Transcript Jet Energy and Resolution at the Tevatron Andrew Mehta YETI meeting, 7/1/2008 Outline  Introduction  CDF +D0 experiments and calorimeters  Jets  CDF Jet Energy Scale method  D0 Jet Energy.

Jet Energy and Resolution at
the Tevatron
Andrew Mehta
YETI meeting, 7/1/2008
Outline

Introduction

CDF +D0 experiments and calorimeters

Jets

CDF Jet Energy Scale method

D0 Jet Energy Scale method

Cross check of jet energy scale
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Motivation (1)

Knowledge of Jet Energy Scale (JES)
is fundamental for hadron colliders

All physics processes involve jets that span
a wide ET range [0,√s/2]

Important for SM measurements …
Inclusive jet cross section
Jet Energy Scale uncertainties
are dominant for high PT jets
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Motivation (2)

… also most of Non-Standard Model
signatures (i.e. squark-gluino production)
involve jets and Missing Transverse
Energy (MET)
 MET must be corrected for jet energy
measurements.
Missing ET
Multiple
jets
Missing ET
Correction ~ 12%
at low MET
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Tevatron RunII
Highest-energy accelerator currently operational
pp collisions at √s=2 TeV
Peak luminosity
 above 2.0 *1032 cm-2 s-1
Integrated luminosity/week
 about 25 pb-1
~3.0 fb-1 on tape
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Jet reconstruction
A jet is a composite object:
•complex underlying physics
•depends on jet definitions
Use different kind of Jet algorithms:
- Cone algorithms (JETCLU and MIDPOINT)
- KT algorithm
Instrumental effects:
- response to hadrons
- poorly instrumented regions
- Multiple p-pbar interactions
Time
Corrections on Jet Energy Scale (JES) for
different effects:
Physics effects:
- Underlying event
- Hadronization
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CDF Calorimeter
Central and Wall ( |h|<1.2 ):
•Granularity: Df × Dh = 15° × 0.1 (~ 800 towers)
•Non compensating
 non-linear response to hadrons
•Rather thin: 4 interaction lengths
•Small amount of noise
•Resolutions:
- EM energies (g,e): s/ET = 13.5%/√ET+1.5%
- HAD energies(p±): s/ET = 50%/√ET+3%
Plug (1.2<|h|<3.6):
•Similar technology to the central
•Resolutions:
- EM energies (g,e): s/E = 16%/√E+1%
- HAD energies (p±): s/E = 80%/√E+5%
•Thicker than central: 7 interaction lengths
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D0 Calorimeter
•LAr sampling
•U absorber: Compensating
 linear response to hadrons
•7 interaction lengths
• Same structure for barrel and plug
•Resolutions:
- EM energies (g,e): s/ET = 15%/√ET+0.3%
- HAD energies(p±): s/ET = 45%/√ET+5%
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Calorimeter calibration: EM energy

Check calorimeter response:


Use test beam (from 1980s!) and single
particles measured in-situ to
understand absolute response
Check time dependence
For EM energy response use:
 MIP peak when possible
(at about 300 MeV)
 Ze+e- mass peak stability
- Set absolute EM scale
in central and plug
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Calorimeter calibration: Hadronic Energy
For hadron energy response use
Minimum Ionizing Particles (MIP):
- J/ and W muons
- Peak HAD calorimeter: ~ 2 GeV
Also Minimum bias events:
- E.g. N towers (ET>500 MeV)
Syst. Uncertainty related to
Calorimeter Calibration ~ 0.5%
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CDF Jet Energy Scale Method
Different correction factors:

(fabs) Absolute Corrections
 Calorimeter non-linear and non-compensating

(frel) Relative Corrections
 Make response uniform in h : all corrections are then referred to
the central region

(MPI) Multiple Particle Interactions
 Energy from different ppbar interaction
PT jetparticle(R) = [ PT jetraw(R)  frel (R) – MPI(R)]  fabs(R)
Additional corrections to get to parton energy:
 (UE) Underlying Event
Energy associated with spectator partons in a hard collision
 Hadron-to-Parton correction (historically defined as Out-Of-Cone)
PT parton(R) = PT jet particle(R) - UE(R) + OOC
Systematic uncertainties are associated with each step
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CDF Absolute Corrections


Use MC simulation to determine Jet Corrections
MC is adjusted by comparison with data to:
 simulate accurately detector response to
single particle (E/p).
 describe jet fragmentation
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CDF single particle response simulation
Jet composition:
• ~ 70 % charged particles
- 10% protons
- 90% pions
• 30 % neutral pions ( gg)
- EM response
Remaining
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hadrons
difference data/simulation  taken as syst. uncertainty
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CDF fragmentation
MC simulation needs to reproduce well data:
• Due to non-linearity of the calorimeter,
non trivial correlation N particles and PT track spectra:
- one 10 GeV pion: ~ 8 GeV
- ten 1 GeV pions: ~ GeV
• Very important a good understand of track efficiency
• Measurement of jet shape is fundamental
Integrated jet shape
1
pT 0, r )
r ) 

N jets jets pT 0, R )
Data/MC different = Systematic uncertainty ~ 1%
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CDF Absolute Correction
Absolute correction factor


Almost independent on jet cone size.
Depends on transverse momentum: calorimeter response is ~
70% for 25 GeV/c jets, ~ 90% for 400 GeV/c jets.
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CDF Relative Corrections
Use dijet events.
Jet corrections relative to the
central calorimeter:
 Central (0.2<|h|<0.6 jets)
~1 by definition (reference)
 Difference Data/MC mainly in the
forward region
 Depends on ET jets considered
cracks
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CDF Multiple Interactions


Overlapping interactions
can overlap the jet
Number of extra interactions
depends on luminosity
 Energy offset depends on number of interactions
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CDF Multiple Interaction corrections
• Linear correlation between number of interactions and number of vertices
• Define random cones in the central region (0.2<|h|<0.6) and determine average
transverse energy associated to a cone
• Cone-based method: should improve to make it more general (KT?)
For cone R = 0.7, <ET> = 1.06 GeV
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CDF Model-dependent corrections



Underlying event (UE) and Hadron-to-Parton (Out-ofcone, OOC) energy corrections used only if need
parton energy
Modelling is required, difference MCs as systematic
uncertainties.
Parton transverse momentum:
PT parton(R) = PT jet particle(R) - UE(R) + OOC
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CDF Underlying event
Particle jet could have
contributions note related
to hard interaction:





Beam-beam renmants
Initial state radiation
MC tuned on Data (as Pythia Tune A)
Use di-jet events
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CDF Out-of-Cone Correction

OOC energy: energy
escaping the cone radius


Obtained from Pythia di-jet
samples:



Gluon radiation (FSR)
Ratio PTparton / PT jet particle
Similar performance Pythia
and Herwig
Systematic uncertainties
from photon+jet events:


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Assume PTg = PT jet corr.
Difference Data/MC of
energy inside annuli around
jet axis taken as systematic
uncertainty
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D0 Jet Energy Scale Method
Different correction factors:

(fabs) Absolute Corrections
 Calorimeter non-linear and non-compensating

(frel) Relative Corrections
 Make response uniform in h : all corrections are then referred to
the central region

(O) Offset correction
 For MPI, underlying event and detector noise

(S) Showering correction
 For detector effect of energy leaking inside or outside of jet
cone
ET jetparticle = [ ET jetraw -O] / (frel fabsl S)
Note D0 correct to a particle level with corrections for underlying event, but not
for out of cone corrections (different from CDF).
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D0 Offset Energy


Corrects for all energy not associated to the hard
scatter: MPI, underlying event and electronic noise
Worked out from minimum bias events
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D0 Relative Corrections
Use dijet and photon-jet events.
Jet corrections relative to the central calorimeter |h|<0.6 :
 Depends on ET jets considered due to crack
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D0 Absolute Correction
Absolute correction factor
Performed with photon-jet events
 Similar corrections for different η
→shows relative corrections ok

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D0 Showering Correction



Use MC to estimate energy smeared in or out due to detector
effects (this is absorbed in the absolute corrections at CDF)
Checks with data to evaluate the systematic error
Does not account for true energy from the parton distributed
outside the jet radius (OOC corrections at CDF)
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JES Systematic uncertainties
Total systematic uncertainties for JES
 between 2 and 3% as a function of corrected transverse jet momentum
CDF
Similar between CDF and D0 apart from out of cone correction, which
is very large at low Pt for CDF
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CDF g Z) + jet pT balance
Used to test procedure – not used in calibration
• ET leading jet > 25 GeV
• ET (second jet) < 3 GeV
• Df (Jet-g) > 3
• Data
Pythia
Herwig
Sensitive to radiation effects
when allow second jet:
Herwig farther away from jet cone
pT balance:
Agreement Data/MC within 3%
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CDF check of scale with
 Look at dijet mass resonances to check b jet energy scale
 Trigger on two displaced tracks+ two 10 GeV jets
 DisplacedVertex tag, SecondryVertex Mass to select b-jets, kinematic cuts to improve
S/B
 Fit signal and background (direct QCD production) templates, for varying JES
DiJet Invariant mass GeV
Jet energy scale:
0.974 ± 0.011 ( stat.) ± 0.017 (sys.)
(agreement with 1 sigma of nominal
scale factor)
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CDF Z-jet pT balance
These events allow us to
reach lower PT than
photon+jet and also cross
check photon+jets results.
Selection

• two e(m) with ET>18 GeV (pT>20 GeV)
• 76 < M ee(mm) < 106 GeV
• ET leading jet > 25 GeV
• ET (second jet) < 3 GeV
• Df (Jet-Z) > 3
Similar Herwig behaviour
for Z+jet w.r.t. g+jet but less visible
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CDF check of calibration from W
Very difficult to see inclusive decays of W and Z in jets
Best possibilities:
- W from top decays
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Summary and Conclusions





Hadron colliders are a very challenging
environment to measure the jet energy scale
Lack of simple clean processes, gluon radiation,
multiple interactions, underlying event etc.
make it tough.
2 very different methods adopted by CDF and
D0
Gives about a 3% error on the jet energy scale
Checks of various signals give faith in this scale
and error
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Back-up
CDF uncertainties on calorimeter simulation
Improvement possible with
higher statistical samples
Sensitive to 0.9x0.9 = 81% inner part of the tower.
 For tower boundaries: additional 10% uncertainty
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Total uncertainties:
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CDF single particle response simulation

Single particle response


Test beam
In situ:





Select ‘isolated’ tracks
Measure energy in tower
behind them
Dedicated trigger
Bgk subtraction
Tune simulation to describe E/p
distribution at each p
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CDF jet resolution (H1 Algorithm)





Apply relative corrections to make response flat in η.
Use tracks (0.5<Pt<15 GeV, Pt ordered), extrapolate to face of calorimeter
Select towers within Δη=0.1 and Δφ=0.2. (Central towers are 0.1x0.26.) Take
the nearest tower one if none within these limits.
Order selected towers in distance from the track.
Remove towers such that corresponding removed energy is always less or
equal to the energy of the track. Energy already removed by a previous
track is not considered by subsequent tracks.
Jet is sum of all quality-selected
tracks and remaining towers in the jet.

Scale the final jet energy

There is improvement (10-15%)
but need much more work for
optimization.

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Jet Algorithms
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Clusters using different Jet algorithms
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Lateral profile
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Lateral profiles scan
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Calorimeter simulation






Use MinBias or
isolated track trigger
Select good tracks
within central 81% of
tower.
No extra track within
7x7 towers, no
ShowerMax cluster.
Measure E/p in data
Tune Gflash
parameters
Difference in data
and simulation is
taken as uncertainty.
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E(EM)/p
E(HAD)/p
E(Total)/p
After BG subtraction
More statistics!
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Photon+jet balancing
Herwig Pythia Data
-0.371 -0.317 -0.360
Δφ> 3, No 2nd jet cut

PT balance
between photon
and jet is about 3%
different among
data and MC.
Δφ>3 , second Jet Pt<3 GeV
Fb  ( pTjet  pTg ) / pTg
Herwig Pythia Data
-0.328 -0.296 -0.306
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Photon/Z – jet balance
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Calorimeter simulation improvements



Tower-phi boundaries
improved with new
Simulation from 10%
uncertainty to less
than 5%
Old simulation
New Simulation 
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Lateral profile

Measure E/p signal in 5 towers adjacent in h

signal defined as 1×3 strip in φ

Plot E/p vs. relative eta for 5 towers

In Gflash, use formula for lateral profile

EM and HAD calorimeter probe different parts of
the hadronic shower
E/p vs ηrel
(Central)
excluding
90° crack
hrel 
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h (center of tower)  h (track )
h (width of tower) / 2
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Jet corrections to particle level (absolute)
 Monte Carlo simulation
used to compare
measured (calorimeter)
jets and particle (hadron)
jets.
 Depends on MC
simulation and how well
data are reproduced,
and on fragmentation
 Main uncertainties due
to calorimeter simulation
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Possible improvements

Absolute energy scale:

Better simulation translate in lower systematic uncertainties:

Old simulation (response as function of track momentum):


[0-12] GeV  2.5%, [12-20] GeV 3%, [20,+]  4%
New simulation (under study):

2% expected in the whole p range
 This would reduce absolute JES uncertainty from 1.8-2.5% to 1.4%

Specific b-jet correction


Using Zbbbar or photon+b
Jet resolution for higgs analysis

H1 algorithm: use tracking information for energy determination
of charged hadrons
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Cross-check using prompt photons


Photons are well measured in
EM calorimeter
Complications:

number of events at high ET very low


From D0 measurement, 40 evt. with
L=1 fb-1 and ETg > 300 GeV
Background due to p0

Purity 30-80 % for [20-100] GeV
photon transverse energy range

In CDF: use photon+jets (but also
Z+jets) for cross check and to
evaluate OOC corrections and JES
systematic uncertainty due to
Data/MC differences.
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