1. University of Chicago Lecture 1: Toward an
Understanding of Hadronization
Rick Field
University of Florida
Enrico Fermi Institute, University of Chicago
CDF Run 2
From Feynman-Field to the Tevatron
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

2. Toward and Understanding of Hadronization
From Feynman-Field to the Tevatron
1st hat!
Feynman
and
Field
From 7 GeV/c p0’s to 600 GeV/c Jets.
Some things we have learned about quark and gluon jets at CDF.
Jet algorithms and the “jet” cross section at CDF.
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

3. The Feynman-Field Days
“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, (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, (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, (1978).
FW1: “A QCD Model for e+e- Annihilation”, R. D. Field and S. Wolfram, Nucl. Phys. B213, (1983).
My 1st graduate student!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

4. Rick Field – Florida/CDF
Before Feynman-Field
Rick Field 1968
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

5. Rick Field – Florida/CDF
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

6. Hadron-Hadron Collisions
FF (preQCD)
What happens when two hadrons collide at high energy?
Feynman quote from FF1
“The model we shall choose is not a popular one,
so that we will not duplicate too much of the
work of others who are similarly analyzing
various models (e.g. constituent interchange
model, multiperipheral models, etc.). We shall
assume that the high PT particles arise from
direct hard collisions between constituent
quarks in the incoming particles, which
fragment or cascade down into several hadrons.”
Most of the time the hadrons ooze through each other and fall apart (i.e. no hard scattering). The outgoing particles continue in roughly the same direction as initial proton and antiproton.
Occasionally there will be a large 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!
“Black-Box Model”
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

7. Quark-Quark Black-Box Model
No gluons!
FF (preQCD)
Quark Distribution Functions
determined from deep-inelastic
lepton-hadron collisions
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 Fragmentation Functions
determined from e+e- annihilations
Quark-Quark Cross-Section
Unknown! Deteremined from
hadron-hadron collisions.
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

8. Quark-Quark Black-Box Model
Predict
particle ratios
FF (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

9. SAW CRONIN AM NOW CONVINCED WERE RIGHT TRACK QUICK WRITE
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

10. Rick Field – Florida/CDF
Letter from Feynman
July 1976
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

11. Letter from Feynman Page 1
Spelling?
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

12. Letter from Feynman Page 3
It is fun!
Onward!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

13. 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

14. QCD Approach: Quarks & Gluons
Quark & Gluon Fragmentation 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.”
Parton Distribution Functions
Q2 dependence predicted from QCD
Quark & Gluon Cross-Sections
Calculated from QCD
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

15. High PT Jets CDF (2006) Feynman, Field, & Fox (1978) 30 GeV/c! Predict
large “jet” cross-section
30 GeV/c!
Feynman quote from FFF
“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.”
600 GeV/c Jets!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

16. A Parameterization of the Properties of Jets
Field-Feynman 1978
Secondary Mesons
(after decay)
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 quark “b” with momentum P1 = h1P0.
Rank 2
Rank 1
Assume that the mesons originating from quark “b” are distributed in presisely the same way as the mesons which came from quark a (i.e. same function f(h)), leaving quark “c” with momentum P2 = h2P1 = h2h1P0.
Primary Mesons
(cb)
(ba)
cc pair
bb pair
continue
Add in flavor dependence by letting bu = probabliity of producing u-ubar pair, bd = probability of producing d-dbar pair, etc.
Calculate F(z) from f(h) and bi!
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.
Original quark with flavor “a” and momentum P0
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

17. 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

18. Monte-Carlo Simulation of Hadron-Hadron Collisions
FF1-FFF1 (1977) “Black-Box” Model
FF2 (1978)
Monte-Carlo simulation of “jets”
F1-FFF2 (1978) QCD Approach
FFFW “FieldJet” (1980)
QCD “leading-log order” simulation
of hadron-hadron collisions
“FF” or “FW” Fragmentation
the past
today
ISAJET
(“FF” Fragmentation)
HERWIG
(“FW” Fragmentation)
PYTHIA
tomorrow
SHERPA
PYTHIA 6.3
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

19. QCD Monte-Carlo Models: High Transverse Momentum Jets
“Hard Scattering” Component
“Underlying Event”
Start with the perturbative 2-to-2 (or sometimes 2-to-3) parton-parton scattering and add initial and final-state 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).
Of course the outgoing colored partons fragment into hadron “jet” and inevitably “underlying event” observables receive contributions from initial and final-state radiation.
The “underlying event” is an unavoidable background to most collider observables and having good understand of it leads to more precise collider measurements!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

20. 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.
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.
hadrons
Field-Feynman
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! Q2
CDF Distribution of Particles in Jets
MLLA Curve!
5 GeV
1 GeV
200 MeV
= ln(Ejet/pparticle)
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

21. Distribution of Particles in Jets
CDF Run 1 Analysis
Momentum distribution of charged hadrons in jets well described by MLLA!
Dijet mass range 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
Gluon-Quark Ratio = 1.6  0.2
Both PYTHIA and HERWIG predict a Gluon-Quark Ratio that is smaller than the data!
Ratio = Ng-jet / Nq-jet
Q = Ejet  qcone
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

22. 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

23. Distribution of Particles in Quark and Gluon Jets
Both PYTHIA and HERWIG predict more charged particles than the data for quark jets!
pchg = 2 GeV/c
CDF Run 1 Analysis
x =
Momentum distribution of charged particles in gluon jets. HERWIG 5.6 predictions are in a good agreement with CDF data. PYTHIA 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

24. Evolution of Charged Jets “Underlying Event”
Charged Particle Df Correlations PT > 0.5 GeV/c |h| < 1
Look at the charged particle density in the “transverse” region!
“Transverse” region very sensitive to the “underlying event”!
CDF Run 1 Analysis
Look at charged particle correlations in the azimuthal angle Df relative to the leading charged particle jet.
Define |Df| < 60o as “Toward”, 60o < |Df| < 120o as “Transverse”, and |Df| > 120o as “Away”.
All three regions have the same size in h-f space, DhxDf = 2x120o = 4p/3.
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

25. “Transverse” Charged Particle Density
“Transverse” region as defined by the leading “charged particle jet”
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 correlated systematic uncertainties.
PYTHIA Tune A was tuned to fit the “underlying event” in Run I!
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

26. Charged Multiplicity in Charged Particle Jets
PYTHIA predict more charged particles than the data for charged jets!
CDF Run 1 Analysis
Includes charged particles from the “underlying event”!
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

27. Charged Multiplicity in Charged Particle Jets
Includes charged particles from the “underlying event”!
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 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

28. Radial Charged Distribution in Charged Particle Jets
Charged multiplicity flow in the radial distance R in h-f space from chgjet#1 (leading charged jet) for charged particles with pT > 0.5 GeV and |h| < 1 when PT(chgjet#1) > 5 and 30 GeV. The points are <Nchg> in a 0.02 bin of R.
Charged PTsum flow in the radial distance R in h-f space from chgjet#1 (leading charged jet) for charged particles with pT > 0.5 GeV and |h| < 1 when PT(chgjet#1) > 5 and 30 GeV. The points are the scalar <PTsum> in a 0.02 bin of R.
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

29. Run 1 Fragmentation Function
CDF Run 1 Analysis
Includes charged particles from the “underlying event”!
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

30. Run 1 Fragmentation Function
PYTHIA does not agree at high z!
CDF Run 1 Analysis
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

31. Run 1 Fragmentation Function
PYTHIA does not agree at high z!
CDF Run 1 Analysis
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

32. The “Transverse” Regions as defined by the Leading Jet
Charged Particle Df Correlations pT > 0.5 GeV/c |h| < 1
Look at the charged particle density in the “transverse” region!
“Transverse” region is very sensitive to the “underlying event”!
CDF Run 2 Analysis
Look at charged particle correlations in the azimuthal angle Df relative to the leading calorimeter jet (JetClu R = 0.7, |h| < 2).
Define |Df| < 60o as “Toward”, 60o < -Df < 120o and 60o < Df < 120o as “Transverse 1” and “Transverse 2”, and |Df| > 120o as “Away”. Each of the two “transverse” regions have area DhDf = 2x60o = 4p/6. The overall “transverse” region is the sum of the two transverse regions (DhDf = 2x120o = 4p/3).
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

33. Charged Particle Density Df Dependence
Refer to this as a “Leading Jet” event
Subset
Refer to this as a
“Back-to-Back” event
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” (Df12 > 150o) with almost equal transverse energies (ET(jet#2)/ET(jet#1) > 0.8) and with ET(jet#3) < 15 GeV.
Shows the Df dependence of the charged particle density, dNchg/dhdf, 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

34. “Transverse” Charge Density PYTHIA Tune A vs HERWIG
“Leading Jet”
“Back-to-Back”
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/dhdf, 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

35. 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!
PYTHIA produces too many particle in the “away-side” jet!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

36. “Transverse” PTsum Density PYTHIA Tune A vs HERWIG
“Leading Jet”
“Back-to-Back”
Now look in detail at “back-to-back” events in the region 30 < ET(jet#1) < 70 GeV!
Shows the average charged PTsum density, dPTsum/dhdf, 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

37. Charged PTsum Density PYTHIA Tune A vs HERWIG
HERWIG (without multiple parton interactions) does not produces enough PTsum in the “transverse” region for 30 < ET(jet#1) < 70 GeV!
PYTHIA produces too many particle in the “away-side” jet!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

38. Rick Field – Florida/CDF
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

39. Jet Corrections & Extrapolations
Calorimeter Level Jets → Hadron Level Jets:
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!
Hadron ← Parton
I do not believe we should extrapolate
the data to the parton level! We should
publish what we measure (i.e. hadron level
with the “underlying event”)!
To compare with theory we should
“extrapolate” the parton level to the
hadron level (i.e. add hadronization and
the “underlying event” to the parton level)!
PYTHIA, HERWIG,
Particle Level Jets (with the “underlying event” removed):
Do we want to make further model dependent corrections?
Do we want to try and subtract the “underlying event” from the observed “particle level” jets.
This cannot really be done, but if you trust the Monte-Carlo modeling of the “underlying event” you can do it by using the Monte-Carlo models (use PYTHIA Tune A).
This is no longer an observable, it is a model dependent extrapolation!
Useless without a model of hadronization!
Hadron Level Jets → Parton Level Jets:
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?
This also cannot really be done, but again if you trust the Monte-Carlo models you can try and do it by using the Monte-Carlo models (use PYTHIA Tune A) including ISR and FSR.
Cannot extrapolate the data to fixed order NLO!
Next-to-leading order parton level calculation
0, 1, 2, or 3 partons!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

40. Good and Bad Algorithms
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).
Infrared Safety (Parton Level) Soft parton emission changes jet multiplicity
below threshold
(no jets)
above threshold
(1 jet)
Collinear Safety (Parton Level)
If you hadronize the parton level and add the “underlying event” (i.e. PYTHIA, HERWIG, 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

41. Towers not included in a jet (i.e. “dark towers”)!
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

42. Rick Field – Florida/CDF
KT Algorithm
kT Algorithm:
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!
KT Algorithm
Will the KT algorithm be effective in the collider environment where there is an “underlying event”?
Raw Jet ET = 533 GeV
Raw Jet ET = 618 GeV
CDF Run 2
Only towers with ET > 0.5 GeV are shown
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF

43. 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

44. 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

45. Hadronization and “Underlying Event” Corrections
Note that DØ does not make any
corrections for hadronization
or the “underlying event”!?
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!
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

46. Summary and Conclusions
Neither HERWIG or PYTHIA describe precisely the distribution charged particles in quark and gluon jets at the Tevatron!
Charged Particle kT Distribution in Jets
Shape Comparison Only
Was this measured in Run 1?
To learn about the fragmentation function at large z we should compare the inclusive “jet” cross-section to the inclusive charged particle cross section!
We have events with 600 GeV “jets” so we must have events with 300 GeV/c charged particles!
In 1 fb-1 we have thousands of charged tracks with pT > 100 GeV/c!
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!
I wish I could show you the following:
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.
Sergo is “blessing” this today in the QCD group!
Lecture 1: University of Chicago July 7, 2006
Rick Field – Florida/CDF