E. Soldatov 01.09.2011
Tight photon efficiency study using FSR photons Tight photon efficiency study using FSR photons fromfrom ZZ decay decay
E.Yu.Soldatov*
*National Research Nuclear University “MEPhI”
Outline:
1. MC study of the chosen sample
2. Background estimation study
3. Tight cut study
Photon ID efficiencies meeting
E. Soldatov
IntroductionIntroduction
№ 2
1. Mass of two leptons should have a missing part e.g. < Z bozon mass
For electron channel 60 < m(ee) < 83 GeV, and for muon channel 40 < m() < 82 GeV
A kinematic approach of the photon selection
2. And 3 body mass should correspond to a mass of Z bozon
For electron channel 80 < m(ee)< 94 GeV and for muon channel 81 < m() < 95 GeV
Kinematics approach is based on a simple criteria of the event selection.
Background-ISR-Brem-Jets
-FSRSignal
Three body mass spectrum (Z)
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IntroductionIntroduction
A “minor” problem: a small production cross section.
What do we want?
The main idea is to obtain a photon sample with maximum purity with the method decoupled from the standard analysis
methods. Why do we want this?
Studies of the ATLAS detector performance with tagged photons and first of all study and optimization of the tight cut criteria.
Very important for analysis all photon containing processes.
The best source of such kind of photons is a production of
FSR photons from Z-lepton decay:
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Photon purity after all cuts appliedPhoton purity after all cuts applied
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Purity of the sample after Et (in cone 0.2)<3 GeV and N=0 cuts
Figure. Purity of the sample as a function of photon energy
Purity=Signal/(Signal+Background)
Et cut [GeV]
Differential purity for each bin.
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TightTight cut efficiency studycut efficiency study
Efficiency of robust tight cut on signal (lift) and on background (right) vs Et photon spectrum, Et (in cone 0.2)<3 GeV
ET [GeV]
- Sgn sample MC
- Data 2011
ET [GeV]
- Bkg sample MC
- Data 2011
Signal Background
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Tight CUT efficiency for signal sample Tight CUT efficiency for background sample
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TightTight cut efficiency studycut efficiency study
Efficiency of robust tight cut on signal (lift) and on background (right) vs Et photon spectrum, Et (in cone 0.2)<3 GeV (barrel only)
Signal Background
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Tight CUT efficiency for signal sample Tight CUT efficiency for background sample
ET [GeV]ET [GeV]
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TightTight cut efficiency studycut efficiency study
Efficiency of robust tight cut on signal (lift) and on background (right) vs Et photon spectrum, Et (in cone 0.2)<3 GeV
ET [GeV]
Signal Background
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Tight CUT efficiency for signal sample Tight CUT efficiency for background sample
ET [GeV]
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TightTight cut efficiency studycut efficiency study
Multiplicity for data
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TightTight cut efficiency studycut efficiency study
For multiplicity<5
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TightTight cut efficiency studycut efficiency study
For multiplicity>6
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Effect of background uncertainty on the tight cut efficiencyEffect of background uncertainty on the tight cut efficiency
Background estimation from MC
5-10 GeV 15-20 GeV
MC Purity=0.827 (slide 11)
S+B Efficiency=0.17 (sl.20)
Bkg Efficiency=0.06 (sl.20)
MC Purity=0.973 (slide 11)
S+B Efficiency=0.53 (sl.20)
Bkg Efficiency=0.32 (sl.20)
S Efficiency=(0.17-0.06*0.173)/0.827=0.193 S Efficiency=(0.53-0.32*0.027)/0.973=0.5358
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Correction gives us uncertainty: (0.193-0.17)/0.17*100%=13.5%
Correction gives us uncertainty: (0.5358-0.53)/0.53*100%=1%
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Data driven background estimationData driven background estimationWork of the background estimation method on real data
Cut Et (in cone 0.2)<3 GeVREAL DATA
ET()>5 GeV, ET()<10 GeV
N (tracks in cone20)
First bin: Data=2312; Bkg estimation=853 => Purity=0.631№ 1201.09.2011Photon ID efficiencies
meeting
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Data driven background estimationData driven background estimationWork of the background estimation method on real data
Cut Et (in cone 0.2)<3 GeVREAL DATA
First bin: Data=774; Bkg estimation=66 => Purity=0.915
ET()>15 GeV, ET()<20 GeV
N (tracks in cone20)
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5-10 GeV 15-20 GeV
Estimated Purity=0.631 (sl.22)
S+B Efficiency=0.17 (sl.20)
Bkg Efficiency=0.06 (sl.20)
Estimated Purity=0.915 (sl.23)
S+B Efficiency=0.53 (sl.20)
Bkg Efficiency=0.32 (sl.20)
S Efficiency=(0.17-0.06*0.369)/0.631=0.234
Correction gives us uncertainty:(0.234-0.17)/0.17*100%=38%
Uncertainty due to the method:
(0.234-0.193)/0.193*100%=21%
S Efficiency=(0.53-0.32*0.085)/0.915=0.5495
Correction gives us uncertainty:(0.5495-0.53)/0.53*100%=3.7%
Uncertainty due to the method:
(0.5495-0.5358)/0.5358*100%=2.5%
Effect of background uncertainty on the tight cut efficiencyEffect of background uncertainty on the tight cut efficiency
Background estimate – data driven
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TightTight cut efficiency study (Z->eecut efficiency study (Z->ee))
Efficiency of robust tight cut on signal (lift) and on background (right) vs Et photon spectrum, Et (in cone 0.2)<3 GeV
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ET [GeV]ET [GeV]
SignalBackground
Tight CUT efficiency for signal sample Tight CUT efficiency for background sample
electron channel
Photon purity after all cuts applied (Z->eePhoton purity after all cuts applied (Z->ee))
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Purity of the sample after Et (in cone 0.2)<3 GeV and N=0 cuts
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Et cut [GeV]
MC purity of the sample:
Estimated purity from here:
ET()>5 GeV
ET()>15 GeVData driven estimation of the background amount in the first bin
electron channel
E. Soldatov
5-10 GeV 15-20 GeV
MC Purity=0.593 (slide 26)
Estimated Purity=0.582 (sl.26)
S+B Efficiency=0.15 (sl.25)
Bkg Efficiency=0.06 (sl.25)
MC Purity=0.96 (slide 26)
Estimated Purity=0.909 (sl.26)
S+B Efficiency=0.55 (sl.25)
Bkg Efficiency=0.26 (sl.25)
S Eff (MC pur)=(0.15-0.06*0.407)/0.593=0.212
S Eff (Est pur)=(0.15-0.06*0.418)/0.582=0.215
Uncertainty due to the method:
(0.215-0.212)/0.212*100%=1.4%
S Eff (MC pur)=(0.55-0.26*0.04)/0.96=0.562
S Eff (MC est)=(0.55-0.26*0.091)/0.909=0.579
Uncertainty due to the method:
(0.579-0.562)/0.562*100%=3%
Effect of background uncertainty on the tight cut efficiency (Z->eeEffect of background uncertainty on the tight cut efficiency (Z->ee))
Background estimate – MC&data driven
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electron channel
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ConclusionsConclusions
The improvement of signal selection has been done. The purity became larger than 97% for 15 GeV photon sample.
Monte Carlo simulation has been compared with the 2011 Data (periods D-I with ~1.33 fb-1 of integral luminocity).
To improve the agreement between simulation and data background estimation method from data has been proposed and implemented.
Tight cut efficiency has been estimated using two methods of sample purity estimation. Efficiency from data has significant differences from MC.
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Back-up slidesBack-up slides
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Data driven background estimationData driven background estimation
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Crosscheck on a larger statistics!
In order to obtain more background photons under in a signal sample less stringent kinematic conditions where taken:
40 < m() < 88 GeV75 < m() < 105 GeV
Excellent agreement!
ET()>5 GeV
N (tracks in cone20)
Number of tracks in cone 0.2 around photon vector in ID.
Again the black line shows the background estimate using extrapolation method described above.
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MC: Study of the pure background sample.MC: Study of the pure background sample.
Spectrum of background photons from the signal sample after 3 body
mass CUT applied
ET [GeV]
Spectrum of background photons from the background sample
Applying 3 body mass cutwe deform a bit the photon
spectrum.
Does it affect the background estimation?
Background photon spectrums
Cut Et (in cone 0.2)<3 GeV
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MC study: Pt cone and N tracks (cone 0.2)MC study: Pt cone and N tracks (cone 0.2)
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Background sample extraction will provide us exact distribution of ID track information for background photon candidates
ET()>10 GeV
PT(cone20) [GeV] N (tracks in cone20)
Sum of all momentums in cone 0.2 around photon vector in ID
Number of tracks in cone 0.2 around photon vector in ID
Background sample kinematic cuts are: for muon channel 89 < m() < 93 GeVCut Et (in cone 0.2)<3 GeV
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MC study: Pt cone and N tracks (cone 0.2)MC study: Pt cone and N tracks (cone 0.2)Background sample extraction will provide us exact distribution
of ID track information for background photon candidates
We have almost the same picture for all energies.
But for high energies, we have a bit large fraction of
the signal.
ET()>15 GeV
Sum of all momentums in cone 0.2 around photon vector in ID
Number of tracks in cone 0.2 around photon vector in ID
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PT(cone20) [GeV] N (tracks in cone20)
Background sample kinematic cuts are: for muon channel 89 < m() < 93 GeVCut Et (in cone 0.2)<3 GeV
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MC: Study of the pure background sample.MC: Study of the pure background sample.
Distribution of number of tracks in the cone 0.2 in Inner Detector around background photon (black line histogram) in the signal sample the three-body invariant mass cut applied, and for photon background sample (blue filled histogram)
ET()>10 GeV
Comparison of the track number distribution for different background photon samples
Cut Et (in cone 0.2)<3 GeV
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MC: Study of the pure background sample.MC: Study of the pure background sample.
Distribution of number of tracks in the cone 0.2 in Inner Detector around background photon (black line histogram) in the signal sample the three-body invariant mass cut applied, and for photon background sample (blue filled histogram)
Comparison of the track number distribution for different background photon samples
Cut Et (in cone 0.2)<3 GeVThe shapes of the
distribution are in a less good agreement,
than for small energies. However
due to big statistical errors, we can use this
shape from photon background sample
for a data driven background estimate
normalizing on number of events for
N>1. There is no signal in this area
ET()>15 GeV
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Data driven background estimationData driven background estimation
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Signal to background ratio is much higher for larger photon energies
Always condition Et in cone20 < 3 GeV is used
Relaxed conditions:40<m()<88 GeV75<m()<105 GeV(to gain more bkg statistics)
N (tracks in cone20)
We use these bins for extrapolation
N (tracks in cone20)
Number of tracks in cone 0.2 around photon vector in ID.
Again the black line shows the background estimate using extrapolation method described above.
We have a problem: signal here!
ET>10 GeV
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TightTight cut effect on background samplecut effect on background sampleEfficiency of robust tight cut on background vs sum of Et in cone 0.2 in calorimeter around photon (left) and Et photon spectrum (right), Et(in cone20)<3 GeV (one photon candidate in event)
List all the conditions: all kinematic cuts, Et in cone20 < 3 GeV , N tracks = 0
ET(cone20) [GeV]
Distribution of Et photon spectrum for background sample before (left) and after (right) robust tight photon cut.
ET [GeV]
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TightTight cut effect on background samplecut effect on background sample
N=Ns+Nb=17228after tight cut we haveNt=effs*Ns+effb*Nb=8414We also know purity=Ns/N (slide 9)
We can extract pure effs (we know effb from slide 25):Effs=(Nt-effb*Nb)/Ns=Nt/N*purity-effb*(1/purity-1)=0.38 (for 5 GeV)
List all the conditions: all kinematic cuts, Et in cone20 < 3 GeV , N tracks = 0
№ 2828.07.2011Physics in ATLAS