[PPT] - Low-energy QCD at the high-energy frontier Andy Buckley University PowerPoint Presentation

SLIDE 1

Low-energy QCD at the high-energy frontier

Andy Buckley

University of Edinburgh

Higgs-Maxwell Particle Physics Workshop, RSE, 2011-02-09

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SLIDE 2

Soft QCD at a hard collider

◮ The LHC is the highest-energy

particle collider ever made – built to directly produce new particles at the TeV scale.

◮ But the dominant interactions are still

verwhelmingly soft!

◮ Usually dismiss this stuff as “just min

bias” – but that means it’s collective QCD interactions of whole nucleon

systems. A theory nightmare!

◮ In these early days of running we

want to understand it as well as we can: as a background and for pure interest.

[GeV]

jet T

p 100 200 300 400 500 ]

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dt=1 nb L

∫

Data PYTHIA ATLAS Preliminary = 7 TeV s jets R=0.6

t

anti-k |<2.8

jet

y >30 GeV |

jet T

p

This talk will be ATLAS-dominated: sorry! But it’s not all that unfair.

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SLIDE 3

Multiple parton interactions (MPI)

Number of parton interactions connected to the ratio of parton–parton cross-sections ˆ σ and total p–p cross-section, σ. QCD total cross-section evolves with √s, e.g. 1992 Donnachie–Landshoff parameterisation, from S-matrix analyticity: σpp

tot(s) 21.7 mb · (s/GeV2) 0.0808 → σtot(14 TeV) = 101–164 mb

New ATLAS measurement of σinel evolution to 7 TeV:

[GeV] s 1 10

2

10

3

10

4

10 [mb]

inel

σ 20 40 60 80 100

strand

Schuler and Sj
5

> 10 ξ strand:

Schuler and Sj

Block 2010

5

> 10 ξ = 7 TeV: s Data 2010 /s

2 p

> m ξ = 7 TeV: extrap. to s Data 2010 pp Data Data p p

/s unless specified otherwise

2 p

> m ξ Theoretical predictions and data are shown for ξ /d σ ATLAS data extrapolated using Pythia prediction for d

Preliminary ATLAS

3/27

SLIDE 4

Minimum bias vs. “underlying event”

Soft QCD is interesting because it’s not just a single-parton interaction: instead we have multiple, correlated interactions. Correlations are non-perturbatively generated. Minimum bias is purely soft MPI; underlying event (UE) is soft QCD in the presence of a hard scattering, such as hard QCD, EW boson

production. . . or Higgs production/new physics! UE = “partial bias”.

There is no sharp distinction. TeV-scale new physics searches are mostly designed to be pretty insensitive to soft QCD, but it’s still important to describe the QCD structure of the events as well as possible. UE could be important for e.g. analyses based on jet-structure.

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SLIDE 5

MC models of soft QCD

UE/MB models in MC generators are based on several things:

◮ Multiple parton interactions (in an eikonal approximation

formalism)

◮ Regularised cross-section (gg → 2 QCD naïvely diverges for low

pT, in both cross-section and PDF)

◮ Hadronic transverse matter distribution ◮ (Colour topology rearrangement between all scattered partons) ◮ Black magic!

Implemented in PYTHIA, JIMMY, Herwig++, Pythia 8, Sherpa, PHOJET, EPOS, (more?) MPI models are the least predictive part of MC event generators! Lots

f non-perturbative QCD, but very dynamic so lattice/semi-analytic

methods don’t work (even if they were tractable on MC event CPU timescales) MC models are the place where theory meets experiment – close interaction.

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SLIDE 6

More MC model details

Many variations: basic PYTHIA model is the most used/familiar:

◮ Ansatz: apply a ˆ

p⊥ cutoff, ˆ p0

⊥, below which scatterings are vetoed

r their cross-sections are suppressed. PYTHIA uses special

“soft-scattering” matrix elements below the ˆ p0

⊥ cutoff. ◮ Another ansatz: assume that ˆ

p0

⊥ evolves with energy with a power

law “inspired” by the original Donnachie–Landshoff pomeron fit: ˆ p0

⊥(√s) = ˆ

p0

⊥(√s0) ·

s s0 e/2 ˆ p0

⊥(√s0) and e are user-configurable parameters. Usually set

√s0 = 1800 GeV. DL pomeron e ∼ 0.16.

◮ Finally, a configurable nucleon hadronic mass distribution in

impact parameter space. PYTHIA has several variants, the most-used being a 2-parameter double-Gaussian.

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SLIDE 7

Tuning the PYTHIA and JIMMY MPI models

Need to fit pheno parameters of asymptotic MPI models to describe

data. Model tuning is best done as the final stage of a wider tune. The

first stages constrain hadronisation (flavour + kinematics), and initial/final-state parton showers: leave as little room as possible for the MPI to exceed its mandate. ATLAS has driven tuning of the Fortran PYTHIA and HERWIG/JIMMY generators to LHC data: new set of tunes for each generator, using early ATLAS data: diffractive-reduced MB data with Nch ≥ 6, ATLAS UE (limited stats) + CDF MB & UE data. Tuning done using the Rivet analysis system to produce data at lots of points in the tuning parameter space, then parameterisation of the

bservables is done with the Professor tool to find optimal parameters.

7/27

SLIDE 8

Minimum bias and PYTHIA AMBT1

Minimum bias data from ATLAS covering quite inclusive charged particle observables using the central tracker. Mainly with a track cut

f pT > 500 MeV, but also at 100 MeV: a challenge for the models.

Various phase spaces, such as diffraction-suppressing Nch cuts.

η / d

ch

N d ⋅

ev

N 1/ 1 1.5 2 2.5 3 3.5 4 Data 2009 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 500 MeV, |

T

p 6, ≥

ch

n = 0.9 TeV s ATLAS η / d

ch

N d ⋅

ev

N 1/ 1 1.5 2 2.5 3 3.5 4 η

2.5 -2 -1.5 -1 -0.5

0.5 1 1.5 2 2.5 Ratio 0.8 1 1.2 Data Uncertainties MC / Data η

2.5 -2 -1.5 -1 -0.5

0.5 1 1.5 2 2.5 Ratio 0.8 1 1.2 η / d

ch

N d ⋅

ev

N 1/ 1.5 2 2.5 3 3.5 4 4.5 5 Data 2010 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 500 MeV, |

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p 6, ≥

ch

n = 7 TeV s ATLAS η / d

ch

N d ⋅

ev

N 1/ 1.5 2 2.5 3 3.5 4 4.5 5 η

2.5 -2 -1.5 -1 -0.5

0.5 1 1.5 2 2.5 Ratio 0.8 1 1.2 Data Uncertainties MC / Data η

2.5 -2 -1.5 -1 -0.5

0.5 1 1.5 2 2.5 Ratio 0.8 1 1.2 8/27

SLIDE 9

Minimum bias and PYTHIA AMBT1

Minimum bias data from ATLAS covering quite inclusive charged particle observables using the central tracker. Mainly with a track cut

f pT > 500 MeV, but also at 100 MeV: a challenge for the models.

Various phase spaces, such as diffraction-suppressing Nch cuts.

ch

n /d

ev

N d ⋅

ev

N 1/

6

10

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10 1 Data 2009 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 500 MeV, |

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p 6, ≥

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n = 0.9 TeV s ATLAS

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n /d

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n 10 15 20 25 30 35 40 45 Ratio 0.5 1 1.5 Data Uncertainties MC / Data

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n 10 15 20 25 30 35 40 45 Ratio 0.5 1 1.5

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n /d

ev

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ev

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10 1 Data 2010 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 500 MeV, |

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n 20 40 60 80 100 120 Ratio 0.5 1 1.5 Data Uncertainties MC / Data

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n 20 40 60 80 100 120 Ratio 0.5 1 1.5 9/27

SLIDE 10

Minimum bias and PYTHIA AMBT1

Minimum bias data from ATLAS covering quite inclusive charged particle observables using the central tracker. Mainly with a track cut

f pT > 500 MeV, but also at 100 MeV: a challenge for the models.

Various phase spaces, such as diffraction-suppressing Nch cuts.

]

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p 1 10 Ratio 0.5 1 1.5 2 10/27

SLIDE 11

Minimum bias and PYTHIA AMBT1

Minimum bias data from ATLAS covering quite inclusive charged particle observables using the central tracker. Mainly with a track cut

f pT > 500 MeV, but also at 100 MeV: a challenge for the models.

Various phase spaces, such as diffraction-suppressing Nch cuts.

[ GeV ] 〉

T

p 〈 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Data 2009 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 500 MeV, |

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p 1, ≥

ch

n = 0.9 TeV s ATLAS [ GeV ] 〉

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p 〈 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

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n 5 10 15 20 25 30 35 40 45 Ratio 0.8 1 1.2 Data Uncertainties MC / Data

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n 5 10 15 20 25 30 35 40 45 Ratio 0.8 1 1.2 [ GeV ] 〉

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n 20 40 60 80 100 120 Ratio 0.8 1 1.2 11/27

SLIDE 12

Minimum bias and PYTHIA AMBT1

Minimum bias data from ATLAS covering quite inclusive charged particle observables using the central tracker. Mainly with a track cut

f pT > 500 MeV, but also at 100 MeV: a challenge for the models.

Various phase spaces, such as diffraction-suppressing Nch cuts.

ch

n /d

ev

N d ⋅

ev

N 1/

6

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10 1 Data 2010 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 100 MeV, |

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p 〈 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 Data 2010 PYTHIA ATLAS AMBT1 PYTHIA ATLAS MC09 PYTHIA DW PYTHIA 8 PHOJET | < 2.5 η > 100 MeV, |

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n 20 40 60 80 100 120 140 160 180 200 Ratio 0.8 1 1.2 12/27

SLIDE 13

Minimum bias and PYTHIA AMBT1

AMBT1 is a min bias dominated tune of PYTHIA MPI: massive improvement in data description by MC. Since then, PYTHIA tuning has moved on to describing hard jets, and then revisiting MB and UE with more data and observables.

[GeV] s

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= 0 η

 η / d

ch

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1/N 2 4 6 8 10

2 ≥

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> 1 M e V , n

T

p 2 ≥

ch

> 1 M e V , n

T

p 6 ≥

c h

> 5 M e V , n

T

p 1 ≥

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> 500 MeV, n

T

p 1 ≥

ch

> 2.5 GeV, n

T

p ATLAS Data PYTHIA 6 AMBT1

[GeV] s

3

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= 0 η

 η / d

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1/N 2 4 6 8 10

13/27

SLIDE 14

UE observables

◮ Underlying event observables are

designed to require a hard scattering process, but to minimise its effect.

◮ Simplest is to align an event with the

momentum flow of the hard scatter, and then look perpendicular to that: define three azimuthal regions, toward, transverse, and away.

◮ Towards region contains hardest

jet/EW boson/etc., away contains balance QCD, and transverse should be UE. (NB. In DY, towards is most interesting for UE)

◮ Plot evolution of UE characteristics

(multiplicity, pT, etc.) with hard process characteristics (plead

⊥ , ηlead,

etc.)

∆φ −∆φ leading track toward |∆φ| < 60◦ away |∆φ| > 120◦ transverse 60◦ < |∆φ| < 120◦ transverse 60◦ < |∆φ| < 120◦

14/27

SLIDE 15

ATLAS UE measurements

We use the leading track rather than leading jet for event orientation –

nly a useful strategy for a short plead

⊥

reach (< 20 GeV) but fewer

systematics. A good plan: CMS are still unfolding and ATLAS JES is not yet

well-understood below ∼ 30 GeV!

Min bias triggered events, but require one track within tracker acceptance of |η| < 2.5 with pT > 1 GeV. Measured at both 900 GeV (limited stats) and at 7 TeV: different energies important for MPI model

tuning. Track pT cuts of 100 and 500 MeV.

Correction back to particle level (as for min bias) – lots of reweighting to account for track and vertex efficiency functions, bin migrations, fakes and secondaries, MC input systematics, detector material. Direct input for signal MC tunings of MPI etc..

15/27

SLIDE 16

Previous UE observations

First UE measurements were made by CDF in 2001: p¯ p at 1800 GeV. Since then, several more CDF studies: transverse cones in 2004, and Drell-Yan and high-stats leading calo jet versions in 2008.

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b

CDF

b

Pythia 8.145 Sherpa 1.2.3 Herwig 0.5 1 1.5 2 Transverse region charged p⊥ density ptrack

T

/dη dφ / GeV 50 100 150 200 250 300 350 400 0.6 0.8 1 1.2 1.4 pT (leading jet) / GeV MC/data

b b b b b b b b b b b b b b b b b b b b

CDF

b

Pythia 8.145 Sherpa 1.2.3 Herwig 0.2 0.4 0.6 0.8 1 1.2 Toward region charged psum

⊥

density ptrack

T

/dη dφ / GeV 20 40 60 80 100 0.6 0.8 1 1.2 1.4 pT (Z) / GeV MC/data

These have all been used in recent years for MC tuning. Little diffractive process effect means it is a clean observable: most MC diffractive models are not great!

16/27

SLIDE 17

∆φ distribution

pT in ∆φ relative to leading track, at 7 TeV

◮ Leading track at

∆φ = 0 has been removed, plot is +/− symmetrized.

◮ Various cuts on track

pT shown.

◮ Note emergence of

leading and balance jet structure; transverse region is depleted of jet activity.

◮ MC description of ∆φ

is pretty bad for higher plead

⊥

[rad]

wrt lead

φ ∆

3
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1 2 3

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p

∑

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d

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= 7 TeV s > 1, 2, 3, 5 GeV, bottom to top

lead T

p | < 2.5, η > 0.5 GeV and |

T

p

ATLAS

Transverse Toward Away Transverse Away

Data 2010 PYTHIA ATLAS MC09

17/27

SLIDE 18

PYTHIA vs. Sherpa description of ∆φ data

(from Hendrik Hoeth, Nov 2010 ATLAS MC meeting / MPI@LHC)

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SLIDE 19

ATLAS UE measurements

pT, transverse region, 900 GeV and 7 TeV

[GeV]

lead T

p

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MC/Data

0.6 0.8 1 1.2 1.4

[GeV]

lead T

p

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MC/Data

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2 3 4 5 6 7 8 9 10

> [GeV] φ d η /d

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p

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<d

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p

ATLAS

Data 2009 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

[GeV]

lead T

p

2 4 6 8 10 12 14 16 18 20

MC/Data

0.6 0.8 1 1.2 1.4

[GeV]

lead T

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MC/Data

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> [GeV] φ d η /d

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<d

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 Transverse Region = 7 TeV s | < 2.5 η > 0.5 GeV and |

T

p

ATLAS

Data 2010 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

Variety of different MC predictions! PHOJET totally uncompetitive for UE (and not generally useful, anyway).

19/27

SLIDE 20

ATLAS UE measurements: results

pT, towards region, 900 GeV and 7 TeV

[GeV]

lead T

p

1 2 3 4 5 6 7 8 9 10

MC/Data

0.7 0.8 0.9 1 1.1 1.2

[GeV]

lead T

p

1 2 3 4 5 6 7 8 9 10

MC/Data

0.7 0.8 0.9 1 1.1 1.2

1 2 3 4 5 6 7 8 9 10

> [GeV] φ d η /d

T

p

∑

2

<d

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 Toward Region = 900 GeV s | < 2.5 η > 0.5 GeV and |

T

p

ATLAS

Data 2009 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

[GeV]

lead T

p

2 4 6 8 10 12 14 16 18 20

MC/Data

0.6 0.8 1 1.2 1.4

[GeV]

lead T

p

2 4 6 8 10 12 14 16 18 20

MC/Data

0.6 0.8 1 1.2 1.4

2 4 6 8 10 12 14 16 18 20

> [GeV] φ d η /d

T

p

∑

2

<d

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Toward Region = 7 TeV s | < 2.5 η > 0.5 GeV and |

T

p

ATLAS

Data 2010 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

Mostly perturbative hard process, so well-described by MC.

20/27

SLIDE 21

ATLAS UE measurements: results

pT vs. nch, transverse region, 7 TeV, 500 MeV track pT cut

ch

N

2 4 6 8 10 12 14 16 18 20

MC/Data

0.9 1 1.1 1.2

ch

N

2 4 6 8 10 12 14 16 18 20

MC/Data

0.9 1 1.1 1.2

2 4 6 8 10 12 14 16 18 20

> [GeV]

T

<p

0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 Transverse Region = 900 GeV s | < 2.5 η > 0.5 GeV and |

T

p

ATLAS

Data 2009 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

ch

N

5 10 15 20 25 30

MC/Data

0.9 1 1.1 1.2

ch

N

5 10 15 20 25 30

MC/Data

0.9 1 1.1 1.2

5 10 15 20 25 30

> [GeV]

T

<p

0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 Transverse Region = 7 TeV s | < 2.5 η > 0.5 GeV and |

T

p

ATLAS

Data 2010 PYTHIA ATLAS MC09 HERWIG+JIMMY ATLAS MC09 PYTHIA DW PYTHIA Perugia0 PHOJET

Strongly influenced by tuning of colour reconnection models: variety

f MC model predictions. JIMMY surprisingly good!

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SLIDE 22

LHC common UE observables

Restrict to |η| < 0.8, pT > 500 MeV for LPCC inter-LHC experiment comparisons: ATLAS pT with common cuts (see LPCC MB/UE workshop Mon/Tues this week!): Informal comparison to ALICE looked good at MPI@LHC! (from Sara Vallejo, MPI@LHC)

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SLIDE 23

HERWIG+JIMMY AUET1 vs. ATLAS UE

JIMMY model is only valid for secondary scattering in the presence of a hard interaction: special UE-only tunes to several PDFs. Manual version of PYTHIA √s evolution.

900 GeV 7 TeV

b b b b b b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.2 0.4 0.6 0.8 1 Transverse region Nch density vs. plead

⊥

(√s = 900 GeV) d2Nch/dηdφ 1 2 3 4 5 6 7 8 9 10 0.6 0.8 1 1.2 1.4 p⊥ (leading track) [GeV] MC/data

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.5 1 1.5 2 Transverse region Nch density vs. plead

⊥

(√s = 7 TeV) d2Nch/dηdφ 2 4 6 8 10 12 14 16 18 20 0.6 0.8 1 1.2 1.4 p⊥ (leading track) [GeV] MC/data 23/27

SLIDE 24

HERWIG+JIMMY AUET1 vs. ATLAS UE

JIMMY model is only valid for secondary scattering in the presence of a hard interaction: special UE-only tunes to several PDFs. Manual version of PYTHIA √s evolution.

900 GeV 7 TeV

b b b b b b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Transverse region ∑ p⊥ density vs. plead

⊥

(√s = 900 GeV) d2 ∑ p⊥/dηdφ [GeV] 1 2 3 4 5 6 7 8 9 10 0.6 0.8 1 1.2 1.4 p⊥ (leading track) [GeV] MC/data

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.5 1 1.5 2 2.5 Transverse region ∑ p⊥ density vs. plead

⊥

(√s = 7 TeV) d2 ∑ p⊥/dηdφ [GeV] 2 4 6 8 10 12 14 16 18 20 0.6 0.8 1 1.2 1.4 p⊥ (leading track) [GeV] MC/data 24/27

SLIDE 25

HERWIG+JIMMY AUET1 vs. ATLAS UE

JIMMY model is only valid for secondary scattering in the presence of a hard interaction: special UE-only tunes to several PDFs. Manual version of PYTHIA √s evolution.

900 GeV 7 TeV

b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 Transverse region p⊥ vs. Nch (√s = 900 GeV) p⊥ [GeV] 2 4 6 8 10 12 14 16 18 20 0.6 0.8 1 1.2 1.4 Nch MC/data

b b b b b b b b b b b b b b b b b b b b b b b b b b b b b

p⊥ > 500 MeV, |η| < 2.5 ATLAS data (preliminary)

b

HERWIG MC09 HERWIG AUET1 (MRST LO∗) HERWIG AUET1 (CTEQ6L1) HERWIG AUET1 (CTEQ6.6) 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 Transverse region p⊥ vs. Nch (√s = 7 TeV) p⊥ [GeV] 5 10 15 20 25 30 0.6 0.8 1 1.2 1.4 Nch MC/data 25/27

SLIDE 26

Strangeness!

ALICE and LHCb – deficient MC models. Requires a really comprehensive retune of PYTHIA (and newer C++ generators) from LEP via Tevatron to LHC to understand what’s going on: happening in ATLAS.

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SLIDE 27

Summary

◮ Collective excitations of protons are being constrained through

MC models using the first year of LHC data.

◮ Total inel. cross-section, min bias (= pile-up), and underlying

event particle and energy-momentum flow has been constrained – super-high precision, full-data version nearing completion. See almost whole particle spectrum with low-pT tracking.

◮ Baryon number, strangeness, forward regions, neutral particle

flow, correlations all being constrained by data nearly released:

nly 1 year in and we’re already entering a new era of precision

soft QCD!

◮ More UE measurements underway: in jets, W and Z events, using

jet structure techniques for jet cleaning heuristics.

◮ The interesting and still mysterious places are the awkward tails

f min bias, particularly forward regions and high multiplicity (cf.

CMS’ “near-side ridge” effect). Hard to measure, but could be very rewarding.

◮ Everything is a tail of min bias eventually! ;-)

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SLIDE 28

Backup slides

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SLIDE 29

Specific MC model details

◮ PYTHIA (and Pythia 8) also have a complex interleaving of

parton shower and MPI scattering evolution, and a dynamic (and very tweakable) colour string reconnection/reconfiguration mechanism.

◮ HERWIG/JIMMY has a variant on the basic model with no

energy evolution, no colour reconnection, and no purely soft scattering (“min bias”)

◮ Herwig++ has an extension of the JIMMY model, with soft

scattering introduced in a more theoretically motivated way than PYTHIA (connection to elastic scattering and total cross-section). The immediate next release will also have pre-hadron cluster reorganisation, cf. PYTHIA’s colour string reconnection.

◮ PHOJET/EPOS have a more “pomerony” soft of model, but with

a lot of similar stuff like the eikonal multiple scattering bit.

◮ Sherpa currently has pretty much the basic model above, with

very simple colour reconnection. But totally new KMR-based model in development for 2.0.

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