 0 0 0 -0 -0 -0 0 0 0 0 23 0 -1 3 -0 0 -0 2 -17 1 -0 0 2 -10 100 -7 1 -0 0 0 0 0 1 -14 1 -0 0 -0 -0 0 0 0 0 0 0 24 -0 0 -0 3 -0 0 -0 1 -15 1 -0 -0 1 -7 100 -8 1 -0 -0 -0 0 0 1 -12 1 -0 0 -0 0 -0 0 0 0 0 25 0 0 0 -0 2 0 0 -0 1 -14 1 0 -0 1 -8 100 -7 0 -0 0 0 0 -0 0 -11 1 -0 -0 0 1 -0 0 0 0 26 -0 -0 -0 -0 -0 -0 0 0 -0 1 -12 -0 0 -0 1 -7 100 -6 0 -0 -0 0 -0 -0 1 -10 1 -0 0 -0 1 -0 -0 -0 27 0 0 0 0 0 0 -0 -0 -0 -0 0 0 -0 0 -0 0 -6 100 -4 0 0 -0 0 0 -0 0 -8 0 -0 0 -0 1 -0 -0 28 0 0 0 0 0 0 -0 -0 -0 -0 0 0 -0 0 -0 -0 0 -4 100 -3 0 -0 0 0 -0 -0 0 -9 0 0 -0 -0 0 -0 29 0 0 0 0 0 0 -0 -0 -0 -0 0 0 -0 0 -0 0 -0 0 -3 100 0 -0 0 0 0 0 -0 -0 -8 0 -0 -0 0 0 31 -0 0 0 0 0 3 -0 0 -0 -0 0 -15 1 0 0 0 -0 0 0 0 100 -13 2 0 0 0 0 -0 0 0 1 1 3 1 32 0 -1 -0 -0 -0 -1 3 -0 0 0 -0 3 -15 1 0 0 0 -0 -0 -0 -13 100 -10 1 0 0 0 -0 0 0 1 1 2 1 33 -0 0 -0 0 0 0 -0 2 -0 -0 0 -0 2 -14 1 -0 -0 0 0 0 2 -10 100 -9 1 -0 0 -0 0 0 0 0 1 0 34 0 0 0 -0 0 0 0 -0 2 -0 0 0 -0 1 -12 0 -0 0 0 0 0 1 -9 100 -8 1 -0 -0 0 0 0 0 1 0 35 -0 -0 -0 0 -0 0 0 0 -0 1 -0 0 0 -0 1 -11 1 -0 -0 0 0 0 1 -8 100 -8 0 -0 0 -9 1 0 0 0 36 -0 0 0 -0 0 0 0 0 0 -0 1 0 0 0 -0 1 -10 0 -0 0 0 0 -0 1 -8 100 -6 0 -0 0 -6 1 0 0 37 -0 -0 -0 -0 -0 0 0 0 -0 0 -0 0 0 -0 0 -0 1 -8 0 -0 0 0 0 -0 0 -6 100 -4 0 -0 0 -8 0 -0 38 0 0 0 0 0 -0 -0 -0 -0 -0 0 -0 -0 -0 -0 -0 -0 0 -9 -0 -0 -0 -0 -0 -0 0 -4 100 -4 -0 -0 0 -6 0 39 0 0 0 0 0 0 -0 -0 -0 -0 0 0 -0 0 0 0 0 -0 0 -8 0 0 0 0 0 -0 0 -4 100 0 0 -0 0 -6 45 0 0 0 0 0 0 -0 -0 0 -0 0 0 -0 0 -0 1 -0 0 0 0 0 0 0 0 -9 0 -0 -0 0 100 -10 1 0 0 46 -0 -0 -0 -0 -0 0 0 0 0 0 -0 0 0 0 0 -0 1 -0 -0 -0 1 1 0 0 1 -6 0 -0 0 -10 100 -7 3 1 47 -0 -0 -0 -0 -0 0 0 0 0 0 -0 0 0 0 0 0 -0 1 -0 -0 1 1 0 0 0 1 -8 0 -0 1 -7 100 -3 1 48 -0 -0 -0 -0 -0 0 0 0 0 0 -0 1 0 0 0 0 -0 -0 0 0 3 2 1 1 0 0 0 -6 0 0 3 -3 100 -3 49 -0 -0 -0 -0 -0 0 0 0 0 0 -0 0 0 0 0 0 -0 -0 -0 0 1 1 0 0 0 0 -0 0 -6 0 1 1 -3 100