Transcript Dijet Transverse Thrust cross sections at D&#216

Dijet Transverse Thrust cross
sections at DØ
Veronica Sorin
University of Buenos Aires
Outline
• Introduction:
– Overview
– The KT algorithm
– Definition of the observable
• Dijet Transverse Thrust cross section
• Systematic uncertainties
• Comparison with theory
• Conclusions
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Theoretical Introduction
Quantum Chromodynamics:
describe the interaction between quarks
and gluons, which carry color charge,
conventionally called: blue, red and
green.
Fundamental Vertices
s
s
s
Main QCD characteristics:
Asymptotic freedom: as the energy of
the interaction increases, the strength
of the coupling get smaller, allowing
the aplication of perturbative
techniques (pQCD).
Confinement: quarks and gluons cannot
be seen as isolated particles, partons (q
and g) are bound together into hadrons.
Jet Physics
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parton jetparticle jetcalorimeter jet
Jet Physics
CH
FH
At the final state of an hadronic collision,
QCD predicts the appareance of highly
collimated sprays of particles, which are
called Jets .
hadrons

EM

K
Time
q
g
q

p

q
q
p
At the DØ experiment using the Fermilab
Laboratory Tevatron collider, we study pp
collisions at a c.m. energy of 1.8 TeV. The
bunch crossing occurs every 3.5 µs.
By identifying these jets, experimental
measurements can be compared with
pQCD predictions.
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Panoramic view of the Fermilab Laboratory
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Event Shapes
Event shapes have been extensively studied at e+eand ep experiments to:
• study spatial distribution of hadronic final states
• test perturbative QCD predictions
• extract a precise value of s
• recently to test QCD developments like resummation
calculations and non-perturbative corrections
Resummations: needed at small values of the shape variable where
fixed-order perturbative calculations are expected to fail.
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Thrust
nˆ : direction which maximizes T
The sum is done over all partons/particles/
detector elements/jets in the event
Jet production rate: s2 is LO
T : Pencil-likeness of the event
s3 is NLO
2 partons in final state
T=1
Thrust (T ≠ 1):
s3 is LO
s4 is NLO
T=[1/2,1]
(N...NLO)
N partons in final state
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T in hadron colliders
Busy environment: underlying event, pile-up, multiple
interactions and noise
We have derived a correction to eliminate
particles
jets
on average the energy contributions from
sources other than the hard interaction
itself.
– c.m system is not the parton-parton c.m.
The pp
Thrust is not invariant under z boosts
Transverse Thrust
Lorentz invariant quantity
TT
3D
2D
By replacing momenta with transverse momenta
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The DØ Calorimeters
y
   
h =  ln t an 
2





Z
x
• Transverse segmentation (towers)
• Liquid argon active medium
and uranium absorber
• Hermetic with full coverage
sE / E = 15% /
|h| < 4.2
sE / E = 45% / for pions
l int > 7.2 (total)
Dh x D
= 0.1 x 0.1
for electrons
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parton jet particle jet calorimeter jet
Jet Algorithms
•Parton jet: q and g (before hadronization)
CH
FH
• Particle jet: final state particles
(after hadronization)
hadrons

EM

• Calorimeter jet: measured object
(after calorimeter shower)
K
Time
q
g
KT (Ellis-Soper)
Iterative
Recombination
Fixed cone of radius R
Distance parameter D
Overlapping cones:
arbitrary criteria to
resolve ambiguities

p
Fixed Cone (RunI)

q
p
Sensitivity to soft
radiation
Infrared and collinear
safe
Requires ad-hoc
parameter for the theory
Same algorithm in
theory and experiment
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RunI DØ Analyses using the KT algorithm
• “Subjet Multiplicity of Gluon and Quark Jets”
Phys. Rev. D 65, 052008 (2002)
• “The Inclusive Jet Cross Section”
Phys. Lett. B 525, 211 (2002)
• “Dijet Transverse Thrust Cross Sections”
paper in preparation
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KT Algorithm at DØ (RunI)
(Ellis-Soper PRD 48 3160)
d ij = min( PT2,i , PT2, j )
KT jet
DRij2
D2
Cone jet
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KT Algorithm at DØ (RunI)
For each particle or pair of particles :
d ij = min( P , P )
2
T ,i
Yes
Merge i+j
2
T, j
Is
DRij2
D2
dii = PT2,i
Beam

 
p ij = p i  p j
d ij less
than
d ii?
Eij = Ei  E j
No
Move i to list of jets
Yes
Any
left?
Beam
No
• Produce list of jets
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Jet Momentum Scale Correction
Calorimeter jet
Particle jet
ptcl
Pjet
=
meas
Pjet
O
R jet
• Offset (O): Ur noise, pileup, multiple interactions,
underlying event (ue)
• Response
(Rjet): Pmeas / Ptrue
(using transverse momentum balance in -jet events)
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Offset Correction
O = UE + N
Ur noise, pileup, multiple interactions
Underlying Event
MC events + detector
simulation + noise data
Noise data can be:
• Zero bias: random crossing
(N)
MC Jets
MC+Noise
• _Minimum bias: crossing with a
pp interaction (UE)
The offset contribution is obtained as the
momentum difference between jets.
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Offset Correction
O = UE + N
.
.
.
MC + Overlayed to crossing with
inelastic interaction
N(GeV)
Luminosity dependent (L in cm-2 s-1)
MC + Overlayed to random
crossing
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Monte Carlo Closure
Rjet Correction
Pmeas / Pptcl
Rjet = a + b ln(Pjet) + c ln2(Pjet)
D=1 (KT jets)
Pptcl (GeV)
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Dijet TransverseThrust
• Sum done over jets
• Jets have been reconstructed
with the KT algorithm with D=1
Jet Momentum scale correction does not eliminate low energy jets ( high
probability to originate 100% from background)  distort the shape of the
physical distributions
Observable selected to reduce
detector effects and maximize
the signal in a hadron collider.
Only the two leading jets
will be used to calculate
Thrust
The spatial configuration of the two
leading jets inherits the information of
the other jets in the event
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Selection of the observable
Effects of noise and luminosity on TT
The addition of randomly
oriented noise jets renders
the event more isotropic
Use only the 2 leading jets
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Selection of the observable
The event energy scale
Look for a variable correlated with Q2 and with low sensitivity to noise
HT3 (scalar sum of the transverse momentum of the three leading
jets)
Noise jets
ET3 spectrum
HT3 vs HT
Data
HT at parton level: measure of Q2
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Brief Recapitulation
• Measurement of T2T cross section as a function of HT3
• Using jets for which we have derived a correction that
eliminates on average the contributions not related with the
hard interaction.
2 / 2  T2T  1
120o
O(s3) calculations can not cover the whole physical range:
for
2 / 2  T2T  3 / 2 , the LO calculation is O(s4)
• Test quality of QCD predictions
• Study significance of resummation calculations
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Coming up now….
• Observed Dijet Transverse Thrust Cross Sections
• Systematic Uncertainties:
– Momentum Scale Correction
– Energy and Angular resolutions
– Unfolding
• Final results and Comparison with Theory
• Conclusions
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Dijet Transverse Thrust cross section
Run Ib (1994 - 1996) , s = 1.8 TeV ,  L = 88 pb 1

ˆ
p

n
KT algorithm (parameter D = 1)

t
i
i
T2T = maxnˆ

i pt i
Event Selection:
• Vertex cut (| z | < 50 cm, e ~ 90 %)
• Cut on missing ET (ET/pTlj < 0.7, e ~ 99.8 %)
Jet Selection:
• Jet quality cuts (e ~ 99.5 % )
( 0.05 < EMF < 0.95, CHF < 0.4 )
• Kinematic cuts: |h1,2| < 1
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HT3 : scalar sum of the transverse
momentum of the three leading jets.
( use 3rd jet only when | h3 | < 3)
It is presented in four HT3 ranges
Four single jet triggers are used for
different HT3 ranges where they are
fully efficient.
Jet Trigger
Jet30
Jet50
Jet85
JetMax
HT3 distributions
HT3 range (GeV)
160-260
260-360
360-430
430-700
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Observed T cross sections
T
2
ds
N
=
T
d T2
DT2T L e
log( 1  T2T )
ds
(1  T )
d T2T
T
2
Resummations ?
LO O(s4)
Distributions still distorted due
to finite detector resolutions
Theoretical Predictions:
Jetrad : QCD event generator
O(s3).
NLOJET++ : NLO 3 jets generator O(s4).
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Momentum scale correction
Uncertainty on the Jet Momentum calibration propagates to
the thrust via two mechanisms: errors between 10-25%
T value changes
Migration of events
between HT3 bins
Dominant Effect
Low energy jets :
2-5% uncertainty to take into account reconstruction efficiencies and
contamination.
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Energy Resolutions
Measured in two jet events, assuming:
pT1  pT2
s1 = s 2
Fractional Resolution
1
0.06
Measured using PT
balance in data, in the
limit of no soft radiation.
0.02
0
Affects T via two
mechanisms:
200
300
Average Momentum (P1T + P2T)/2 (GeV)
 Effect smaller than 5%
Deconvolution
100
T value changes
Event migration
between HT3
ranges
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 Resolutions
Calculated from position
difference between calorimeter
and particle MC jets:
s ( E , h ) = A 
B C
 2
E E
MC smeared
MC
Important effect in the limit T  1
10-2
10-4
10-6
10-6
10-4
10-2
1-T
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Unfolding
Smear MC at particle level by energy and angular resolutions
Correction factor extracted
from MC as : generated / smeared
MC
Uncertainty:
Conservative way:
let the contents on
each bin vary freely

1-T
Correlation Matrix
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Correction factors
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DØ preliminary
DØ preliminary
DØ preliminary
DØ preliminary
CTEQ4HJ, µF = µR = PTmax/2
Only statistical errors are shown.
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DØ preliminary
DØ preliminary
DØ preliminary
DØ preliminary
Only statistical errors are shown.
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Sources of systematic uncertainties
(2nd Bin)
9.5
9
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Sources of systematic uncertainties
9.5
9
(2nd Bin)
Using the full covariance matrix (Cij )
 2 =  ( Di  Ti ) Cij1 ( D j  T j )
ij
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DØ preliminary
Comparison with theory (s3)
Jetrad up to T2T = 3 / 2
DØ preliminary
DØ preliminary
Thrust Range (1-T)
0. – 0.1
0. – 0.12
0. – 0.14
2
ndof
Prob (%)
10.19
12.98
41.52
10
11
12
42.40
29.46
0.004
Thrust range 10-4-10-1.2
HT3
2
160-260
95.08
260-360
81.68
360-430
62.15
430-700
27.69
Thrust Range (1-T)
-2.4
-1.2
10 – 10
10-3 – 10-1.2
10-4 – 10-1.2
2
ndof
2.69
3.76
95.08
5
6
7
Prob (%)
74.76
70.9
0.
Strong point to point correlations
in the uncertainty
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Comparison with theory (s4)
DØ
DØpreliminary
preliminary
DØ preliminary
DØ preliminary
Thrust Range (1-T)
2
ndof
0.01. – 0.12
0.01 – 0.14
0.01 – 0.28
6.10
6.78
15.15
10
11
16
Prob (%)
80.67
81.66
51.36
Thrust range 10-4-10-1.2
HT3
2
160-260
28.86
260-360
8.25
360-430
3.89
430-700
4.54
Thrust Range (1-T)
-2.4
-1.2
10 – 10
10-3 – 10-1.2
10-4 – 10-1.2
2
ndof
Prob (%)
3.19
6.26
28.86
5
6
7
67.0
39.5
0.01
430<HT3<700
DØ preliminary
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Conclusions
The first precise measurement of an event shape distribution such
as ds/dT in a hadron collider.
The prediction s3 (Jetrad) agrees with data except for high T
values, 1-T < 10-3 and in the low region 1-T > 0.12 .
Resummation calculations needed in the limit T  1.
Between 2 / 2  T2T  3 / 2 the LO prediction is O(s4).
Excellent opportunity to test the recently developed NLO 3-jet
generators.
This prediction (NLOJET++) agrees with data over the whole T
range (T ≠ 1), except in the limit T  1 for low HT3, where higher
order corrections are still important.
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