The Underlying Event in Hard Scattering Processes beam-beam remnants initial-state radiation multiple-parton interactions The underlying event in a hard scattering process is a complicated and not very well understood object. It is an interesting region since it probes the interface between perturbative and non-perturbative physics. There are two CDF analyses which quantitatively study the underlying event and compare with the QCD Monte-Carlo models. It is important to model this region well since it is an unavoidable background to all collider observables. Also, we need a good model of min-bias (zero-bias) collisions. CDF WYSIWYG+Df Rick Field David Stuart Rich Haas CDF QFL+Cones Valeria Tano Eve Kovacs Joey Huston Anwar Bhatti Ph.D. Thesis Ph.D. Thesis Different but related problem! Snowmass 2001 Rick Field - Florida/CDF

Rick Field - Florida/CDF Beam-Beam Remnants The underlying event in a hard scattering process has a “hard” component (particles that arise from initial & final-state radiation and from the outgoing hard scattered partons) and a “soft” component (beam-beam remnants). However the “soft” component is color connected to the “hard” component so this separation is (at best) an approximation. Min-Bias? For ISAJET (no color flow) the “soft” and “hard” components are completely independent and the model for the beam-beam remnant component is the same as for min-bias (“cut pomeron”) but with a larger <PT>. HERWIG breaks the color connection with a soft q-qbar pair and then models the beam-beam remnant component the same as HERWIG min-bias (cluster decay). Snowmass 2001 Rick Field - Florida/CDF

MPI: Multiple Parton Interactions PYTHIA models the “soft” component of the underlying event with color string fragmentation, but in addition includes a contribution arising from multiple parton interactions (MPI) in which one interaction is hard and the other is “semi-hard”. The probability that a hard scattering events also contains a semi-hard multiple parton interaction can be varied but adjusting the cut-off for the MPI. One can also adjust whether the probability of a MPI depends on the PT of the hard scattering, PT(hard) (constant cross section or varying with impact parameter). One can adjust the color connections and flavor of the MPI (singlet or nearest neighbor, q-qbar or glue-glue). Also, one can adjust how the probability of a MPI depends on PT(hard) (single or double Gaussian matter distribution). Snowmass 2001 Rick Field - Florida/CDF

WYSIWYG: Comparing Data with QCD Monte-Carlo Models Charged Particle Data QCD Monte-Carlo WYSIWYG What you see is what you get. Almost! Select “clean” region Make efficiency corrections Look only at the charged particles measured by the CTC. Zero or one vertex |zc-zv| < 2 cm, |CTC d0| < 1 cm Require PT > 0.5 GeV, |h| < 1 Assume a uniform track finding efficiency of 92% Errors include both statistical and correlated systematic uncertainties Require PT > 0.5 GeV, |h| < 1 Make an 8% correction for the track finding efficiency Errors (statistical plus systematic) of around 5% compare Small Corrections! Uncorrected data Corrected theory Snowmass 2001 Rick Field - Florida/CDF

Define Charged Particle “Jets” as Circular Regions in h-f Space “Jets” contain particles from the underlying event in addition to particles from the outgoing partons. Order Charged Particles in PT (|h| < 1 PT > 0.5 GeV/c). Start with highest PT particle and include in the “jet” all particles (|h| < 1 PT > 0.5 GeV/c) within radius R = 0.7 (considering each particle in decreasing PT and recalculating the centroid of the jet after each new particle is added to the jet). Go to next highest PT particle (not already included in a previous jet) and include in the “jet” all particles (|h| < 1 PT > 0.5 GeV/c) within radius R = 0.7 (not already included in a previous jet). Continue until all particles are in a “jet”. Maximum number of “jets” is about 2(2)(2p)/(p(0.7)2) or 16. 6 particles 5 “jets” Snowmass 2001 Rick Field - Florida/CDF

The Evolution of Charged Jets from 0.5 GeV/c to 50 GeV/c QCD “hard” scattering predictions of Herwig 5.9, Isajet 7.32, and Pythia 6.115 JET20 data connects on smoothly to the Min-Bias data Local Jet Observable Compares data on the average number of charged particles within charged Jet#1 (leading jet, R = 0.7) with the QCD hard scattering predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA 6.115 (default parameters with PT(hard)>3 GeV/c).. Only charged particles with |h| < 1 and PT > 0.5 GeV/c are included and the theory has been corrected for track finding efficiency. Snowmass 2001 Rick Field - Florida/CDF

Jet#1 “Size” vs PT(chgjet#1) Isajet 7.32 JET20 data connects on smoothly to the Min-Bias data Pythia 6.115 Herwig 5.9 Local Jet Observable Compares data on the average radius containing 80% of the particles and 80% of the PT of chgjet#1 (leading jet) with the QCD hard scattering predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA 6.115 (default parameters with PT(hard)>3 GeV/c). Only charged particles with |h| < 1 and PT > 0.5 GeV/c are included and the theory has been corrected for track finding efficiency. Snowmass 2001 Rick Field - Florida/CDF

Charged Particle Df Correlations 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. Snowmass 2001 Rick Field - Florida/CDF

Charged Multiplicity versus PT(chgjet#1) Underlying Event “plateau” Data on the average number of “toward” (|Df|<60o), “transverse” (60<|Df|<120o), and “away” (|Df|>120o) charged particles (PT > 0.5 GeV, |h| < 1, including jet#1) as a function of the transverse momentum of the leading charged particle jet. Each point corresponds to the <Nchg> in a 1 GeV bin. The solid (open) points are the Min-Bias (JET20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Snowmass 2001 Rick Field - Florida/CDF

“Transverse” PT Distribution PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 2.3 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 2.2 Comparison of the “transverse” <Nchg> versus PT(charged jet#1) with the PT distribution of the “transverse” <Nchg>, dNchg/dPT. The integral of dNchg/dPT is the “transverse” <Nchg>. Shows how the “transverse” <Nchg> is distributed in PT. Snowmass 2001 Rick Field - Florida/CDF

“Max/Min Transverse” Nchg versus PT(chgjet#1) Area DhDf 2x60o = 2p/3 “TransMAX” “TransMIN” Define “TransMAX” and “TransMIN” to be the maximum and minimum of the region 60o<Df<120o (60o<-Df<120o) on an event by event basis. The overall “transverse” region is the sum of “TransMAX” and “TransMIN”. The plot shows the average “TransMAX” Nchg and “TransMIN” Nchg versus PT(charged jet#1). The solid (open) points are the Min-Bias (JET20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Snowmass 2001 Rick Field - Florida/CDF

QFL: Comparing Data with QCD Monte-Carlo Models Charged Particle And Calorimeter Data QCD Monte-Carlo Look only at both the charged particles measured by the CTC and the calorimeter data. QFL detector simulation Select region Tano-Kovacs-Huston-Bhatti Calorimeter: tower threshold = 50 MeV, Etot < 1800 GeV, |hlj| < 0.7, |zvtx| < 60 cm, 1 and only 1 class 10, 11, or 12 vertex Tracks: |zc-zv| < 5 cm, |CTC d0| < 0.5 cm, PT > 0.4 GeV, |h| < 1, correct for track finding efficiency compare Require PT > 0.4 GeV, |h| < 1 Snowmass 2001 Rick Field - Florida/CDF

Tano-Kovacs-Huston-Bhatti “Transverse” Cones Tano-Kovacs-Huston-Bhatti Transverse Cone: p(0.7)2=0.49p 1.36 Transverse Region: 2p/3=0.67p Sum the PT of charged particles (or the energy) in two cones of radius 0.7 at the same h as the leading jet but with |DF| = 90o. Plot the cone with the maximum and minimum PTsum versus the ET of the leading (calorimeter) jet.. Snowmass 2001 Rick Field - Florida/CDF

Transverse Regions vs Transverse Cones Field-Stuart-Haas 2.9 GeV/c 2.1 GeV/c 0.5 GeV/c 0 < PT(chgjet#1) < 50 GeV/c 0.4 GeV/c Multiply by ratio of the areas: Max=(2.1 GeV/c)(1.36) = 2.9 GeV/c Min=(0.4 GeV/c)(1.36) = 0.5 GeV/c. This comparison is only qualitative! 50 < ET(jet#1) < 300 GeV/c Tano-Kovacs-Huston-Bhatti Can study the “underlying event” over a wide range! Snowmass 2001 Rick Field - Florida/CDF

“Transverse” Nchg versus PT(chgjet#1) Isajet 7.32 Pythia 6.115 Herwig 5.9 Plot shows the “transverse” <Nchg> versus PT(chgjet#1) compared to the the QCD hard scattering predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA 6.115 (default parameters with PT(hard)>3 GeV/c). Only charged particles with |h| < 1 and PT > 0.5 GeV are included and the QCD Monte-Carlo predictions have been corrected for efficiency. Snowmass 2001 Rick Field - Florida/CDF

“Transverse” PTsum versus PT(chgjet#1) Isajet 7.32 Pythia 6.115 Herwig 5.9 Plot shows the “transverse” <PTsum> versus PT(chgjet#1) compared to the the QCD hard scattering predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA 6.115 (default parameters with PT(hard)>3 GeV/c). Only charged particles with |h| < 1 and PT > 0.5 GeV are included and the QCD Monte-Carlo predictions have been corrected for efficiency. Snowmass 2001 Rick Field - Florida/CDF

ISAJET: “Transverse” Nchg versus PT(chgjet#1) Initial-State Radiation Beam-Beam Remnants Outgoing Jets Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard scattering predictions of ISAJET 7.32 (default parameters with PT(hard)>3 GeV/c) . The predictions of ISAJET are divided into three categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants), charged particles that arise from initial-state radiation, and charged particles that result from the outgoing jets plus final-state radiation. Snowmass 2001 Rick Field - Florida/CDF

ISAJET: “Transverse” Nchg versus PT(chgjet#1) Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard scattering predictions of ISAJET 7.32 (default parameters with PT(hard)>3 GeV/c) . The predictions of ISAJET are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants); and charged particles that arise from the outgoing jet plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

HERWIG: “Transverse” Nchg versus PT(chgjet#1) Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard scattering predictions of HERWIG 5.9 (default parameters with PT(hard)>3 GeV/c). The predictions of HERWIG are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants); and charged particles that arise from the outgoing jet plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

PYTHIA: “Transverse” Nchg versus PT(chgjet#1) Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants plus Multiple Parton Interactions Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA 6.115 (default parameters with PT(hard)>3 GeV/c). The predictions of PYTHIA are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants including multiple parton interactions); and charged particles that arise from the outgoing jet plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

Hard Scattering Component: “Transverse” Nchg vs PT(chgjet#1) ISAJET PYTHIA HERWIG QCD hard scattering predictions of HERWIG 5.9, ISAJET 7.32, and PYTHIA 6.115. Plot shows the “transverse” <Nchg> vs PT(chgjet#1) arising from the outgoing jets plus initial and finial-state radiation (hard scattering component). HERWIG and PYTHIA modify the leading-log picture to include “color coherence effects” which leads to “angle ordering” within the parton shower. Angle ordering produces less high PT radiation within a parton shower. Snowmass 2001 Rick Field - Florida/CDF

ISAJET: “Transverse” PT Distribution PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 3.7 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 2.0 Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of ISAJET 7.32 (default parameters with with PT(hard) > 3 GeV/c). The integral of dNchg/dPT is the “transverse” <Nchg>. Snowmass 2001 Rick Field - Florida/CDF

ISAJET: “Transverse” PT Distribution exp(-2pT) same Data on the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of ISAJET 7.32 (default parameters with with PT(hard) > 3 GeV/c). The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Snowmass 2001 Rick Field - Florida/CDF

Tuned ISAJET: “Transverse” PT Distribution PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 3.2 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 2.1 Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of Tuned ISAJET 7.32 (PT(hard) > 3 GeV/c, CUTJET = 12 GeV, e-2PT beam-beam remnants). The integral of dNchg/dPT is the “transverse” <Nchg>. Default = 6 GeV Snowmass 2001 Rick Field - Florida/CDF

Tuned ISAJET: “Transverse” PT Distribution exp(-2pT) Data on the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of Tuned ISAJET 7.32 (PT(hard) > 3 GeV/c, CUTJET = 12 GeV, e-2PT beam-beam remnants). The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Snowmass 2001 Rick Field - Florida/CDF

Tuned ISAJET: “Transverse” Nchg and PTsum vs PT(chgjet#1) “Transverse” <PTsum> Data on the “transverse” Nchg and PTsum vs PT(chgjet#1) compared with the QCD Monte-Carlo predictions of ISAJET 7.32 (with PT(hard) > 3 GeV/c). Tuned ISAJET has CUTJET = 12 GeV (default = 6 GeV) and e-2PT beam-beam remnants (default is 1/(PT2+PT02)4). Snowmass 2001 Rick Field - Florida/CDF

HERWIG: “Transverse” PT Distribution PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 2.2 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 1.7 Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of HERWIG 5.9 (default parameters with with PT(hard) > 3 GeV/c). The integral of dNchg/dPT is the “transverse” <Nchg>. Snowmass 2001 Rick Field - Florida/CDF

HERWIG: “Transverse” PT Distribution exp(-2pT) same Data on the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of HERWIG 5.9 (default parameters with with PT(hard) > 3 GeV/c). The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Snowmass 2001 Rick Field - Florida/CDF

HERWIG: “TransMAX/MIN” vs PT(chgjet#1) “TransMAX” <Nchg> “TransMIN” <Nchg> Data on the “transMAX/MIN” Nchg vs PT(chgjet#1) compared with the QCD Monte-Carlo predictions of HERWIG 5.9 (default parameters with PT(hard) > 3 GeV/c). The predictions of HERWIG are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants); and charged particles that arise from the outgoing jets plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

HERWIG: “TransMAX/MIN” vs PT(chgjet#1) <Nchg> <PTsum> Plots shows data on the “transMAX/MIN” <Nchg> and “transMAX/MIN” <PTsum> vs PT(chgjet#1). The solid (open) points are the Min-Bias (JET20) data. The data are compared with the QCD Monte-Carlo predictions of HERWIG 5.9 (default parameters with PT(hard) > 3 GeV/c). Snowmass 2001 Rick Field - Florida/CDF

PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 2.9 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 2.3 Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of PYTHIA 6.115 (default parameters with with PT(hard) > 3 GeV/c). The integral of dNchg/dPT is the “transverse” <Nchg>. Snowmass 2001 Rick Field - Florida/CDF

PYTHIA: Multiple Parton Interactions Pythia uses multiple parton interactions to enhace the underlying event. and new HERWIG! Multiple parton interaction more likely in a hard (central) collision! Parameter Value Description MSTP(81) Multiple-Parton Scattering off 1 Multiple-Parton Scattering on MSTP(82) Multiple interactions assuming the same probability, with an abrupt cut-off PTmin=PARP(81) 3 Multiple interactions assuming a varying impact parameter and a hadronic matter overlap consistent with a single Gaussian matter distribution, with a smooth turn-off PT0=PARP(82) 4 Multiple interactions assuming a varying impact parameter and a hadronic matter overlap consistent with a double Gaussian matter distribution (governed by PARP(83) and PARP(84)), with a smooth turn-off PT0=PARP(82) Hard Core Snowmass 2001 Rick Field - Florida/CDF

PYTHIA Multiple Parton Interactions PYTHIA default parameters Parameter 6.115 6.125 MSTP(81) 1 MSTP(82) PARP(81) 1.4 GeV/c 1.9 GeV/c PARP(82) 1.55 GeV/c 2.1 GeV/c 6.115 6.125 No multiple scattering Plot shows “Transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 3 GeV. PYTHIA 6.115: GRV94L, MSTP(82)=1, PTmin=PARP(81)=1.4 GeV/c. PYTHIA 6.125: GRV94L, MSTP(82)=1, PTmin=PARP(81)=1.9 GeV/c. PYTHIA 6.115: GRV94L, MSTP(81)=0, no multiple parton interactions. Constant Probability Scattering Snowmass 2001 Rick Field - Florida/CDF

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 0 GeV/c. PYTHIA 6.115: GRV94L, MSTP(82)=1, PTmin=PARP(81)=1.4 GeV/c. PYTHIA 6.115: CTEQ3L, MSTP(82)=1, PTmin =PARP(81)=1.4 GeV/c. PYTHIA 6.115: CTEQ3L, MSTP(82)=1, PTmin =PARP(81)=0.9 GeV/c. Constant Probability Scattering Snowmass 2001 Rick Field - Florida/CDF

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 0 GeV/c. PYTHIA 6.115: GRV94L, MSTP(82)=3, PT0=PARP(82)=1.55 GeV/c. PYTHIA 6.115: CTEQ3L, MSTP(82)=3, PT0=PARP(82)=1.55 GeV/c. PYTHIA 6.115: CTEQ3L, MSTP(82)=3, PT0=PARP(82)=1.35 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=3, PT0=PARP(82)=1.8 GeV/c. Varying Impact Parameter Snowmass 2001 Rick Field - Florida/CDF

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 0 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=4, PT0=PARP(82)=1.55 GeV/c. PYTHIA 6.115: CTEQ3L, MSTP(82)=4, PT0=PARP(82)=1.55 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. Varying Impact Parameter Hard Core Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “Transverse” Nchg vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions! Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 0 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=3, PT0=PARP(82)=1.8 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. Varying Impact Parameter Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “Transverse” PTsum vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions! Plot shows “transverse” <PTsum> versus PT(chgjet#1) compared to the QCD hard scattering predictions of PYTHIA with PT(hard) > 0 GeV. PYTHIA 6.115: CTEQ4L, MSTP(82)=3, PT0=PARP(82)=1.8 GeV/c. PYTHIA 6.115: CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. Varying Impact Parameter Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 GeV/c “Transverse” <Nchg> = 2.7 PT(charged jet#1) > 5 GeV/c “Transverse” <Nchg> = 2.3 Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0 GeV/c, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. The integral of dNchg/dPT is the “transverse” <Nchg>. Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions Data on the PT distribution of the “transverse” <Nchg>, dNchg/dPT, compared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “TransMAX/MIN” vs PT(chgjet#1) <Nchg> <PTsum> Plots shows data on the “transMAX/MIN” <Nchg> and “transMAX/MIN” <PTsum> vs PT(chgjet#1). The solid (open) points are the Min-Bias (JET20) data. The data are compared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “TransSUM/DIF” vs PT(chgjet#1) <Nchg> <PTsum> Plots shows data on the “transSUM/DIF” <Nchg> and “transSUM/DIF” <PTsum> vs PT(chgjet#1). The solid (open) points are the Min-Bias (JET20) data. The data are compared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “TransMAX/MIN” vs PT(chgjet#1) “TransMAX” <Nchg> “TransMIN” <Nchg> Includes Multiple Parton Interactions Data on the “transMAX/MIN” Nchg vs PT(chgjet#1) comared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. The predictions of PYTHIA are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants); and charged particles that arise from the outgoing jets plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

Tuned PYTHIA: “TransSUM/DIF” vs PT(chgjet#1) “TransSUM” <Nchg> “TransDIF” <Nchg> Includes Multiple Parton Interactions Data on the “transSUM/DIF” Nchg vs PT(chgjet#1) comared with the QCD Monte-Carlo predictions of PYTHIA 6.115 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c. The predictions of PYTHIA are divided into two categories: charged particles that arise from the break-up of the beam and target (beam-beam remnants); and charged particles that arise from the outgoing jet plus initial and final-state radiation (hard scattering component). Snowmass 2001 Rick Field - Florida/CDF

The Underlying Event: Summary & Conclusions Combining the two CDF analyses gives a quantitative study of the underlying event from very soft collisions to very hard collisions. ISAJET (with independent fragmentation) produces too many (soft) particles in the underlying event with the wrong dependence on PT(jet#1). HERWIG and PYTHIA modify the leading-log picture to include “color coherence effects” which leads to “angle ordering” within the parton shower and do a better job describing the underlying event. Both ISAJET and HERWIG have the too steep of a PT dependence of the beam-beam remnant component of the underlying event and hence do not have enough beam-beam remnants with PT > 0.5 GeV/c. PYTHIA (with multiple parton interactions) does the best job in describing the underlying event. Perhaps the multiple parton interaction approach is correct or maybe we simply need to improve the way the Monte-Carlo models handle the beam-beam remnants (or both!). Snowmass 2001 Rick Field - Florida/CDF

Multiple Parton Interactions: Summary & Conclusions Proton AntiProton Hard Core Hard Core The increased activity in the underlying event in a hard scattering over a soft collision cannot be explained by initial-state radiation. Multiple parton interactions gives a natural way of explaining the increased activity in the underlying event in a hard scattering. A hard scattering is more likely to occur when the hard cores overlap and this is also when the probability of a multiple parton interaction is greatest. For a soft grazing collision the probability of a multiple parton interaction is small. PYTHIA (with varying impact parameter) describes the underlying event data fairly well. However, there are problems in fitting min-bias events with this approach. Multiple parton interactions are very sensitive to the parton structure functions. You must first decide on a particular PDF and then tune the multiple parton interactions to fit the data. Slow! Snowmass 2001 Rick Field - Florida/CDF