commissioning the detectors
DESCRIPTION
Determination cross section and M Top in initial phase of data taking Use ‘Golden plated’ lepton+jet channel Selection: Isolated lepton with P T >20 GeV Exactly 4 jets ( R=0.4) with P T >40 GeV Reconstruction: Select 3 jets with maximal resulting P T. Commissioning the detectors. - PowerPoint PPT PresentationTRANSCRIPT
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Stan Bentvelsen Commissioning
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Commissioning the detectors
Determination cross section and MTop in initial phase of data taking Use ‘Golden plated’ lepton+jet channel
Selection: Isolated lepton with PT>20 GeV
Exactly 4 jets (R=0.4) with PT>40 GeV
Reconstruction: Select 3 jets with maximal resulting PT
No background
included
Calibrating detector in comissioning phase
Assume pessimistic scenario:
-) No b-tagging
-) No jet calibration
-) But: Good lepton identification
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Extraction of top signal
Fit to signal and background Gaussian signal 4th order polynomal background In this fit the width of top is fixed at 12 GeV
Extract
cross section
and Mtop?
150 pb-1
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Fit to W mass
Fit signal and background also possible for W-mass
Not easy to converge Fix W width to 6 GeV
150 pb-1 mean σ(stat)
in peak 3.0% 5%
Mtop 167.0 0.8
Mw 77.8 0.7
These numbers for statistical uncertainties are consistent to the earlier study
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Energy scale / MC dependence
Variation of the jet energy scale to infer systematics Bjet scale: 0.92 – 0.96 – 1.00 – 1.04 – 1.08 Light scale: 0.94 – 0.98 – 1.00 – 1.02 – 1.04
1) Redo analysis with jet energyscaled
2) Redo all with MC@NLO, Herwigand Pythia
3) Redo analysis with doubled W+4jet background (stat indep)
Effect on selection, via selection cuts
Effect on W and T mass Quote standard deviation
as systematic uncertainty
Mtop stat MW stat
mcatnlo 1 158,86 0,73 74,36 0,74
mcatnlo 2 163,05 0,76 76,21 0,73
mcatnlo 3 167,03 0,76 77,75 0,66
mcatnlo 4 171,40 0,74 79,23 0,70
mcatnlo 5 175,33 0,77 82,28 0,97
herwig 1 158,66 0,81 74,67 0,69
herwig 2 162,72 0,87 76,64 0,72
herwig 3 166,85 0,85 77,86 0,65
herwig 4 170,43 0,86 79,43 0,66
herwig 5 174,45 0,81 81,90 0,69
pythia 1 162,65 0,81 75,85 0,69
pythia 2 167,62 0,81 77,25 0,72
pythia 3 171,42 0,79 79,17 0,63
pythia 4 175,23 0,92 81,33 0,64
pythia 5 178,78 0,88 83,34 0,67
Fully consistent to earlier studies as shown by Marina
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Correction
Top mass
155
160
165
170
175
180
0 5 10 15 20 25
Scale variations
To
p m
ass
Raw Top Mass
Scaled Top Mass
Determine Mtop and σ(top) ‘Raw’, i.e. no correction for jet
scale ‘Corrected’, i.e. apply
percentage difference of W-peak to the reconstructed top
Not granted Mjj gives correct MW, i.e. for hard FSR events…
Dependence on top mass reduced by scaling with W:
Rms of top masses: Raw: 6.2 GeV Scaled: 1.2 GeV
Note: Here simple rescaling of Top mass – not of the jet-energies themselves!
Large dependence σ(top) on jet energy scale
Via event selection.
Scale variations:
5 scales (see previous slide)
for each of the three generators (MC@NLO Pythia Herwig)
And for MC@NLO with 2 times background added
Cross section
0
200
400
600
800
1000
1200
0 5 10 15 20 25
Cross section
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Some results… (still no b-tag)
Using 150 pb-1 of data:
Statistic uncertainty already smaller than these systematic variations
Note these numbers are very preliminary –
No luminosity uncertainty included here!
How to judge these values? Systematics overestimated:
since all generators are used, with all energy scales; double counting
W+4jets rate can be measured from data
Systematics underestimated: No real FSR variation No other backgrounds
(e.g. WW, QCD) Trigger Non-uniformities
Need further detailed studies!
Please don’t thrust any of this
without Full simulation
mean Stat std percent
Mtop raw 168,1 0.8 6,2 3,7%
correcte
d 171,9 0.8 1,2 0,7%
σ(top) raw 817,2 5% 94,8 11,6%
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Is this an idea: ‘Purify’ W-sample
Select events for which reconstructed top mass: 150<Mtop<200 GeV
Look at W-mass:
Better S/B ratio Need pursued
further
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Reconstruct top mass
Sharp top mass peaks with little background Only use events for which |Mjj-80.4| < 20 GeV
Standard kinematic top reconstruction for 1 and 2 b-tags Background from W+4jets removed by b-tag requirement These results are very sensitive to b mis-tag rate
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100 000 tt events (~ 1.5 days at LHC at low L)
o Simulated using PYTHIA + ATLSIM
/ G3 (initial detector, < 3.2)o Reconstructed using ATHENA 7.0.0
Preselection of events:
o At least one recontructed e or
with PT > 20 GeV and < 2.5
o ETmiss > 20 GeV
o At least 4 jets with PT > 20 GeV and < 2.5
EM clusters
Jets
Analysis
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Results
If the 33 weak HV sectors die (very pessimistic), the effects on the top mass measurement, after a crude recalibration, are:
o Loss of signal: < 8 %
o Increase in background: not studied
o Displacement of the peak of the mass distribution: -0.2 GeV
The effect on the mass distribution should be known (much) better than the effects from the other systematic errors
Mtop(without ) – mtop(with dead regions)
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B-tagging efficiency
tag = probability to tag at least one jet in a top event tag b-tag non-b – ( b-tag
. non-b)
non-b c-tag nonhf
b-tag is the sum of these possibilities: Probability to tag 1 b-jet in the event, when 1 is found in the
detector Probability to tag 1 b-jet when 1 is found in the detector Probability to tag 2 b-jets when 2 are found in the detector
First simple evaluation (counting method): Select a very pure ttbar sample with tight kinematical cuts Count the number of events with at least 1 tagged b-jet Divide this number by the number of pre-tag candidate events
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“Inputs” to the top group
B-tagging algorithm Estimate of the non-perfect ID alignment
E.g. for the pixels (from S. Rozanov): - after 2 months: 100 m - after 4 months: 20 m (0.6 effect on b-tag efficiency)- after 6 months: 10 m - after 8 months: 5 m (design performance!!!)- asymptotic ?\
- Staging pixel detector- 2 layers -> 0.6 effect on b-tag efficiency
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B-tagging efficiency
’s are measured in MC (where flavor content of jets in top events can be precisely determined). The tagging algorithm however will perform differently on data and on MC. This difference can be accounted for by introducing a scale factor: SF
F1b = fraction of events with 1 taggable jets F2b = fraction of events with 2 taggable jets
)1(2 222
21 btagbtagbbtagbbtagbeventtagb SFFSFFSFF
Probability to tag oneB-jet when one is found
Probability to tag twoB-jets when two are found
Probability to tag oneB-jet when two are found
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Cross Section
The ttbar cross section formula may be written as:
We define the ttbar event detection efficiency as:
kin = fraction of ttbar events which pass the requirements
trig = trigger efficiency for identifying high PT leptons
tag event = efficiency to tag at least one tight jet in a ttbar event
Need to insert trigger efficiencies and kinematic acceptances.
Ldt
NN
tt
bgdobstt
eventtagtrigkintt
vetoIDleptonZottkin A