The Underlying Event in Hard Scattering Processes The

  • Slides: 44
Download presentation
The Underlying Event in Hard Scattering Processes The Underlying Event: beam-beam remnants initial-state radiation

The Underlying Event in Hard Scattering Processes The Underlying Event: beam-beam remnants initial-state radiation multiple-parton interactions Æ 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. Æ There are two CDF analyses which quantitatively study the underlying event and compare with the QCD Monte-Carlo models. Æ 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 QFL+Cones Valeria Tano Eve Kovacs Joey Huston Anwar Bhatti CDF WYSIWYG+Df Rick Field David Stuart Rich Haas Ph. D. Thesis Different but related problem! Les Houches 2001 Rick Field - Florida/CDF 1

Beam-Beam Remnants Æ The underlying event in a hard scattering process has a “hard”

Beam-Beam Remnants Æ 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). Æ However the “soft” component is color connected to the “hard” component so this separation is (at best) an approximation. Min-Bias? Æ 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>. Æ 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). Les Houches 2001 Rick Field - Florida/CDF 2

Multiple Parton Interactions Æ PYTHIA models the “soft” component of the underlying event with

Multiple Parton Interactions Æ 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”. Æ 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. Æ 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). Æ One can adjust the color connections and flavor of the MPI (singlet or nearest neighbor, q-qbar or glue-glue). Æ Also, one can adjust how the probability of a MPI depends on PT(hard) (single or double Gaussian matter distribution). Les Houches 2001 Rick Field - Florida/CDF 3

WYSIWYG: Comparing Data with QCD Monte-Carlo Models Charged Particle Data Select “clean” region Æ

WYSIWYG: Comparing Data with QCD Monte-Carlo Models Charged Particle Data Select “clean” region Æ Æ Æ WYSIWYG What you see is what you get. Almost! Make efficiency corrections Look only at the charged particles measured by the CTC. Zero or one vertex |zc-zv| < 2 cm, |CTC d 0| < 1 cm Require PT > 0. 5 Ge. V, |h| < 1 Assume a uniform track finding efficiency of 92% Errors include both statistical and correlated systematic uncertainties Æ Require PT > 0. 5 Ge. V, |h| < 1 Æ Make an 8% correction for the compare Uncorrected data Les Houches 2001 QCD Monte-Carlo Æ track finding efficiency Errors (statistical plus systematic) of around 5% Corrected theory Rick Field - Florida/CDF Small Corrections! 4

Charged Particle Df Correlations Æ Look at charged particle correlations in the azimuthal angle

Charged Particle Df Correlations Æ Look at charged particle correlations in the azimuthal angle Df relative to the leading charged Æ Æ particle jet. Define |Df| < 60 o as “Toward”, 60 o < |Df| < 120 o as “Transverse”, and |Df| > 120 o as “Away”. All three regions have the same size in h-f space, Dhx. Df = 2 x 120 o = 4 p/3. Les Houches 2001 Rick Field - Florida/CDF 5

Charged Multiplicity versus PT(chgjet#1) Underlying Event “plateau” Æ Data on the average number of

Charged Multiplicity versus PT(chgjet#1) Underlying Event “plateau” Æ Data on the average number of “toward” (|Df|<60 o), “transverse” (60<|Df|<120 o), and “away” (|Df|>120 o) charged particles (PT > 0. 5 Ge. V, |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 Ge. V bin. The solid (open) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 6

Shape of an Average Event with PT(chgjet#1) = 20 Ge. V/c Includes Jet#1 Underlying

Shape of an Average Event with PT(chgjet#1) = 20 Ge. V/c Includes Jet#1 Underlying event “plateau” Remember |h| < 1 PT > 0. 5 Ge. V Shape in Nchg Les Houches 2001 Rick Field - Florida/CDF 7

“Height” of the Underlying Event “Plateau” Implies 1. 09*3(2. 4)/2 = 3. 9 charged

“Height” of the Underlying Event “Plateau” Implies 1. 09*3(2. 4)/2 = 3. 9 charged particles per unit h with PT > 0. 5 Ge. V/c. Hard 4 per unit h Les Houches 2001 Soft Implies 2. 3*3. 9 = 9 charged particles per unit h with PT > 0 Ge. V/c which is a factor of 2 larger than “soft” collisions. Rick Field - Florida/CDF 8

“Transverse” PT Distribution Æ Plot shows the PT distribution of Æ the “Transverse” <Nchg>,

“Transverse” PT Distribution Æ Plot shows the PT distribution of Æ the “Transverse” <Nchg>, d. Nchg/d. PT. The integral of d. Nchg/d. PT is the “Transverse” <Nchg>. The triangle and circle (square) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 9

“Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2. 3

“Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2. 3 PT(charged jet#1) > 5 Ge. V/c “Transverse” <Nchg> = 2. 2 Æ Comparison of the “transverse” <Nchg> versus PT(charged jet#1) with the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT. The integral of d. Nchg/d. PT is the “transverse” <Nchg>. Shows how the “transverse” <Nchg> is distributed in PT. Les Houches 2001 Rick Field - Florida/CDF 10

“Max/Min Transverse” Nchg versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2

“Max/Min Transverse” Nchg versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2 p/3 “Trans. MAX” “Trans. MIN” Æ Define “Trans. MAX” and “Trans. MIN” to be the maximum and minimum of the region Æ 60 o<Df<120 o (60 o<-Df<120 o) on an event by event basis. The overall “transverse” region is the sum of “Trans. MAX” and “Trans. MIN”. The plot shows the average “Trans. MAX” Nchg and “Trans. MIN” Nchg versus PT(charged jet#1). The solid (open) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 11

“Trans. SUM/DIF” Nchg versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2

“Trans. SUM/DIF” Nchg versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2 p/3 “Trans. SUM” “Trans. DIF” Æ Define “Trans. MAX” and “Trans. MIN” to be the maximum and minimum of the region Æ 60 o<Df<120 o (60 o<-Df<120 o) on an event by event basis. The plot shows the average sum and difference of the “Trans. MAX” Nchg and the “Trans. MIN” Nchg versus PT(charged jet#1). The overall “transverse” region is the sum of “Trans. MAX” and “Trans. MIN”. The solid (open) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 12

“Max/Min Transverse” PTsum versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2

“Max/Min Transverse” PTsum versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2 p/3 “Trans. MAX” “Trans. MIN” Æ Define “Trans. MAX” and “Trans. MIN” to be the maximum and minimum of the region Æ 60 o<Df<120 o (60 o<-Df<120 o) on an event by event basis. The overall “transverse” region is the sum of “Trans. MAX” and “Trans. MIN”. The plot shows the average “Trans. MAX” PTsum and “Trans. MIN” PTsum versus PT(charged jet#1). . The solid (open) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 13

“Trans. SUM/DIF” PTsum versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2

“Trans. SUM/DIF” PTsum versus PT(chgjet#1) Area Dh. Df 2 x 60 o = 2 p/3 “Trans. SUM” “Trans. DIF” Æ Define “Trans. MAX” and “Trans. MIN” to be the maximum and minimum of the region Æ 60 o<Df<120 o (60 o<-Df<120 o) on an event by event basis. The plot shows the average sum and difference of the “Trans. MAX” PTsum and the “Trans. MIN” PTsum versus PT(charged jet#1). The overall “transverse” region is the sum of “Trans. MAX” and “Trans. MIN”. The solid (open) points are the Min-Bias (JET 20) data. The errors on the (uncorrected) data include both statistical and correlated systematic uncertainties. Les Houches 2001 Rick Field - Florida/CDF 14

QFL: Comparing Data with QCD Monte-Carlo Models Charged Particle And Calorimeter Data Select region

QFL: Comparing Data with QCD Monte-Carlo Models Charged Particle And Calorimeter Data Select region QCD Look only at both the Monte-Carlo charged particles measured by the CTC and the calorimeter data. Tano-Kovacs-Huston-Bhatti QFL detector simulation Æ Calorimeter: tower threshold = 50 Æ Me. V, Etot < 1800 Ge. V, |hlj| < 0. 7, |zvtx| < 60 cm, 1 and only 1 class 10, 11, or 12 vertex Tracks: |zc-zv| < 5 cm, |CTC d 0| < 0. 5 cm, PT > 0. 4 Ge. V, |h| < 1, correct for track finding efficiency Les Houches 2001 compare Æ Rick Field - Florida/CDF Require PT > 0. 4 Ge. V, |h| < 1 15

“Transverse” Cones Transverse Cone: p(0. 7)2=0. 49 p Tano-Kovacs-Huston-Bhatti 1. 36 Transverse Region: 2

“Transverse” Cones Transverse Cone: p(0. 7)2=0. 49 p Tano-Kovacs-Huston-Bhatti 1. 36 Transverse Region: 2 p/3=0. 67 p Æ 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| = 90 o. Æ Plot the cone with the maximum and minimum PTsum versus the ET of the leading (calorimeter) jet. . Les Houches 2001 Rick Field - Florida/CDF 16

Transverse Regions vs Transverse Cones Field-Stuart-Haas 2. 9 Ge. V/c 2. 1 Ge. V/c

Transverse Regions vs Transverse Cones Field-Stuart-Haas 2. 9 Ge. V/c 2. 1 Ge. V/c 0. 5 Ge. V/c 0. 4 Ge. V/c 0 < PT(chgjet#1) < 50 Ge. V/c Æ Multiply by ratio of the areas: Max=(2. 1 Ge. V/c)(1. 36) = 2. 9 Ge. V/c Min=(0. 4 Ge. V/c)(1. 36) = 0. 5 Ge. V/c. Æ This comparison is only qualitative! 50 < ET(jet#1) < 300 Ge. V/c Tano-Kovacs-Huston-Bhatti Can study the “underlying event” over a wide range! Les Houches 2001 Rick Field - Florida/CDF 17

“Transverse” Nchg versus PT(chgjet#1) Isajet 7. 32 Pythia 6. 115 Herwig 5. 9 Æ

“Transverse” Nchg versus PT(chgjet#1) Isajet 7. 32 Pythia 6. 115 Herwig 5. 9 Æ Plot shows the “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ scattering predictions of HERWIG 5. 9, ISAJET 7. 32, and PYTHIA 6. 115 (default parameters with PT(hard)>3 Ge. V/c). Only charged particles with |h| < 1 and PT > 0. 5 Ge. V are included and the QCD Monte. Carlo predictions have been corrected for efficiency. Les Houches 2001 Rick Field - Florida/CDF 18

“Transverse” PTsum versus PT(chgjet#1) Isajet 7. 32 Pythia 6. 115 Herwig 5. 9 Æ

“Transverse” PTsum versus PT(chgjet#1) Isajet 7. 32 Pythia 6. 115 Herwig 5. 9 Æ Plot shows the “transverse” <PTsum> versus PT(chgjet#1) compared to the QCD Æ hard scattering predictions of HERWIG 5. 9, ISAJET 7. 32, and PYTHIA 6. 115 (default parameters with PT(hard)>3 Ge. V/c). Only charged particles with |h| < 1 and PT > 0. 5 Ge. V are included and the QCD Monte. Carlo predictions have been corrected for efficiency. Les Houches 2001 Rick Field - Florida/CDF 19

ISAJET: “Transverse” Nchg versus PT(chgjet#1) ISAJET Initial-State Radiation Beam-Beam Remnants Outgoing Jets Æ Plot

ISAJET: “Transverse” Nchg versus PT(chgjet#1) ISAJET Initial-State Radiation Beam-Beam Remnants Outgoing Jets Æ Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard Æ scattering predictions of ISAJET 7. 32 (default parameters with PT(hard)>3 Ge. V/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. Les Houches 2001 Rick Field - Florida/CDF 20

ISAJET: “Transverse” Nchg versus PT(chgjet#1) ISAJET Outgoing Jets plus Initial & Final-State Radiation Beam-Beam

ISAJET: “Transverse” Nchg versus PT(chgjet#1) ISAJET Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants Æ Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard Æ scattering predictions of ISAJET 7. 32 (default parameters with PT(hard)>3 Ge. V/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). Les Houches 2001 Rick Field - Florida/CDF 21

HERWIG: “Transverse” Nchg versus PT(chgjet#1) HERWIG Outgoing Jets plus Initial & Final-State Radiation Beam-Beam

HERWIG: “Transverse” Nchg versus PT(chgjet#1) HERWIG Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants Æ Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard Æ scattering predictions of HERWIG 5. 9 (default parameters with PT(hard)>3 Ge. V/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). Les Houches 2001 Rick Field - Florida/CDF 22

PYTHIA: “Transverse” Nchg versus PT(chgjet#1) PYTHIA Outgoing Jets plus Initial & Final-State Radiation Beam-Beam

PYTHIA: “Transverse” Nchg versus PT(chgjet#1) PYTHIA Outgoing Jets plus Initial & Final-State Radiation Beam-Beam Remnants plus Multiple Parton Interactions Æ Plot shows the “transverse” <Nchg> vs PT(chgjet#1) compared to the QCD hard Æ scattering predictions of PYTHIA 6. 115 (default parameters with PT(hard)>3 Ge. V/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). Les Houches 2001 Rick Field - Florida/CDF 23

Hard Scattering Component: “Transverse” Nchg vs PT(chgjet#1) ISAJET PYTHIA HERWIG Æ QCD hard scattering

Hard Scattering Component: “Transverse” Nchg vs PT(chgjet#1) ISAJET PYTHIA HERWIG Æ QCD hard scattering predictions of HERWIG 5. 9, ISAJET 7. 32, and PYTHIA 6. 115. Æ Plot shows the “transverse” <Nchg> vs PT(chgjet#1) arising from the outgoing jets plus Æ 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. Les Houches 2001 Rick Field - Florida/CDF 24

ISAJET: “Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 3.

ISAJET: “Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 3. 7 PT(charged jet#1) > 5 Ge. V/c “Transverse” <Nchg> = 2. 0 Æ Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of ISAJET 7. 32 (default parameters with PT(hard) > 3 Ge. V/c). The integral of d. Nchg/d. PT is the “transverse” <Nchg>. Les Houches 2001 Rick Field - Florida/CDF 25

ISAJET: “Transverse” PT Distribution exp(-2 p. T) same Æ Data on the PT distribution

ISAJET: “Transverse” PT Distribution exp(-2 p. T) same Æ Data on the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of ISAJET 7. 32 (default parameters with PT(hard) > 3 Ge. V/c). The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Les Houches 2001 Rick Field - Florida/CDF 26

HERWIG: “Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2.

HERWIG: “Transverse” PT Distribution PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2. 2 PT(charged jet#1) > 5 Ge. V/c “Transverse” <Nchg> = 1. 7 Æ Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of HERWIG 5. 9 (default parameters with PT(hard) > 3 Ge. V/c). The integral of d. Nchg/d. PT is the “transverse” <Nchg>. Les Houches 2001 Rick Field - Florida/CDF 27

HERWIG: “Transverse” PT Distribution exp(-2 p. T) same Æ Data on the PT distribution

HERWIG: “Transverse” PT Distribution exp(-2 p. T) same Æ Data on the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of HERWIG 5. 9 (default parameters with PT(hard) > 3 Ge. V/c). The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Les Houches 2001 Rick Field - Florida/CDF 28

PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 Ge. V/c

PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2. 9 PT(charged jet#1) > 5 Ge. V/c “Transverse” <Nchg> = 2. 3 Æ Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 (default parameters with PT(hard) > 3 Ge. V/c). The integral of d. Nchg/d. PT is the “transverse” <Nchg>. Les Houches 2001 Rick Field - Florida/CDF 29

PYTHIA: Multiple Parton Interactions Pythia uses multiple parton interactions to enhace the underlying event.

PYTHIA: Multiple Parton Interactions Pythia uses multiple parton interactions to enhace the underlying event. Parameter Value MSTP(81) 0 Multiple-Parton Scattering off 1 Multiple-Parton Scattering on 1 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 turnoff PT 0=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 PT 0=PARP(82) MSTP(82) Les Houches 2001 Description Rick Field - Florida/CDF and new HERWIG ! Multiple parton interaction more likely in a hard (central) collision! Hard Core 30

PYTHIA Multiple Parton Interactions PYTHIA default parameters Parameter 6. 115 6. 125 MSTP(81) 1

PYTHIA Multiple Parton Interactions PYTHIA default parameters Parameter 6. 115 6. 125 MSTP(81) 1 1 MSTP(82) 1 1 PARP(81) 1. 4 Ge. V/c 1. 9 Ge. V/c PARP(82) 1. 55 Ge. V/c 2. 1 Ge. V/c 6. 115 6. 125 No multiple scattering Æ Plot shows “Transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ Æ Æ scattering predictions of PYTHIA with PT(hard) > 3 Ge. V. PYTHIA 6. 115: GRV 94 L, MSTP(82)=1, PTmin=PARP(81)=1. 4 Ge. V/c. PYTHIA 6. 125: GRV 94 L, MSTP(82)=1, PTmin=PARP(81)=1. 9 Ge. V/c. PYTHIA 6. 115: GRV 94 L, MSTP(81)=0, no multiple parton interactions. Les Houches 2001 Rick Field - Florida/CDF Constant Probability Scattering 31

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ Æ Æ scattering predictions of PYTHIA with PT(hard) > 0 Ge. V/c. PYTHIA 6. 115: GRV 94 L, MSTP(82)=1, PTmin=PARP(81)=1. 4 Ge. V/c. PYTHIA 6. 115: CTEQ 3 L, MSTP(82)=1, PTmin =PARP(81)=0. 9 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF Constant Probability Scattering 32

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ Æ scattering predictions of PYTHIA with PT(hard) > 0 Ge. V/c. PYTHIA 6. 115: GRV 94 L, MSTP(82)=3, PT 0=PARP(82)=1. 55 Ge. V/c. PYTHIA 6. 115: CTEQ 3 L, MSTP(82)=3, PT 0=PARP(82)=1. 35 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=3, PT 0=PARP(82)=1. 8 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF Varying Impact Parameter 33

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ

PYTHIA Multiple Parton Interactions Note: Multiple parton interactions depend sensitively on the PDF’s! Æ Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ Æ Æ scattering predictions of PYTHIA with PT(hard) > 0 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=1. 55 Ge. V/c. PYTHIA 6. 115: CTEQ 3 L, MSTP(82)=4, PT 0=PARP(82)=1. 55 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF Varying Impact Parameter Hard Core 34

Tuned PYTHIA: “Transverse” Nchg vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions!

Tuned PYTHIA: “Transverse” Nchg vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions! Æ Plot shows “transverse” <Nchg> versus PT(chgjet#1) compared to the QCD hard Æ Æ scattering predictions of PYTHIA with PT(hard) > 0 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=3, PT 0=PARP(82)=1. 8 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF Varying Impact Parameter 35

Tuned PYTHIA: “Transverse” PTsum vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions!

Tuned PYTHIA: “Transverse” PTsum vs PT(chgjet#1) Describes correctly the rise from soft-collisions to hard-collisions! Æ Plot shows “transverse” <PTsum> versus PT(chgjet#1) compared to the QCD hard Æ Æ scattering predictions of PYTHIA with PT(hard) > 0 Ge. V. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=3, PT 0=PARP(82)=1. 8 Ge. V/c. PYTHIA 6. 115: CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF Varying Impact Parameter 36

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 Ge.

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions PT(charged jet#1) > 30 Ge. V/c “Transverse” <Nchg> = 2. 7 PT(charged jet#1) > 5 Ge. V/c “Transverse” <Nchg> = 2. 3 Æ Data on the “transverse” <Nchg> versus PT(charged jet#1) and the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0 Ge. V/c, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. The integral of d. Nchg/d. PT is the “transverse” <Nchg>. Les Houches 2001 Rick Field - Florida/CDF 37

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions Æ Data on the PT

Tuned PYTHIA: “Transverse” PT Distribution Includes Multiple Parton Interactions Æ Data on the PT distribution of the “transverse” <Nchg>, d. Nchg/d. PT, compared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. The dashed curve is the beam-beam remnant component and the solid curve is the total (beam-beam remnants plus hard component). Les Houches 2001 Rick Field - Florida/CDF 38

Tuned PYTHIA: “Trans. MAX/MIN” vs PT(chgjet#1) <Nchg> <PTsum> Æ Plots shows data on the

Tuned PYTHIA: “Trans. MAX/MIN” vs PT(chgjet#1) <Nchg> <PTsum> Æ Plots shows data on the Æ “trans. MAX/MIN” <Nchg> and “trans. MAX/MIN” <PTsum> vs PT(chgjet#1). The solid (open) points are the Min-Bias (JET 20) data. The data are compared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF 39

Tuned PYTHIA: “Trans. SUM/DIF” vs PT(chgjet#1) <Nchg> <PTsum> Æ Plots shows data on the

Tuned PYTHIA: “Trans. SUM/DIF” vs PT(chgjet#1) <Nchg> <PTsum> Æ Plots shows data on the Æ “trans. SUM/DIF” <Nchg> and “trans. SUM/DIF” <PTsum> vs PT(chgjet#1). The solid (open) points are the Min-Bias (JET 20) data. The data are compared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/c. Les Houches 2001 Rick Field - Florida/CDF 40

Tuned PYTHIA: “Trans. MAX/MIN” vs PT(chgjet#1) “Trans. MAX” <Nchg> “Trans. MIN” <Nchg> Includes Multiple

Tuned PYTHIA: “Trans. MAX/MIN” vs PT(chgjet#1) “Trans. MAX” <Nchg> “Trans. MIN” <Nchg> Includes Multiple Parton Interactions Æ Data on the “trans. MAX/MIN” Nchg vs Æ PT(chgjet#1) comared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/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). Les Houches 2001 Rick Field - Florida/CDF 41

Tuned PYTHIA: “Trans. SUM/DIF” vs PT(chgjet#1) “Trans. SUM” <Nchg> “Trans. DIF” <Nchg> Includes Multiple

Tuned PYTHIA: “Trans. SUM/DIF” vs PT(chgjet#1) “Trans. SUM” <Nchg> “Trans. DIF” <Nchg> Includes Multiple Parton Interactions Æ Data on the “trans. SUM/DIF” Nchg vs Æ PT(chgjet#1) comared with the QCD Monte-Carlo predictions of PYTHIA 6. 115 with PT(hard) > 0, CTEQ 4 L, MSTP(82)=4, PT 0=PARP(82)=2. 4 Ge. V/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). Les Houches 2001 Rick Field - Florida/CDF 42

The Underlying Event: Summary & Conclusions The “Underlying Event” Æ Combining the two CDF

The Underlying Event: Summary & Conclusions The “Underlying Event” Æ Combining the two CDF analyses gives a quantitative study of the underlying event from Æ Æ 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 Ge. V/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!). Les Houches 2001 Rick Field - Florida/CDF 43

Multiple Parton Interactions: Summary & Conclusions Proton Multiple Parton Interactions Anti. Proton Hard Core

Multiple Parton Interactions: Summary & Conclusions Proton Multiple Parton Interactions Anti. Proton Hard Core Æ The increased activity in the underlying event in a hard scattering over a soft collision Æ Æ Æ 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. Slow! 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. Les Houches 2001 Rick Field - Florida/CDF 44