1
Nadia Davidson, Naoko Kanaya
E/p Analysis Update
Jet EtMiss Meeting29th September 2009
2
Review
E/p
Hadron track momentum
will be very accurate
p
Energy deposited
by hadrons in the
calorimeter will not
be well known in
early data.
E
∆R
The ratio E/p allows the energy reconstruction of hadrons in the calorimeters to be validated.
Tracks matched to clusters can be used to
study properties of the clusters (or sum of
clusters) close to the track. For example:
- Hadronic calibration
- Shower profiles
- Noise suppression
- pi0's associated with tracks
This can help to improve jet and tau jet
reconstruction. eg. Choice of hadronic
showering model, modifying the material
description of ATLAS
Trigger for E/p study (1)Good track selection
• Track isolation : No tracks around good track within dR=0.4• Calorimeter isolation : ∑EHCAL
dR=0.4-1.0 < 1%PTRK
Isolated track selection
• pT>500MeV• NSI ≥7• |d0|<2mm, |z0sin|<10(100) mm for physics process (singlepart)• chi2/ndof < 2.5• NTRT≥ 1 if ||<2.0
Trigger Menu• 1E31 Menu • Event rate is calculated inclusively (event weight=∑PS unless >1)• Use mibias, single,double diffractive, J0-J5, W
https://twiki.cern.ch/twiki/bin/view/Atlas/L31TriggerMenuReference (although given menu is slightly different)
Calorimeter response • Cells associated to topo clusters around track within dR<0.4• Energy summed up at EM scale
Naoko Kanaya
Trigger for E/p study (2)
menu e10_mediumMbSp(+Trk)
object rate (Hz) 7.4 (21)4.2 (8.5)
Dominant trigger menu(1E31)
Trigger bias…?We don’t have L1 track trigger.Do not use a candidate track if it matches to only one active e// trigger object in the event, dR<0.2 (except jet)…similarly to tag&prove method
Reject
Active triggerobject
Rate of isolated tracks with pT>500MeV
menu e10_medium2e5_medium
2mu4
event rate (Hz) 0.90.240.12
Rate of isolated tracks with pT>5GeV* Not unique rate, event rate is given in ()
Lepton trigger threshold
… Inclusive event rate is 150Hz in my analysis
w/o HCAL Isolation
43 HzpT>500MeV
Trigger for E/p study (3)
Rate (Hz) 1.10.70.1
Day1/=0.11.9k11020
PT distribution (remove active trigger objects)
* Assume ~flat eta distribution
- minimum bias DPD can be useful for low pT scale 10Hz x 1/50 x (1/5+4/5*0.7) -> 250 tracks/0.1/day (minbias, pT>500MeV)
- No suitable DPD for high pT isolated tracks.
Possible to run unseeded IDSCAN/isolation on Jet stream at EF?
If not…
pT>5GeV 2.9Hz1.3Hz
pT (GeV)4-77-1111-20
Situation will be worse in the presence of the pileup. Also we need quite a lot of statistics for better precision.(Quantitative study is on going…)
Matching to soletrigger objects
High pT single track?Is it possible to analyze all ESD? If so, we have enough statistics with pT<10GeV
E/p measurement in data (1)In TestBeam, study is done in only a limited region and also for pions while we need to verify E/p response in the whole region (||<2.5) and also our analysis is flavor blind (/K/P~60/30/10). Geant4 may give different performance for different primary and target (calorimeter and dead material).
<>=0.58<>=0.57<>=0.54
pT=0.5-7GeV||<2
sim14.2.10.1/reco14.2.25.8
This effect is negligible (may not be seen) at the beginning of the experiment.But the fraction may change e.g. due selection criteria, It will be checked.
E/p measurement in data (2)Not only E/p but other calorimeter response variable, such as shower shapesis also useful to validate geant4 physics list.
To avoid distortion from background:
Compute variables by subtracting/unfolding background Compute variables using cells within a limited region (one closest cluster) Use ECAL as a filter and compute variables using HCAL.
CENTER_LAMBDAin the closest cluster
MinBiasSingle pi
MinBiasSingle pi
EHAD/PTKR
(dR<0.4)
Normalized
The size of the closest cluster is not sufficiently small distorted by contamination
Small deviation is seen.Need to check…
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Energy in the Hadronic CalorimeterHad. Cal.
EM Cal.
Hadron shower
Showers from
other particles
Track momentum Track η
Red - Single PionsRed - Single Pions
Black - Min. BiasBlack - Min. Bias<E
had/p><E
had/p>
<Ehad
/p> is consistent
with the reference single pion
sample to within <0.01
(or 10%)
Can be measured in early data?
ResidualsResiduals
Non-pileup Sample
Cuts: same as slide 3
+ B layer cut
+ ptrk
/Σptrk
>0.1
- cut on E in HAD cal. 1.0-0.4
was not used
Non-pileup Sample
Cuts: same as slide 3
+ B layer cut
+ ptrk
/Σptrk
>0.1
- cut on E in HAD cal. 1.0-0.4
was not used
Nadia Davidson
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Energy Close to the Track
EM Cal.
Hadron shower
Showers from
other particles
Had. Cal.
The energy in a
narrow cone of ΔR < 0.05
Results are within about
0.02 (or 5%) of the
single pion reference
sample.
Had. Cal. Hadron shower
Track momentum Track η
Red - Single PionsRed - Single Pions
Black - Min. BiasBlack - Min. Bias<E
0.05/p><E
0.05/p>
Can be measured in early data?
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Total EnergyHad. Cal.
EM Cal.
Hadron shower
Showers from
other particles
Red - Single PionsRed - Single Pions
Black - Min. BiasBlack - Min. Bias
Track momentum Track η E/p distribution
Approx 15% extra
energy from
contaminating
Source. Background
Is approx. flat in eta.
Large tail
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Data-driven Background Estimation Hadrons are classified as either early showering or late showering (mips) based on the
energy deposition in the hadronic calorimeter compared to the electromagnetic calorimeter (in the green core region).
The contaminating energy is measured in the electromagnetic calorimeter (blue) region for
late showering pions.
The contaminating energy distribution is unfolded from the distribution for all pions (late and
early showering)
Had Cal.
EM Cal.
core coneΔR
mip
Late showering hadronsThere is little overlap between hadron
Showers and showers of other particles
Hadron
shower
Showers
from other
particles
Early Showering hadronsThere is overlap between hadron
showers and showers of other particles
Hadron
shower
Showers from
other particles
Had Cal.
EM Cal.
Region where
background
was measured
See CSC Book
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E/p with Background Subtracted
There is systematic error in the way the background is estimated:
- Choose ΔRMIP
too small and there is pion leakage out of the cone
- Choose ΔRMIP
too large and we may miss some of the correlated background
Track momentum Track η
Single PionsSingle Pions
MinBias (MinBias (ΔRΔRmipmip=0.04)=0.04)
MinBias (MinBias (ΔRΔRmipmip=0.08)=0.08)
MinBias (MinBias (ΔRΔRmipmip=0.10)=0.10)
MinBias (MinBias (ΔRΔRmipmip=0.15)=0.15)
Single PionsSingle Pions
MinBias (MinBias (ΔRΔRmipmip=0.04)=0.04)
MinBias (MinBias (ΔRΔRmipmip=0.08)=0.08)
MinBias (MinBias (ΔRΔRmipmip=0.10)=0.10)
MinBias (MinBias (ΔRΔRmipmip=0.15)=0.15)
<E/p><E/p>
The background estimate is reasonably stable with respect to the choice of narrow cone
… some work is still needed to quantify the uncertainty from this.
… MIP selection should also be varied.
MIPs selected with:
400 MeV < EEM
< 700 MeV
0.3 < EHAD
/ptrk
< 0.9
MIPs selected with:
400 MeV < EEM
< 700 MeV
0.3 < EHAD
/ptrk
< 0.9
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Distribution Recovery using Fitting
Use a predicted shape to perform a fit for the convolved E/p distribution
• Easier to estimate the statistical error
• Works better with lower statistics
• No regularisation of the noise required (so less systemic error if the
shape is well know).
E/p measured
= E/p background
* E/p isolated
Get from data
Fit a convolution:
fbackground
* fisolated
Get from data
Fit a convolution:
fbackground
* fisolated
Get from data.
Fit: fbackground
Get from data.
Fit: fbackground
Result: fisolated
Result: fisolated
Minuit was used to perform a chi2 minimisation which allows a
simultaneous fit of E/pmeasured
and E/pbackground
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Fit for Hadrons in Minimum Bias
expexp exp
free
free
exp
bifurcated
gaussian
exp
Note: Error band are approximate.
chi2/ndf=200/132chi2/ndf=200/132
pink - fit
black - data points
Black histogram – result
from iterative unfolding
(using TSpectrum::Deconvolution)
Predicted shape
6 parameters
P = 1-2 GeV, |η|<0.8
7 parameters
ResultMeasured
Background
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Fit for Single Pion Monte-Carlo
chi2/ndf=150/94chi2/ndf=150/94
ResultMeasured
Background
We need to deconvolute the noise for a fair
comparison with minimum bias hadrons (this should
not effect the mean).
Comparison of the min. bias and single pion fits will be the next step
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Conclusion/Plans There is still a lot to do:
• Study systematics of the unfolding method.
• See if fitting is a good alternative to unfolding.
• Study the possibility of a special trigger (unseeded track trigger at
EF) if ESD/DPD is not sufficient.
• See how well we can recover quantities from all cells (rather than
Topo-Clusters cells).
• Repeat with PHOJET minimum bias Monte-Carlo.
• Repeat with another hadronic showering model (eg. FTFP_BERT)
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Back-up Slides
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Selection of “good” tracks
Red – bad tracks (no matched truth particle, or a truth which comes from an ID interaction)Black – good tracks (all others)
Minimum
bias
19
Result of track selection
Tracks from
minimum bias
monte-carlo
Tracks (>10 GeV)
from J0 monte-carlo
(J0 = dijets of
8-17 GeV)
Bad and “fake”
tracks are removed
before after
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Mean, sigma, prob. of no cluster
<E/p>isolated
= <E/p>measured
- <E/p>background
<E/p>isolated
= <E/p>measured
- <E/p>background
σ2isolated
= σ2measured
- σ2background
σ2isolated
= σ2measured
- σ2background
P(E/p=0)isolated
=P(0)measured
/P(0)background
P(E/p=0)isolated
=P(0)measured
/P(0)background
Not okayNot okayOkayOkay Maybe okayMaybe okay
Red-
Single Pions
Red-
Single Pions
Black -
Min. Bias
Black -
Min. Bias
Results obtained for MIP selection of EHAD
/Ptrk
> 0.3 and ΔRmip
=0.1
Residual
Value
Non pile-up
events
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Systematics - Particle Species
Pile-up eventsConsistent within statistical precision