{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
" ![](\"../../images/ATLASOD.gif\")
\n",
""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Searching for the Higgs boson in the H→γγ channel
\n",
"\n",
"\n",
"SM Higgs signal Feynman diagram:\n",
"![](\"../../images/Figures_FeynmanHprod.png\")
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Introduction**\n",
"Let's take a current ATLAS Open Data sample and create a histogram:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Welcome to JupyROOT 6.18/04\n"
]
}
],
"source": [
"import ROOT\n",
"from ROOT import TMath\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"%jsroot on"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"start = time.time()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"f = ROOT.TFile.Open(\"https://atlas-opendata.web.cern.ch/atlas-opendata/samples/2020/GamGam/Data/data_A.GamGam.root\")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"canvas = ROOT.TCanvas(\"Canvas\",\"cz\",800,600)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"tree = f.Get(\"mini\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"430344"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tree.GetEntries()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we're going to extract the photons variables"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"#Invariant mass histograms definition\n",
"hist = ROOT.TH1F(\"h_M_Hyy\",\"Diphoton invariant-mass ; Invariant Mass m_{yy} [GeV] ; events\",30,105,160)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we're filling the variables defined above with the content of those inside the input ntuples."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We're creating a histogram for this example. The plan is to fill them with events."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We are selecting below a simple look for them."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The Higgs boson analysis implemented here considers Higgs boson decays into a photon-photon pair. The event selection criteria are:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10000\n",
"20000\n",
"30000\n",
"40000\n",
"50000\n",
"60000\n",
"70000\n",
"80000\n",
"90000\n",
"100000\n",
"110000\n",
"120000\n",
"130000\n",
"140000\n",
"150000\n",
"160000\n",
"170000\n",
"180000\n",
"190000\n",
"200000\n",
"210000\n",
"220000\n",
"230000\n",
"240000\n",
"250000\n",
"260000\n",
"270000\n",
"280000\n",
"290000\n",
"300000\n",
"310000\n",
"320000\n",
"330000\n",
"340000\n",
"350000\n",
"360000\n",
"370000\n",
"380000\n",
"390000\n",
"400000\n",
"410000\n",
"420000\n",
"430000\n"
]
}
],
"source": [
"Photon_1 = ROOT.TLorentzVector()\n",
"Photon_2 = ROOT.TLorentzVector()\n",
"n = 0\n",
"for event in tree:\n",
" n += 1\n",
" ## printing the evolution in number of events\n",
" if(n%10000==0):\n",
" print(n)\n",
" ## checking the trigger \n",
" if(tree.trigP):\n",
" goodphoton_index = [0]*5\n",
" goodphoton_n = 0\n",
" photon_index = 0\n",
" ## \n",
" j=0\n",
" ## looping the photons per event\n",
" for j in range(tree.photon_n):\n",
" ##\n",
" if(tree.photon_isTightID[j]):\n",
" ##\n",
" if(tree.photon_pt[j] > 25000 and (TMath.Abs(tree.photon_eta[j]) < 2.37)\\\n",
" and (TMath.Abs(tree.photon_eta[j]) < 1.37 or TMath.Abs(tree.photon_eta[j]) > 1.52)):\n",
" ##\n",
" goodphoton_n += 1 #count\n",
" goodphoton_index[photon_index]=j\n",
" photon_index += 1\n",
" ## end Pt and eta pre-selection\n",
" ## end on request of quality of the photon\n",
" ## end looping photons in the current event\n",
" \n",
" ## Using the two selected photons\n",
" if(goodphoton_n==2):\n",
" ##\n",
" goodphoton1_index = goodphoton_index[0]\n",
" goodphoton2_index = goodphoton_index[1]\n",
" ## Getting couple of photons with good isolation \n",
" if((tree.photon_ptcone30[goodphoton1_index]/tree.photon_pt[goodphoton1_index] < 0.065)\\\n",
" and (tree.photon_etcone20[goodphoton1_index] / tree.photon_pt[goodphoton1_index] < 0.065)):\n",
" ##\n",
" if((tree.photon_ptcone30[goodphoton2_index]/tree.photon_pt[goodphoton2_index] < 0.065)\\\n",
" and (tree.photon_etcone20[goodphoton2_index] / tree.photon_pt[goodphoton2_index] < 0.065)):\n",
" ##\n",
" Photon_1.SetPtEtaPhiE(tree.photon_pt[goodphoton1_index]/1000., tree.photon_eta[goodphoton1_index],\\\n",
" tree.photon_phi[goodphoton1_index],tree.photon_E[goodphoton1_index]/1000.)\n",
" Photon_2.SetPtEtaPhiE(tree.photon_pt[goodphoton2_index]/1000., tree.photon_eta[goodphoton2_index],\\\n",
" tree.photon_phi[goodphoton2_index],tree.photon_E[goodphoton2_index]/1000.)\n",
" ## Adding the two TLorentz vectors\n",
" Photon_12 = Photon_1 + Photon_2\n",
" ## Filling with the mass of the gamma-gamma system\n",
" hist.Fill(Photon_12.M())\n",
" ## end isolation photon #2\n",
" ## end isolation photon #1\n",
" ## end 2-good photons\n",
" ## end of trigger request\n",
"## End loop in the events"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Final plot"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hist.Draw(\"E\")\n",
"canvas.Draw()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Log Scale"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
"\n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hist.Draw(\"E\")\n",
"hist.SetMinimum(10)\n",
"canvas.SetLogy()\n",
"canvas.Draw()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Finished in 0 min 41 s\n"
]
}
],
"source": [
"end = time.time()\n",
"duration = end-start\n",
"print(\"Finished in {} min {} s\".format(int(duration//60),int(duration%60))) # Python3"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"**Done!**"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.9"
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