University of Chicago
Lecture 1: Toward an
Understanding of Hadronization
Rick Field
University of Florida
Calorimeter Jet
Enrico Fermi Institute, University of Chicago
Charged Particle Jet
CDF Run 2
From Feynman-Field to the Tevatron
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 1
Toward and Understanding of
Hadronization
1 hat!
From Feynman-Field to the Tevatron
st
Feynman
and
Field
 From 7 GeV/c p0’s to 600 GeV/c Jets.
Outgoing Parton
PT(hard)
 Some things we have learned about
quark and gluon jets at CDF.
Initial-State Radiation
Proton
Underlying Event
 Jet algorithms and the “jet” cross section
at CDF.
Lecture 1: University of Chicago
July 7, 2006
AntiProton
Rick Field – Florida/CDF
Outgoing Parton
Underlying Event
Final-State
Radiation
Page 2
The Feynman-Field Days
1973-1983
“Feynman-Field
Jet Model”
 FF1: “Quark Elastic Scattering as a Source of High Transverse Momentum
Mesons”, R. D. Field and R. P. Feynman, Phys. Rev. D15, 2590-2616 (1977).
 FFF1: “Correlations Among Particles and Jets Produced with Large Transverse
Momenta”, R. P. Feynman, R. D. Field and G. C. Fox, Nucl. Phys. B128, 1-65
(1977).
 FF2: “A Parameterization of the properties of Quark Jets”, R. D. Field and R. P.
Feynman, Nucl. Phys. B136, 1-76 (1978).
 F1: “Can Existing High Transverse Momentum Hadron Experiments be
Interpreted by Contemporary Quantum Chromodynamics Ideas?”, R. D. Field,
Phys. Rev. Letters 40, 997-1000 (1978).
 FFF2: “A Quantum Chromodynamic Approach for the Large Transverse
Momentum Production of Particles and Jets”, R. P. Feynman, R. D. Field and G.
C. Fox, Phys. Rev. D18, 3320-3343 (1978).
 FW1: “A QCD Model for e+e- Annihilation”, R. D. Field and S. Wolfram, Nucl.
Phys. B213, 65-84 (1983).
My 1st graduate
student!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 3
Before Feynman-Field
Rick Field 1968
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 4
Before Feynman-Field
Rick & Jimmie
1970
Rick & Jimmie
1968
Rick & Jimmie
1972 (pregnant!)
Rick & Jimmie at CALTECH 1973
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 5
Hadron-Hadron Collisions
FF1 1977 (preQCD)
 What happens when two hadrons
collide at high energy?
Hadron
???
Hadron
Feynman quote from FF1
“The model
we shall choose is not a popular one,
 Most of the time the hadrons
ooze
thatapart
we will
not duplicate too much of the
through each other andsofall
(i.e.
work of others who are similarly analyzing
no hard scattering). The outgoing
various models (e.g. constituent interchange
particles continue in roughly
the same
Parton-Parton
Scattering Outgoing Parton
model, multiperipheral
models,
etc.). We shall
direction as initial proton
and
assume that the high PT particles
arise from
“Soft” Collision
(no large transverse momentum)
antiproton.
direct hard collisions between constituent
in the incoming
particles, which
Hadron
 Occasionally there will bequarks
a large
Hadron
fragment or cascade down into several hadrons.”
transverse momentum meson.
Question: Where did it come from?
 We assumed it came from quark-quark
elastic scattering, but we did not know
how to calculate it!
Outgoing Parton
high PT meson
“Black-Box Model”
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 6
Quark-Quark Black-Box Model
No gluons!
Quark Distribution Functions
determined from deep-inelastic
lepton-hadron collisions
FF1 1977 (preQCD)
Feynman quote from FF1
“Because of the incomplete knowledge of
our functions some things can be predicted
with more certainty than others. Those
experimental results that are not well
predicted can be “used up” to determine
these functions in greater detail to permit
better predictions of further experiments.
Our papers will be a bit long because we
wish to discuss this interplay in detail.”
Quark-Quark Cross-Section
Unknown! Deteremined from
hadron-hadron collisions.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Quark Fragmentation Functions
determined from e+e- annihilations
Page 7
Quark-Quark Black-Box Model
Predict
particle ratios
FF1 1977 (preQCD)
Predict
increase with increasing
CM energy W
“Beam-Beam
Remnants”
Predict
overall event topology
(FFF1 paper 1977)
7 GeV/c p0’s!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 8
Telagram from Feynman
July 1976
SAW CRONIN AM NOW CONVINCED WERE RIGHT TRACK QUICK WRITE
FEYNMAN
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 9
Letter from Feynman
July 1976
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 10
Letter from Feynman Page 1
Spelling?
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 11
Letter from Feynman Page 3
It is fun!
Onward!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 12
Feynman Talk at Coral Gables
(December 1976)
1st transparency
Last transparency
“Feynman-Field
Jet Model”
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 13
QCD Approach: Quarks & Gluons
Quark & Gluon Fragmentation
Functions
Q2 dependence predicted from QCD
Parton Distribution Functions
Q2 dependence predicted from
QCD
FFF2 1978
Feynman quote from FFF2
“We investigate whether the present
experimental behavior of mesons with
large transverse momentum in hadron-hadron
collisions is consistent with the theory of
quantum-chromodynamics (QCD) with
asymptotic freedom, at least as the theory
is now partially understood.”
Quark & Gluon Cross-Sections
Calculated from QCD
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 14
High PT Jets
CDF (2006)
Feynman, Field, & Fox (1978)
Predict
large “jet”
cross-section
30 GeV/c!
Feynman quote
from FFF
600 GeV/c
Jets!
“At the time of this writing, there is
still no sharp quantitative test of QCD.
An important test will come in connection
with the phenomena of high PT discussed here.”
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 15
A Parameterization of
the Properties of Jets
Field-Feynman 1978
Secondary Mesons
(after decay)
continue
 Assumed that jets could be analyzed on a “recursive”
principle.
(bk) (ka)
 Let f(h)dh be the probability that the rank 1 meson leaves
fractional momentum h to the remaining cascade, leaving
Rank 2
Rank 1
quark “b” with momentum P1 = h1P0.
 Assume that the mesons originating from quark “b” are
distributed in presisely the same way as the mesons which
(cb)
(ba)
Primary Mesons
came from quark a (i.e. same function f(h)), leaving
quark “c” with momentum P2 = h2P1 = h2h1P0.
cc pair bb pair
Calculate F(z)
from f(h) and b i!
Original quark with
flavor “a” and
momentum P0
Lecture 1: University of Chicago
July 7, 2006
 Add in flavor dependence by letting bu = probabliity of
producing u-ubar pair, bd = probability of producing ddbar pair, etc.
 Let F(z)dz be the probability of finding a meson
(independent of rank) with fractional mementum z of the
original quark “a” within the jet.
Rick Field – Florida/CDF
Page 16
Feynman-Field Jet Model
R. P. Feynman
ISMD, Kaysersberg,
France, June 12, 1977
Feynman quote from FF2
“The predictions of the model are reasonable
enough physically that we expect it may
be close enough to reality to be useful in
designing future experiments and to serve
as a reasonable approximation to compare
to data. We do not think of the model
as a sound physical theory, ....”
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 17
Monte-Carlo Simulation
of Hadron-Hadron Collisions
FF1-FFF1 (1977)
“Black-Box” Model
F1-FFF2 (1978)
QCD Approach
FFFW “FieldJet” (1980)
QCD “leading-log order” simulation
of hadron-hadron collisions
the past
today
FF2 (1978)
Monte-Carlo
simulation of “jets”
ISAJET
HERWIG
(“FF” Fragmentation)
(“FW” Fragmentation)
tomorrow
Lecture 1: University of Chicago
July 7, 2006
SHERPA
Rick Field – Florida/CDF
“FF” or “FW”
Fragmentation
PYTHIA
PYTHIA 6.3
Page 18
QCD Monte-Carlo Models:
High Transverse Momentum Jets
Hard Scattering
Hard Scattering
Initial-State Radiation
“Jet”
Initial-State Radiation
Outgoing Parton
PT(hard)
Outgoing Parton
“Jet” PT(hard)
Proton
“Hard Scattering” Component
AntiProton
Underlying Event
Final-State Radiation
Underlying Event
Outgoing Parton
Proton
“Jet”
Final-State Radiation
AntiProton
Underlying Event
Outgoing Parton
Underlying Event
“Underlying Event”
 Start with the perturbative 2-to-2 (or sometimes 2-to-3) parton-parton scattering and add initial and finalstate gluon radiation (in the leading log approximation or modified leading log approximation).
 The “underlying event” consists of the “beam-beam remnants” and from particles arising from soft or
semi-soft multiple parton interactions (MPI).
The “underlying
event” is“jet”
an unavoidable
 Of course the outgoing colored partons fragment
into hadron
and inevitably “underlying event”
background to most collider observables
observables receive contributions from initial
and final-state radiation.
and having good understand of it leads to
more precise collider measurements!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 19
Monte-Carlo Simulation
of Quark and Gluon Jets
 ISAJET: Evolve the parton-shower from Q2 (virtual photon invariant mass) to Qmin ~ 5
GeV. Use a complicated fragmentation model to evolve from Qmin to outgoing hadrons.
Q2
 HERWIG: Evolve the parton-shower from Q2 (virtual
photon invariant mass) to Qmin ~ 1 GeV. Form color singlet
clusters which “decay” into hadrons according to 2-particle
phase space.
 MLLA: Evolve the parton-shower from Q2 (virtual
photon invariant mass) to Qmin ~ 230 MeV. Assume that
the charged particles behave the same as the partons
with Nchg/Nparton = 0.56!

hadrons
 
CDF Distribution of Particles in Jets
MLLA Curve!
Field-Feynman
5 GeV
1 GeV 200 MeV
Lecture 1: University of Chicago
July 7, 2006
= ln(Ejet/pparticle)
Rick Field – Florida/CDF
Page 20
Distribution of Particles in Jets
CDF Run 1 Analysis
 Momentum distribution of charged hadrons in
jets well described by MLLA!
 Dijet mass range 80-600 GeV
 Cutoff Qeff = 230  40 MeV
 Ncharged-hadrons/Npartons = 0.56  0.10
 Ratio of charged hadron multiplicities in gluon
and quark jets agrees with NNLLA
Both PYTHIA and HERWIG
predict a Gluon-Quark Ratio
that is smaller than the data!
Ratio = Ng-jet / Nq-jet
 Gluon-Quark Ratio = 1.6  0.2
Q = Ejet  qcone
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 21
Charged Multiplicity
in Quark and Gluon Jets
 CDF Run 1 data on the average charged
particle multiplicities in gluon and quark jets
versus Q = Ejet × qcone compared with NLLA,
PYTHIA, and HERWIG.
CDF Run 1 Analysis
 HERWIG and PYTHIA correctly predict the
charged multiplicity for gluon jets.
 Both HERWIG and PYTHIA over-estimate
the charged multiplicity in quark jets by
~30%!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 22
Distribution of Particles
in Quark and Gluon Jets
Both PYTHIA and HERWIG
predict more charged particles
than the data for quark jets!
CDF Run 1 Analysis
x = 0.37
0.14
0.05
0.02
0.007
pchg = 2 GeV/c
 Momentum distribution of charged particles in gluon jets. HERWIG 5.6 predictions are in a
good agreement with CDF data. PYTHIA 6.115 produces slightly more particles in the region
around the peak of distribution.
 Momentum distribution of charged particles in quark jets. Both HERWIG and PYTHIA
produce more particles in the central region of distribution.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 23
Evolution of Charged Jets
“Underlying Event”
Charged Particle  Correlations
PT > 0.5 GeV/c |h| < 1
Charged Jet #1
Direction
“Transverse” region
very sensitive to the
“underlying event”!
Look at the charged
particle density in the
“transverse” region!
2p
“Toward-Side” Jet

“Toward”
CDF Run 1 Analysis
Away Region
Charged Jet #1
Direction

Transverse
Region
“Toward”
“Transverse”

Leading
Jet
“Transverse”
Toward Region
“Transverse”
“Transverse”
Transverse
Region
“Away”
“Away”
Away Region
“Away-Side” Jet
0
-1
h
+1
 Look at charged particle correlations in the azimuthal angle relative to the leading charged
particle jet.
 Define || < 60o as “Toward”, 60o < || < 120o as “Transverse”, and || > 120o as “Away”.
 All three regions have the same size in h- space, hx = 2x120o = 4p/3.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 24
“Transverse”
Charged Particle Density
“Transverse” region as
defined by the leading
“charged particle jet”
“Toward”
“Transverse”
“Transverse”
“Away”
1.25
1.25
1.25
"Transverse"Charged
ChargedDensity
Density
Charged
Density
"Transverse"
"Transverse"
Charged Particle Jet #1
Direction

"Transverse"
"Transverse" Charged
Charged Particle
Particle
Density:
dN/dhd
Particle Density:
Density: dN/dhd
dN/dhd
CDF Run 1 Min-Bias
CDFRun
Run11Published
Min-Bias
CDF
CDF
Run
1 JET20
CDF
Run
1 Published
CDFRun
Run21Preliminary
JET20
CDF
CDF Run 2 Preliminary
PYTHIA
Tune
CDF
RunA2
CDFPreliminary
Run 1 Data
CDF
CDF
Preliminary
CDFdata
Preliminary
uncorrected
1.00
1.00
1.00
data
uncorrected
data
uncorrected
data
uncorrected
theory corrected
0.75
0.75
0.75
0.50
0.50
0.25
0.25
1.8
TeV
|h|<1.0
PT>0.5
GeV
|h|<1.0
|h|<1.0
PT>0.5
PT>0.5
GeV/c
GeV/c
|h|<1.0
PT>0.5
GeV
0.00
0.00
00
10 5 20
10
30
30
40
4015 50
50
20
60
60
70
702580
80
30
40 130
50
90
90 100
10035110
110 120
120
13045140
140 150
150
PT(charged
PT(charged jet#1)
jet#1) (GeV/c)
(GeV/c)
(GeV/c)
Excellent agreement
between Run 1 and 2!
 Shows the data on the average “transverse” charge particle density (|h|<1, pT>0.5 GeV) as
a function of the transverse momentum of the leading charged particle jet from Run 1.
 Compares the Run 2 data (Min-Bias, JET20, JET50, JET70, JET100) with Run 1.

The errors on the (uncorrected) Run 2 data include both statistical
and Tune
correlated
PYTHIA
A was tuned to fit
the “underlying event” in Run I!
systematic uncertainties.
Shows the prediction of PYTHIA Tune A at 1.96 TeV after detector simulation (i.e. after
CDFSIM).
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 25
Charged Multiplicity
in Charged Particle Jets
PYTHIA predict more
charged particles than the
data for charged jets!
Nchg (jet#1) versus PT(charged jet#1)
<Nchg> (Jet#1, R=0.7)
12
CDF Run 1 Analysis
1.8 TeV |eta|<1.0 PT>0.5 GeV
10
8
6
Includes charged particles
from the “underlying event”!
4
CDF
2
data uncorrected
theory corrected
0
0
5
10
15
20
25
30
35
40
45
50
PT(charged jet#1) (GeV)
Herwig
Isajet
Pythia 6.115
CDF Min-Bias
CDF JET20
 Plot shows the average number of charged particles (pT > 0.5 GeV, |h| < 1) within the leading
charged particle jet (R = 0.7) as a function of the PT of the leading charged jet. The solid
(open) points are Min-Bias (JET20) data. The errors on the (uncorrected) data include both
statistical and correlated systematic uncertainties. The QCD “hard scattering” theory curves
(Herwig 5.9, Isajet 7.32, Pythia 6.115) are corrected for the track finding efficiency.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 26
Charged Multiplicity
in Charged Particle Jets
Jet#1 Charged Multiplicity Distribution
% with Nchg
PT(jet#1) > 5 GeV
30%
CDF
Isajet
Herwig
data uncorrected
theory corrected
Pythia
20%
1.8 TeV |eta|<1.0 PT>0.5 GeV
PT(jet#1) > 30 GeV
10%
Includes charged particles
from the “underlying event”!
0%
1
2
3
4
5
6
7
8
9
Nchg
10
11
12
13
14
15
16
CDF Run 1 Analysis
 CDF Run 1 data on the multiplicity distribution of charged particles (pT > 0.5 GeV and |h| <
1) within chgjet#1 (leading charged jet) for PT(chgjet#1) > 5 and 30 GeV compared with the
QCD “hard scattering” Monte-Carlo predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA
6.115. Plot shows the percentage of events in which the leading charged jet (R = 0.7) contains
Nchg charged particles.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 27
Run 1 Fragmentation Function
Density F(z)=dNchg/dz
100.0
Charged Momentum Distribution Jet#1
PT(jet#1) > 30 GeV
<NchgJet#1> = 8.0
CDF
PT(jet#1) > 5 GeV
<NchgJet#1> = 4.0
data uncorrected
1.8 TeV |eta|<1.0 PT>0.5 GeV
10.0
CDF Run 1 Analysis
Includes charged particles
from the “underlying event”!
1.0
PT(jet#1) > 2 GeV
<NchgJet#1> = 2.5
0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
z = p(charged)/P(charged jet#1)
 CDF Run 1 data on the momentum distribution of charged particles (pT > 0.5 GeV and |h|
< 1) within chgjet#1 (leading charged jet). The points are the charged number density,
F(z) = dNchg/dz, where z = pchg/P(chgjet#1) is the ratio of the charged particle momentum
to the charged momentum of chgjet#1. The integral of F(z) is the average number of
particles within chgjet#1.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 29
Run 1 Fragmentation Function
Charged Momentum Distribution Jet#1
Density F(z)=dNchg/dz
100.0
PT(jet#1) > 5 GeV
PYTHIA does not
agree at high z!
CDF
data uncorrected
theory corrected
10.0
1.8 TeV |eta|<1.0 PT>0.5 GeV
CDF Run 1 Analysis
1.0
Herwig
Isajet
Pythia 6.115
CDF Min-Bias
0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
z = p(charged)/P(charged jet#1)
 CDF Run 1 data from on the momentum distribution of charged particles (pT > 0.5 GeV
and |h| < 1) within chgjet#1 (leading charged jet) for PT(chgjet#1) > 5 GeV compared with
the QCD “hard scattering” Monte-Carlo predictions of HERWIG, ISAJET, and
PYTHIA. The points are the charged number density, F(z) = dNchg/dz, where
z = pchg/P(chgjet#1) is the ratio of the charged particle momentum to the charged
momentum of chgjet#1.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 30
Run 1 Fragmentation Function
Charged Momentum Distribution Jet#1
Density F(z)=dNchg/dz
100.0
PYTHIA does not
agree at high z!
CDF
PT(jet#1) > 30 GeV
data uncorrected
theory corrected
10.0
1.8 TeV |eta|<1.0 PT>0.5 GeV
CDF Run 1 Analysis
1.0
Herwig
Isajet
Pythia 6.115
CDF JET20
0.1
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
z = p(charged)/P(charged jet#1)
 Data from Fig. 3.8 on the momentum distribution of charged particles (pT > 0.5 GeV and
|h| < 1) within chgjet#1 (leading charged jet) for PT(chgjet#1) > 30 GeV compared with the
QCD “hard scattering” Monte-Carlo predictions of HERWIG, ISAJET, and PYTHIA.
The points are the charged number density, F(z) =dNchg/dz, where z = pchg/P(chgjet#1) is
the ratio of the charged particle momentum to the charged momentum of chgjet#1.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 31
The “Transverse” Regions
as defined by the Leading Jet
Jet #1 Direction
“Transverse” region is
very sensitive to the
“underlying event”!
Charged Particle  Correlations
pT > 0.5 GeV/c |h| < 1
2p
“Toward-Side” Jet
CDF Run 2 Analysis
Jet #1 Direction

“Toward”
“Transverse”
“Transverse”
“Away”
Away Region
Transverse
Region 1

“Toward”
“Trans 1”
Look at the charged
particle density in the
“transverse” region!

Leading
Jet
“Trans 2”
Toward Region
Transverse
Region 2
“Away”
Away Region
“Away-Side” Jet
0
-1
h
+1
 Look at charged particle correlations in the azimuthal angle relative to the leading

calorimeter jet (JetClu R = 0.7, |h| < 2).
o
o
o
o
o
Define || < 60 as “Toward”, 60 < - < 120 and 60 <  < 120 as “Transverse 1” and
o
“Transverse 2”, and || > 120 as “Away”. Each of the two “transverse” regions have
o
area h = 2x60 = 4p/6. The overall “transverse” region is the sum of the two
o
transverse regions (h = 2x120 = 4p/3).
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 32
Charged Particle Density  Dependence
Refer to this as a
“Leading Jet” event
Jet #1 Direction
Charged
Particle Density:
Density: dN/dhd
dN/dhd
Charged Particle

10.0
10.0
Subset
“Transverse”
“Transverse”
“Away”
Refer to this as a
“Back-to-Back” event
Jet #1 Direction

“Toward”
“Transverse”
“Transverse”
Charged Particle
Particle Density
Density
Charged
“Toward”
CDF
CDF Preliminary
Preliminary
30 << ET(jet#1)
ET(jet#1) << 70
70 GeV
GeV
30
Back-to-Back
data
data uncorrected
uncorrected
Leading Jet
Min-Bias
"Transverse"
"Transverse"
Region
Region
1.0
1.0
Jet#1
Jet#1
Charged
Charged Particles
Particles
(|h|<1.0,
(|h|<1.0, PT>0.5
PT>0.5 GeV/c)
GeV/c)
0.1
0.1
00
30
30
60
60
90
“Away”
120
150
180
210
210
240
240
270
270
300
300
330
330
360
360
 (degrees)
Jet #2 Direction
 Look at the “transverse” region as defined by the leading jet (JetClu R = 0.7, |h| < 2) or by the
leading two jets (JetClu R = 0.7, |h| < 2). “Back-to-Back” events are selected to have at least
two jets with Jet#1 and Jet#2 nearly “back-to-back” (12 > 150o) with almost equal
transverse energies (ET(jet#2)/ET(jet#1) > 0.8) and with ET(jet#3) < 15 GeV.
 Shows the  dependence of the charged particle density, dNchg/dhd, for charged
particles in the range pT > 0.5 GeV/c and |h| < 1 relative to jet#1 (rotated to 270o) for 30
< ET(jet#1) < 70 GeV for “Leading Jet” and “Back-to-Back” events.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 33
“Transverse” Charge Density
PYTHIA Tune A vs HERWIG
“Leading Jet”
Jet #1 Direction

"AVE Transverse" Charge Density: dN/dhd
1.0
“Transverse”
“Transverse”
“Away”
“Back-to-Back”
Jet #1 Direction

“Toward”
“Transverse”
“Transverse”
"Transverse" Charge Density
“Toward”
CDF Preliminary
data uncorrected
theory + CDFSIM
0.8
Leading Jet
PY Tune A
0.6
0.4
HW
Back-to-Back
0.2
1.96 TeV
Charged Particles (|h|<1.0, PT>0.5 GeV/c)
0.0
0
50
“Away”
100
150
200
250
ET(jet#1) (GeV)
Jet #2 Direction
Now look in detail at “back-to-back” events in
the region 30 < ET(jet#1) < 70 GeV!
 Shows the average charged particle density, dNchg/dhd, in the “transverse” region (pT >
0.5 GeV/c, |h| < 1) versus ET(jet#1) for “Leading Jet” and “Back-to-Back” events.
 Compares the (uncorrected) data with PYTHIA Tune A and HERWIG after CDFSIM.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 34
Charged Particle Density
PYTHIA Tune A vs HERWIG
HERWIG (without multiple parton
interactions) produces too few charged
particles in the “transverse” region
for 30 < ET(jet#1) < 70 GeV!
Charged Particle Density: dN/dhd
Charged Particle Density: dN/dhd
10.0
1.0
CDF Preliminary
"Transverse"
Region
data uncorrected
theory + CDFSIM
0.1
0
30
60
90
120
150
180
210
 (degrees)
Jet#1
HERWIG
1.0
CDF Preliminary
"Transverse"
Region
data uncorrected
theory + CDFSIM
PYTHIA produces too
0.1 many
0
30
60
240
270
300
330
360
particle in the “away-side”
jet!
90
120
150
180
210
Jet#1
240
270
300
330
360
330
360
 (degrees)
Data - Theory: Charged Particle Density dN/dhd
Data - Theory: Charged Particle Density dN/dhd
1.0
1.0
CDF Preliminary
data uncorrected
theory + CDFSIM
Back-to-Back
30 < ET(jet#1) < 70 GeV
CDF Preliminary
PYTHIA Tune A
data uncorrected
theory + CDFSIM
0.5
Data - Theory
0.5
Data - Theory
30 < ET(jet#1) < 70 GeV
Charged Particles
(|h|<1.0, PT>0.5 GeV/c)
Back-to-Back
Charged Particle Density
Charged Particle Density
PY Tune A
10.0
30 < ET(jet#1) < 70 GeV
Charged Particles
(|h|<1.0, PT>0.5 GeV/c)
Back-to-Back
0.0
"Transverse"
Region
-0.5
Back-to-Back
30 < ET(jet#1) < 70 GeV
0.0
"Transverse"
Region
-0.5
Jet#1
Charged Particles
(|h|<1.0, PT>0.5 GeV/c)
HERWIG
Jet#1
Charged Particles
(|h|<1.0, PT>0.5 GeV/c)
-1.0
-1.0
0
30
60
90
120
150
180
210
240
270
300
330
360
0
30
90
120
150
180
210
240
270
300
 (degrees)
 (degrees)
Lecture 1: University of Chicago
July 7, 2006
60
Rick Field – Florida/CDF
Page 35
Jet Algorithms
 Clustering algorithms are used to combine calorimeter towers or charged particles into “jets”
in order to study the event topology and to compare with the QCD Monte-Carlo Models.
 We do not detect partons! The outgoing partons fragment into hadrons before they travel a
distance of about the size of the proton. At long distances the partons manifest themselves as
“jets”. The “underlying event” can also form “jets”. Most “jets” are a mixture of particles
arising from the “hard” outgoing partons and the “underlying event”.
 Since we measure hadrons every observable is infrared and collinear safe. There are no
divergences at the hadron level!
 Every “jet” algorithms correspond to a
different observable and different
algorithms give different results.
 Studying the difference between the
algorithms teaches us about the event
structure.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 38
Jet Corrections & Extrapolations
 Calorimeter Level Jets → Hadron Level Jets:
Hadron ← Parton
 We measure “jets” at the “hadron level” in the calorimeter.
 We certainly want to correct the “jets” for the detector resolution and
efficiency.
 Also, we must correct the “jets” for “pile-up”.
 Must correct what we measure back to the true “hadron level” (i.e.
particle level) observable!
 Particle Level Jets (with the “underlying event” removed):
Useless without a model
of hadronization!
Outgoing Parton
I do
believe
wemodel
shoulddependent
extrapolate
 Do we want
to not
make
further
corrections?
the data to the parton level! We should
 Do we want to try and subtract the “underlying event” from the
publish
what
we measure
(i.e. hadron level
observed
“particle
level”
jets.
with the “underlying event”)!
 This cannot really be done, but if you trust the Monte-Carlo
with event”
theory you
we should
modeling ofTo
thecompare
“underlying
can do it by using the
“extrapolate”
the
parton
level
to the
Monte-Carlo models (use PYTHIA Tune A).
(i.e. add hadronization
and
 This is nohadron
longerlevel
an observable,
it is a model dependent
the “underlying event” to the parton level)!
extrapolation!
HERWIG,
MC@NLO
 Hadron LevelPYTHIA,
Jets → Parton
Level
Jets:
PT(hard)
Initial-State Radiation
Proton
AntiProton
Underlying Event
Outgoing Parton
Underlying Event
Final-State
Radiation
Lecture 1: University of Chicago
July 7, 2006
 Do we want to use the data to try and extrapolate back to the
parton level? What parton level, PYTHIA (Leading Log) or fixed
order NLO?
Next-to-leading
order
 This
also cannot
really be done, but again if you trust the Monteparton
level
calculation
Carlo models you can try and do it by using the Monte-Carlo
0, 1, 2, or 3 partons!
models
(use PYTHIA Tune A) including ISR and FSR.
 Cannot extrapolate the data to fixed order NLO!
Rick Field – Florida/CDF
Page 39
Good and Bad Algorithms
Calorimeter Jet
Particle
Jet
 In order to correct what we see in the calorimeter back
to the hadron level we must use an algorithm that can
be defined at both the calorimeter and particle level.
 If you insist on extrapolating the data to the parton
level then it is better to use an algorithm that is well
defined at the parton level (i.e. infrared and collinear
safe at the parton level).
 If you hadronize the parton level and add the
“underlying event” (i.e. PYTHIA, HERWIG,
MC@NLO) then you do not care if the algorithm is
infrared and collinear safe at the parton level. You
can predict any hadron level observable!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Infrared Safety (Parton Level)
Soft parton emission changes jet multiplicity
Collinear Safety (Parton Level)
below threshold
(no jets)
above threshold
(1 jet)
Page 40
Four Jet Algorithms
Towers not included in a
jet (i.e. “dark towers”)!
Bad
 JetClu is bad because the algorithm cannot be defined at the particle level.
 The MidPoint and Modified MidPoint (i.e. Search Cone) algorithms are not infrared and
collinear safe at the parton level.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 41
KT Algorithm
 kT Algorithm:
Begin







For each precluster, calculate
di  pT2,i
For each pair of preculsters, calculate
( y  y j ) 2  (i   j ) 2
dij  min( pT2 ,i , pT2 , j ) i
D2
Find the minimum of all di and dij.
Merge
i and j
yes
Minumum
is dij?
Cluster together calorimeter towers by their kT proximity.
Infrared and collinear safe at all orders of pQCD.
No splitting and merging.
No ad hoc Rsep parameter necessary to compare with parton level.
Every parton, particle, or tower is assigned to a “jet”.
No biases from seed towers.
Favored algorithm in e+e- annihilations!
no
Will the KT algorithm be
effective in the collider
environment where there is
an “underlying event”?
Move i to list of jets
yes
Any
Preclusters
left?
Raw Jet ET = 533 GeV
KT Algorithm
Raw Jet ET = 618 GeV
no
End
Outgoing Parton
PT(hard)
Initial-State Radiation
Proton
AntiProton
Underlying Event
Underlying Event
CDF Run 2
Outgoing Parton
Final-State
Radiation
Lecture 1: University of Chicago
July 7, 2006
Only towers with ET > 0.5 GeV are shown
Rick Field – Florida/CDF
Page 42
KT Inclusive Jet Cross Section





KT Algorithm (D = 0.7)
Data corrected to the hadron level
L = 385 pb-1
0.1 < |yjet| < 0.7
Compared with NLO QCD (JetRad)
corrected to the hadron level.
Sensitive to UE + hadronization
effects for PT < 300 GeV/c!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 43
Search Cone
Inclusive Jet Cross Section
 Modified MidPoint Cone
Algorithm (R = 0.7, fmerge = 0.75)
 Data corrected to the hadron level
and the parton level
 L = 1.04 fb-1
 0.1 < |yjet| < 0.7
 Compared with NLO QCD
(JetRad, Rsep = 1.3)
Sensitive to UE + hadronization
effects for PT < 200 GeV/c!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 44
Hadronization and
“Underlying Event” Corrections
 Compare the hadronization and “underlying event” corrections for the KT algorithm (D = 0.7)
and the MidPoint algorithm (R = 0.7)!
 We see that the KT algorithm (D = 0.7) is slightly more sensitive to the underlying event than
the cone algorithm (R = 0.7), but with a good model of the “underlying event” both cross
sections can be measured at the Tevatrun!
Note that DØ does not make any
corrections for hadronization
or the “underlying event”!?
MidPoint Cone Algorithm (R = 0.7)
The KT algorithm is slightly more
sensitive to the “underlying event”!
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Page 45
Summary and Conclusions
 Neither HERWIG or PYTHIA describe
Charged
Particle
kT Distribution in Jets
precisely the distribution
charged
particles
Was this Particle
measured in Run 1?
in quark and gluon jets at the Tevatron!
Jet
 To learn about the fragmentation function at large z we should
Comparison
Only
compare the inclusive “jet” cross-sectionShape
to the
inclusive
charged particle cross section!
 We have events with 600 GeV “jets” so we must have events
In 1 fb-1 we have thousands of
with 300 GeV/c charged particles!
charged tracks with p > 100 GeV/c!
T
 I wish I could show you the following:
Charged Particle PT Distribution
100,000,000
CDF Run 2 Pre-Preliminary
Number in 1 GeV/c Bin
 A lot of work has been done in comparing to analytic
MLLA calculations (Korytov and students), but more
work needs to be done in improving the
fragmentation models in HERWIG and PYTHIA!
 CDF measured fragmentation functions at different Q2
compared with PYTHIA and HERWIG.
 The kT distribution of charged particles within “jets”
compared with PYTHIA and HERWIG.
 The ratio of the inclusive charged particle cross-section to the
inclusive “jet” cross-section compared with PYTHIA and
HERWIG.
Lecture 1: University of Chicago
July 7, 2006
Rick Field – Florida/CDF
Jet 100 Trigger
10,000,000
1,000,000
100,000
1.96 TeV
10,000
Charged Particles (|h|<1.0)
1,000
0
10
20
30
40
50
60
70
80
90
Charged Particle PT (GeV/c)
Sergo is “blessing” this
today in the QCD group!
Page 46
100