Stan Bentvelsen Commissioning

P 1

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

Stan Bentvelsen Commissioning

P 2

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

Stan Bentvelsen Commissioning

P 3

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

Stan Bentvelsen Commissioning

P 4

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

Stan Bentvelsen Commissioning

P 5

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

Stan Bentvelsen Commissioning

P 6

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%

Stan Bentvelsen Commissioning

P 7

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

Stan Bentvelsen Commissioning

P 8

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

Stan Bentvelsen Commissioning

P 9

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

Stan Bentvelsen Commissioning

P 10

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)

Stan Bentvelsen Commissioning

P 11

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

Stan Bentvelsen Commissioning

P 12

“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

Stan Bentvelsen Commissioning

P 13

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

Stan Bentvelsen Commissioning

P 14

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