Jet etmiss meeting 29 th september 2009
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Jet EtMiss Meeting 29 th September 2009. Nadia Davidson, Naoko Kanaya. E/p Analysis Update. Review. The ratio E/p allows the energy reconstruction of hadrons in the calorimeters to be validated.

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Jet etmiss meeting 29 th september 2009
Jet EtMiss Meeting29th September 2009

  • Nadia Davidson, Naoko Kanaya

E/p Analysis Update


Review
Review

  • 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

E/p

∆R

Energy deposited

by hadrons in the

calorimeter will not

be well known in

early data.

E

Hadron track momentum

will be very accurate

p


Jet etmiss meeting 29 th september 2009

Naoko Kanaya

Trigger for E/p study (1)

Good 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

Isolated track selection

  • Track isolation : No tracks around good track within dR=0.4

  • Calorimeter isolation : ∑EHCALdR=0.4-1.0 < 1%PTRK

Calorimeter response

  • Cells associated to topo clusters around track within dR<0.4

  • Energy summed up at EM scale

Trigger Menu

  • 1E31 Menu

  • Event rate is calculated inclusively (event weight=∑PS unless >1)

  • Use mibias, single,double diffractive, J0-J5, W

Reference (although given menu is slightly different)

https://twiki.cern.ch/twiki/bin/view/Atlas/L31TriggerMenu


Jet etmiss meeting 29 th september 2009

Trigger for E/p study (2)

Dominant trigger menu(1E31)

… Inclusive event rate is 150Hz in my analysis

Rate of isolated tracks with pT>500MeV

w/o HCAL

Isolation

menu

e10_medium

MbSp(+Trk)

object rate (Hz)

7.4 (21)

4.2 (8.5)

Lepton trigger

threshold

* Not unique rate, event rate is given in ()

Rate of isolated tracks with pT>5GeV

43 Hz

pT>500MeV

menu

e10_medium

2e5_medium

2mu4

event rate (Hz)

0.9

0.24

0.12

Active trigger

object

Trigger bias…?

Reject

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


Jet etmiss meeting 29 th september 2009

Trigger for E/p study (3)

PT distribution (remove active trigger objects)

pT (GeV)

4-7

7-11

11-20

Rate (Hz)

1.1

0.7

0.1

Day1/=0.1

1.9k

110

20

Matching to sole

trigger objects

* Assume ~flat eta distribution

pT>5GeV

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…)

2.9Hz1.3Hz

High pT single track?

Is it possible to analyze all ESD?

 If so, we have enough statistics with pT<10GeV

 If not…

- No suitable DPD for high pT isolated tracks.

  • 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)

Possible to run unseeded IDSCAN/isolation on Jet stream at EF?


Jet etmiss meeting 29 th september 2009

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).

sim14.2.10.1/reco14.2.25.8

pT=0.5-7GeV

||<2

<>=0.58

<>=0.57

<>=0.54

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.


Jet etmiss meeting 29 th september 2009

E/p measurement in data (2)

Not only E/p but other calorimeter response variable, such as shower shapes

is 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_LAMBDA

in the closest cluster

EHAD/PTKR

(dR<0.4)

MinBias

Single pi

Normalized

MinBias

Single pi

The size of the closest cluster is not sufficiently small

 distorted by contamination

Small deviation is seen.

Need to check…


Energy in the hadronic calorimeter

Nadia Davidson

Energy in the Hadronic Calorimeter

Had. Cal.

Red - Single Pions

Hadron shower

<Ehad/p>

Black - Min. Bias

EM

Cal.

Showers from

other particles

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

Track momentum

Track η

<Ehad/p> is consistent

with the reference single pion

sample to within <0.01

(or 10%)

Residuals

Can be measured in early data?


Energy close to the track
Energy Close to the Track

Had. Cal.

Had. Cal.

Red - Single Pions

Hadron shower

Hadron shower

<E0.05/p>

Black - Min. Bias

EM

Cal.

Showers from

other particles

The energy in a

narrow cone of ΔR < 0.05

Results are within about

0.02 (or 5%) of the

single pion reference

sample.

Track momentum

Track η

Can be measured in early data?


Total energy
Total Energy

Had. Cal.

Hadron shower

Red - Single Pions

Large tail

Black - Min. Bias

EM

Cal.

Showers from

other particles

Track momentum

Track η

E/p distribution

Approx 15% extra

energy from

contaminating

Source. Background

Is approx. flat in eta.


Data driven background estimation
Data-driven Background Estimation

Had Cal.

EM

Cal.

  • 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)

Late showering hadrons

There is little overlap between hadron

Showers and showers of other particles

Early Showering hadrons

There is overlap between hadron

showers and showers of other particles

Hadron

shower

Hadron

shower

Had Cal.

core cone

ΔRmip

Showers

from other

particles

Region where

background

was measured

EM

Cal.

Showers from

other particles

See CSC Book


E p with background subtracted
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

Single Pions

MinBias (ΔRmip=0.04)

MinBias (ΔRmip=0.08)

MinBias (ΔRmip=0.10)

MinBias (ΔRmip=0.15)

<E/p>

  • MIPs selected with:

  • 400 MeV < EEM < 700 MeV

  • 0.3 < EHAD/ptrk < 0.9

Track momentum

Track η

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.


Distribution recovery using fitting
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: fbackground

Get from data

Fit a convolution:

fbackground * fisolated

Result: fisolated

Minuit was used to perform a chi2 minimisation which allows a

simultaneous fit of E/pmeasured and E/pbackground


Fit for hadrons in minimum bias
Fit for Hadrons in Minimum Bias

chi2/ndf=200/132

Measured

Result

pink - fit

Predicted shape

black - data points

7 parameters

free

bifurcated

gaussian

Background

free

6 parameters

exp

exp

exp

exp

exp

Black histogram – result

from iterative unfolding

(using TSpectrum::Deconvolution)

P = 1-2 GeV, |η|<0.8

Note: Error band are approximate.


Fit for single pion monte carlo
Fit for Single Pion Monte-Carlo

chi2/ndf=150/94

Measured

Result

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


Conclusion plans
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)



Selection of good tracks
Selection of “good” tracks

Minimum

bias

Red – bad tracks (no matched truth particle, or a truth which comes from an ID interaction)

Black – good tracks (all others)


Result of track selection
Result of track selection

after

Tracks from

minimum bias

monte-carlo

before

Bad and “fake”

tracks are removed

Tracks (>10 GeV)

from J0 monte-carlo

(J0 = dijets of

8-17 GeV)


Mean sigma prob of no cluster
Mean, sigma, prob. of no cluster

<E/p>isolated = <E/p>measured - <E/p>background

P(E/p=0)isolated=P(0)measured/P(0)background

σ2isolated = σ2measured - σ2background

Red-

Single Pions

Value

Black -

Min. Bias

Okay

Not okay

Maybe okay

Non pile-up

events

Residual

Results obtained for MIP selection of EHAD/Ptrk > 0.3 and ΔRmip=0.1


Systematics particle species
Systematics - Particle Species

Pile-up events

Consistent within statistical precision