1. 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

2. 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

3. 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

4. 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

5. 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

6. 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 (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

7. 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 (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

8. 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

9. 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

10. “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

11. “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

12. 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

13. 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

14. 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

15. “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 (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

16. “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 (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

17. 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

18. 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

19. 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

20. 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 (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

21. 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
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

22. 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

23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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

31. 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 (default parameters with with PT(hard) > 3 GeV/c). The integral of dNchg/dPT is the “transverse” <Nchg>.
Snowmass 2001
Rick Field - Florida/CDF

32. 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

33. 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

34. 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

35. 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

36. 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

37. 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

38. 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

39. 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 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

40. 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 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

41. 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 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c.
Snowmass 2001
Rick Field - Florida/CDF

42. 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 with PT(hard) > 0, CTEQ4L, MSTP(82)=4, PT0=PARP(82)=2.4 GeV/c.
Snowmass 2001
Rick Field - Florida/CDF

43. 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 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

44. 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 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

45. 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

46. 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