df106_HiggsToFourLeptons.py File Reference

Namespaces
namespace	df106_HiggsToFourLeptons

Detailed Description

The Higgs to four lepton analysis from the ATLAS Open Data release of 2020, with RDataFrame.

This tutorial is the Higgs to four lepton analysis from the ATLAS Open Data release in 2020 (http://opendata.atlas.cern/release/2020/documentation/). The data was taken with the ATLAS detector during 2016 at a center-of-mass energy of 13 TeV. The decay of the Standard Model Higgs boson to two Z bosons and subsequently to four leptons is called the "golden channel". The selection leads to a narrow invariant mass peak on top a relatively smooth and small background, revealing the Higgs at 125 GeV.

The analysis is translated to a RDataFrame workflow processing about 300 MB of simulated events and data.

## \date May 2023
 
import ROOT
import os
 
# Create the RDataFrame from the spec json file. The df106_HiggsToFourLeptons_spec.json is provided in the same folder as this tutorial
 
my_spec = os.path.join(ROOT.gROOT.GetTutorialsDir(), "dataframe", "df106_HiggsToFourLeptons_spec.json")
 
df = ROOT.RDF.Experimental.FromSpec(my_spec) # Creates a single dataframe for all the samples
 
# Access metadata information that is stored in the JSON config file of the RDataFrame
# The metadata contained in the JSON file is accessible within a `DefinePerSample` call, through the `RDFSampleInfo` class
 
# Add the ProgressBar feature
 
ROOT.RDF.Experimental.AddProgressbar(df) 
 
df = df.DefinePerSample("xsecs", 'rdfsampleinfo_.GetD("xsecs")')
df = df.DefinePerSample("lumi", 'rdfsampleinfo_.GetD("lumi")') 
df = df.DefinePerSample("sumws", 'rdfsampleinfo_.GetD("sumws")')
df = df.DefinePerSample("sample_category", 'rdfsampleinfo_.GetS("sample_category")')
 
# Select events for the analysis
 
ROOT.gInterpreter.Declare("""
using cRVecF = const ROOT::RVecF &;
bool GoodElectronsAndMuons(const ROOT::RVecI & type, cRVecF pt, cRVecF eta, cRVecF phi, cRVecF e, cRVecF trackd0pv, cRVecF tracksigd0pv, cRVecF z0)
{
    for (size_t i = 0; i < type.size(); i++) {
        ROOT::Math::PtEtaPhiEVector p(pt[i] / 1000.0, eta[i], phi[i], e[i] / 1000.0);
        if (type[i] == 11) {
            if (pt[i] < 7000 || abs(eta[i]) > 2.47 || abs(trackd0pv[i] / tracksigd0pv[i]) > 5 || abs(z0[i] * sin(p.Theta())) > 0.5) return false;
        } else {
            if (abs(trackd0pv[i] / tracksigd0pv[i]) > 5 || abs(z0[i] * sin(p.Theta())) > 0.5) return false;
        }
    }
    return true;
}
""")
 
# Select electron or muon trigger
df = df.Filter("trigE || trigM")
 
# Select events with exactly four good leptons conserving charge and lepton numbers
# Note that all collections are RVecs and good_lep is the mask for the good leptons.
# The lepton types are PDG numbers and set to 11 or 13 for an electron or muon
# irrespective of the charge.
 
df = df.Define("good_lep", "abs(lep_eta) < 2.5 && lep_pt > 5000 && lep_ptcone30 / lep_pt < 0.3 && lep_etcone20 / lep_pt < 0.3")\
       .Filter("Sum(good_lep) == 4")\
       .Filter("Sum(lep_charge[good_lep]) == 0")\
       .Define("goodlep_sumtypes", "Sum(lep_type[good_lep])")\
       .Filter("goodlep_sumtypes == 44 || goodlep_sumtypes == 52 || goodlep_sumtypes == 48")
 
# Apply additional cuts depending on lepton flavour
df = df.Filter("GoodElectronsAndMuons(lep_type[good_lep], lep_pt[good_lep], lep_eta[good_lep], lep_phi[good_lep], lep_E[good_lep], lep_trackd0pvunbiased[good_lep], lep_tracksigd0pvunbiased[good_lep], lep_z0[good_lep])")
 
# Create new columns with the kinematics of good leptons
df = df.Define("goodlep_pt", "lep_pt[good_lep]")\
       .Define("goodlep_eta", "lep_eta[good_lep]")\
       .Define("goodlep_phi", "lep_phi[good_lep]")\
       .Define("goodlep_E", "lep_E[good_lep]")
 
# Select leptons with high transverse momentum
df = df.Filter("goodlep_pt[0] > 25000 && goodlep_pt[1] > 15000 && goodlep_pt[2] > 10000")
 
# Reweighting of the samples is different for "data" and "MC". This is the function to add reweighting for MC samples
ROOT.gInterpreter.Declare("""
double weights(float scaleFactor_1, float scaleFactor_2, float scaleFactor_3, float scaleFactor_4, float mcWeight_, double xsecs_, double sumws_, double lumi_)
{
    double weight_ = scaleFactor_1 * scaleFactor_2 * scaleFactor_3 * scaleFactor_4 * mcWeight_ * xsecs_/sumws_ * lumi_;
    return (weight_);
}
""")
 
# Use DefinePerSample to define which samples need reweighting
df = df.DefinePerSample("reweighting", 'rdfsampleinfo_.Contains("mc")')
df = df.Define("weight", 'double x; if (reweighting) {return weights(scaleFactor_ELE, scaleFactor_MUON, scaleFactor_LepTRIGGER, scaleFactor_PILEUP, mcWeight, xsecs, sumws, lumi);} else {return 1.;}')
                        
# Compute invariant mass of the four lepton system and make a histogram
ROOT.gInterpreter.Declare("""
float ComputeInvariantMass(cRVecF pt, cRVecF eta, cRVecF phi, cRVecF e)
{
    ROOT::Math::PtEtaPhiEVector p1(pt[0], eta[0], phi[0], e[0]);
    ROOT::Math::PtEtaPhiEVector p2(pt[1], eta[1], phi[1], e[1]);
    ROOT::Math::PtEtaPhiEVector p3(pt[2], eta[2], phi[2], e[2]);
    ROOT::Math::PtEtaPhiEVector p4(pt[3], eta[3], phi[3], e[3]);
    return (p1 + p2 + p3 + p4).M() / 1000;
}
""")
df = df.Define("m4l", "ComputeInvariantMass(goodlep_pt, goodlep_eta, goodlep_phi, goodlep_E)")
 
# Book histograms for the four different samples: data, higgs, zz and other (this is specific to this particular analysis)
histos = [] 
for sample_category in ["data", "higgs", "zz", "other"]:
    histos.append(df.Filter(f"sample_category == \"{sample_category}\"").Histo1D(ROOT.RDF.TH1DModel(f"{sample_category}", "m4l", 24, 80, 170), "m4l", "weight"))
 
 
h_data = histos[0].GetValue()
h_higgs = histos[1].GetValue()
h_zz = histos[2].GetValue()
h_other = histos[3].GetValue()
 
# Apply MC correction for ZZ due to missing gg->ZZ process
h_zz.Scale(1.3) 
 
# Create the plot
 
# Set styles
ROOT.gROOT.SetStyle("ATLAS")
 
# Create canvas with pad
c = ROOT.TCanvas("c", "", 600, 600)
pad = ROOT.TPad("upper_pad", "", 0, 0, 1, 1)
pad.SetTickx(False)
pad.SetTicky(False)
pad.Draw()
pad.cd()
 
# Draw stack with MC contributions
 
stack = ROOT.THStack()
 
for h, color in zip([h_other, h_zz, h_higgs], [(155, 152, 204), (100, 192, 232), (191, 34, 41)]):
    h.SetLineWidth(1)
    h.SetLineColor(1)
    h.SetFillColor(ROOT.TColor.GetColor(*color))
    stack.Add(h)
 
stack.Draw("HIST")
stack.GetXaxis().SetLabelSize(0.04)
stack.GetXaxis().SetTitleSize(0.045)
stack.GetXaxis().SetTitleOffset(1.3)
stack.GetXaxis().SetTitle("m_{4l}^{H#rightarrow ZZ} [GeV]")
stack.GetYaxis().SetTitle("Events")
stack.GetYaxis().SetLabelSize(0.04)
stack.GetYaxis().SetTitleSize(0.045)
stack.SetMaximum(33)
stack.GetYaxis().ChangeLabel(1, -1, 0)
 
h_data.SetMarkerStyle(20)
h_data.SetMarkerSize(1.2)
h_data.SetLineWidth(2)
h_data.SetLineColor(ROOT.kBlack)
h_data.Draw("E SAME") #draw data with errorbars 
 
# Add legend
legend = ROOT.TLegend(0.60, 0.65, 0.92, 0.92)
legend.SetTextFont(42)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.04)
legend.SetTextAlign(32)
legend.AddEntry(h_data, "Data" ,"lep")
legend.AddEntry(h_higgs, "Higgs", "f")
legend.AddEntry(h_zz, "ZZ", "f")
legend.AddEntry(h_other, "Other", "f")
legend.Draw("SAME")
 
# Add ATLAS label
text = ROOT.TLatex()
text.SetNDC()
text.SetTextFont(72)
text.SetTextSize(0.045)
text.DrawLatex(0.21, 0.86, "ATLAS")
text.SetTextFont(42)
text.DrawLatex(0.21 + 0.16, 0.86, "Open Data")
text.SetTextSize(0.04)
text.DrawLatex(0.21, 0.80, "#sqrt{s} = 13 TeV, 10 fb^{-1}")
 
# Save the plot
c.SaveAs("df106_HiggsToFourLeptons.png")
print("Saved figure to df106_HiggsToFourLeptons.png")

|=>                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |   [Elapsed time: 0:15m  processing file: 5 / 9  processed evts: 1000 / 165548  6.56e+01 evt/s 41:46m  remaining time (per file)]   
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Saved figure to df106_HiggsToFourLeptons.png

Date

March 2020

Author

Stefan Wunsch (KIT, CERN)

Definition in file df106_HiggsToFourLeptons.py.