df104_HiggsToTwoPhotons¶
The Higgs to two photons analysis from the ATLAS Open Data 2020 release, with RDataFrame.
This tutorial is the Higgs to two photons 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. Although the Higgs to two photons decay is very rare, the contribution of the Higgs can be seen as a narrow peak around 125 GeV because of the excellent reconstruction and identification efficiency of photons at the ATLAS experiment.
The analysis is translated to a RDataFrame workflow processing 1.7 GB of simulated events and data.
Author: Stefan Wunsch (KIT, CERN)
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Monday, March 27, 2023 at 09:46 AM.
In [1]:
import ROOT
import os
Welcome to JupyROOT 6.29/01
Enable multi-threading
In [2]:
ROOT.ROOT.EnableImplicitMT()
Create a ROOT dataframe for each dataset
In [3]:
path = "root://eospublic.cern.ch//eos/opendata/atlas/OutreachDatasets/2020-01-22"
df = {}
df["data"] = ROOT.RDataFrame("mini", (os.path.join(path, "GamGam/Data/data_{}.GamGam.root".format(x)) for x in ("A", "B", "C", "D")))
df["ggH"] = ROOT.RDataFrame("mini", os.path.join(path, "GamGam/MC/mc_343981.ggH125_gamgam.GamGam.root"))
df["VBF"] = ROOT.RDataFrame("mini", os.path.join(path, "GamGam/MC/mc_345041.VBFH125_gamgam.GamGam.root"))
processes = list(df.keys())
Apply scale factors and MC weight for simulated events and a weight of 1 for the data
In [4]:
for p in ["ggH", "VBF"]:
df[p] = df[p].Define("weight",
"scaleFactor_PHOTON * scaleFactor_PhotonTRIGGER * scaleFactor_PILEUP * mcWeight");
df["data"] = df["data"].Define("weight", "1.0")
Plugin No such file or directory loading sec.protocol libXrdSeckrb5-5.so
Select the events for the analysis
In [5]:
for p in processes:
# Apply preselection cut on photon trigger
df[p] = df[p].Filter("trigP")
# Find two good muons with tight ID, pt > 25 GeV and not in the transition region between barrel and encap
df[p] = df[p].Define("goodphotons", "photon_isTightID && (photon_pt > 25000) && (abs(photon_eta) < 2.37) && ((abs(photon_eta) < 1.37) || (abs(photon_eta) > 1.52))")\
.Filter("Sum(goodphotons) == 2")
# Take only isolated photons
df[p] = df[p].Filter("Sum(photon_ptcone30[goodphotons] / photon_pt[goodphotons] < 0.065) == 2")\
.Filter("Sum(photon_etcone20[goodphotons] / photon_pt[goodphotons] < 0.065) == 2")
Compile a function to compute the invariant mass of the diphoton system
In [6]:
ROOT.gInterpreter.Declare(
"""
using namespace ROOT;
float ComputeInvariantMass(RVecF pt, RVecF eta, RVecF phi, RVecF 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]);
return (p1 + p2).mass() / 1000.0;
}
""")
Out[6]:
True
Define a new column with the invariant mass and perform final event selection
In [7]:
hists = {}
for p in processes:
# Make four vectors and compute invariant mass
df[p] = df[p].Define("m_yy", "ComputeInvariantMass(photon_pt[goodphotons], photon_eta[goodphotons], photon_phi[goodphotons], photon_E[goodphotons])")
# Make additional kinematic cuts and select mass window
df[p] = df[p].Filter("photon_pt[goodphotons][0] / 1000.0 / m_yy > 0.35")\
.Filter("photon_pt[goodphotons][1] / 1000.0 / m_yy > 0.25")\
.Filter("m_yy > 105 && m_yy < 160")
# Book histogram of the invariant mass with this selection
hists[p] = df[p].Histo1D(
ROOT.RDF.TH1DModel(p, "Diphoton invariant mass; m_{#gamma#gamma} [GeV];Events", 30, 105, 160),
"m_yy", "weight")
Run the event loop
RunGraphs allows to run the event loops of the separate RDataFrame graphs concurrently. This results in an improved usage of the available resources if each separate RDataFrame can not utilize all available resources, e.g., because not enough data is available.
In [8]:
ROOT.RDF.RunGraphs([hists[s] for s in ["ggH", "VBF", "data"]])
ggh = hists["ggH"].GetValue()
vbf = hists["VBF"].GetValue()
data = hists["data"].GetValue()
Create the plot
Set styles
In [9]:
ROOT.gROOT.SetStyle("ATLAS")
Create canvas with pads for main plot and data/MC ratio
In [10]:
c = ROOT.TCanvas("c", "", 700, 750)
upper_pad = ROOT.TPad("upper_pad", "", 0, 0.35, 1, 1)
lower_pad = ROOT.TPad("lower_pad", "", 0, 0, 1, 0.35)
for p in [upper_pad, lower_pad]:
p.SetLeftMargin(0.14)
p.SetRightMargin(0.05)
p.SetTickx(False)
p.SetTicky(False)
upper_pad.SetBottomMargin(0)
lower_pad.SetTopMargin(0)
lower_pad.SetBottomMargin(0.3)
upper_pad.Draw()
lower_pad.Draw()
Fit signal + background model to data
In [11]:
fit = ROOT.TF1("fit", "([0]+[1]*x+[2]*x^2+[3]*x^3)+[4]*exp(-0.5*((x-[5])/[6])^2)", 105, 160)
fit.FixParameter(5, 125.0)
fit.FixParameter(4, 119.1)
fit.FixParameter(6, 2.39)
fit.SetLineColor(2)
fit.SetLineStyle(1)
fit.SetLineWidth(2)
data.Fit("fit", "0", "", 105, 160)
Out[11]:
<cppyy.gbl.TFitResultPtr object at 0x41449760>
FCN=19.9699 FROM HESSE STATUS=NOT POSDEF 23 CALLS 158 TOTAL
EDM=3.65047e-12 STRATEGY= 1 ERR MATRIX NOT POS-DEF
EXT PARAMETER APPROXIMATE STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 p0 9.43252e+04 7.20516e+01 2.24889e-02 8.93365e-09
2 p1 -1.77723e+03 7.78152e-01 4.23724e-04 -1.87354e-06
3 p2 1.15606e+01 5.36057e-03 2.75626e-06 -1.80941e-04
4 p3 -2.56282e-02 2.66823e-05 6.11023e-09 3.02615e-02
5 p4 1.19100e+02 fixed
6 p5 1.25000e+02 fixed
7 p6 2.39000e+00 fixed
Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S Error in <TFitResultPtr>: TFitResult is empty - use the fit option S
Draw data
In [12]:
upper_pad.cd()
data.SetMarkerStyle(20)
data.SetMarkerSize(1.2)
data.SetLineWidth(2)
data.SetLineColor(ROOT.kBlack)
data.SetMinimum(1e-3)
data.SetMaximum(8e3)
data.GetYaxis().SetLabelSize(0.045)
data.GetYaxis().SetTitleSize(0.05)
data.SetStats(0)
data.SetTitle("")
data.Draw("E")
Draw fit
In [13]:
fit.Draw("SAME")
Draw background
In [14]:
bkg = ROOT.TF1("bkg", "([0]+[1]*x+[2]*x^2+[3]*x^3)", 105, 160)
for i in range(4):
bkg.SetParameter(i, fit.GetParameter(i))
bkg.SetLineColor(4)
bkg.SetLineStyle(2)
bkg.SetLineWidth(2)
bkg.Draw("SAME")
Scale simulated events with luminosity * cross-section / sum of weights and merge to single Higgs signal
In [15]:
lumi = 10064.0
ggh.Scale(lumi * 0.102 / 55922617.6297)
vbf.Scale(lumi * 0.008518764 / 3441426.13711)
higgs = ggh.Clone()
higgs.Add(vbf)
higgs.Draw("HIST SAME")
Draw ratio
In [16]:
lower_pad.cd()
ratiobkg = ROOT.TH1I("zero", "", 100, 105, 160)
ratiobkg.SetLineColor(4)
ratiobkg.SetLineStyle(2)
ratiobkg.SetLineWidth(2)
ratiobkg.SetMinimum(-125)
ratiobkg.SetMaximum(250)
ratiobkg.GetXaxis().SetLabelSize(0.08)
ratiobkg.GetXaxis().SetTitleSize(0.12)
ratiobkg.GetXaxis().SetTitleOffset(1.0)
ratiobkg.GetYaxis().SetLabelSize(0.08)
ratiobkg.GetYaxis().SetTitleSize(0.09)
ratiobkg.GetYaxis().SetTitle("Data - Bkg.")
ratiobkg.GetYaxis().CenterTitle()
ratiobkg.GetYaxis().SetTitleOffset(0.7)
ratiobkg.GetYaxis().SetNdivisions(503, False)
ratiobkg.GetYaxis().ChangeLabel(-1, -1, 0)
ratiobkg.GetXaxis().SetTitle("m_{#gamma#gamma} [GeV]")
ratiobkg.Draw("AXIS")
ratiosig = ROOT.TH1F("ratiosig", "ratiosig", 5500, 105, 160)
ratiosig.Eval(fit)
ratiosig.SetLineColor(2)
ratiosig.SetLineStyle(1)
ratiosig.SetLineWidth(2)
ratiosig.Add(bkg, -1)
ratiosig.Draw("SAME")
ratiodata = data.Clone()
ratiodata.Add(bkg, -1)
for i in range(1, data.GetNbinsX()):
ratiodata.SetBinError(i, data.GetBinError(i))
ratiodata.Draw("E SAME")
Add legend
In [17]:
upper_pad.cd()
legend = ROOT.TLegend(0.55, 0.55, 0.89, 0.85)
legend.SetTextFont(42)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.05)
legend.SetTextAlign(32)
legend.AddEntry(data, "Data" ,"lep")
legend.AddEntry(bkg, "Background", "l")
legend.AddEntry(fit, "Signal + Bkg.", "l")
legend.AddEntry(higgs, "Signal", "l")
legend.Draw()
Add ATLAS label
In [18]:
text = ROOT.TLatex()
text.SetNDC()
text.SetTextFont(72)
text.SetTextSize(0.05)
text.DrawLatex(0.18, 0.84, "ATLAS")
text.SetTextFont(42)
text.DrawLatex(0.18 + 0.13, 0.84, "Open Data")
text.SetTextSize(0.04)
text.DrawLatex(0.18, 0.78, "#sqrt{s} = 13 TeV, 10 fb^{-1}")
Out[18]:
<cppyy.gbl.TLatex object at 0x4295dcc0>
Save the plot
In [19]:
c.SaveAs("df104_HiggsToTwoPhotons.png")
print("Saved figure to df104_HiggsToTwoPhotons.png")
Saved figure to df104_HiggsToTwoPhotons.png
Info in <TCanvas::Print>: png file df104_HiggsToTwoPhotons.png has been created
Draw all canvases
In [20]:
from ROOT import gROOT
gROOT.GetListOfCanvases().Draw()
