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

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

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

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

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

Hadron-Hadron Collisions FF1 1977 (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

Quark-Quark Black-Box Model No gluons! FF1 1977 (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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 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

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

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 = 0.37 0.14 0.05 0.02 0.007 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

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

“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

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

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 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

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

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

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

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

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

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

“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

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

“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

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

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

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, MC@NLO 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

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, 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

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

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

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

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

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

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