MC Tuning from TeV to LHC based on Dijet Azimuthal...

MC Tuning from TeV to LHCbased on Dijet Azimuthal Decorelations

Markus Wobisch, Fermilab

TeV4LHC Workshop – September 16, 2004

• Motivation / Observable

• Experimental Results

• Fixed Order pQCD Description

• MC Tuning to TeV Data

• Extrapolation to LHC Energies?

in collaboration with: A. Kupco, M. Begel, C. Royon, M. Zielinski

Markus Wobisch, Fermilab MC Tuning from TeV to LHC TeV4LHC Workshop, 09/15/04 1

Monte Carlos – what can be tuned?

event topology: fundamental signature + broad features + fine details

Monte Carlo Event Generators:

• LO Matrix Elements for fundamental process (e.g. 2 → 2) → normalization uncertainty!

• perturbative parton cascade models (based on soft and collinear approximations)

• phenomenological models for non-perturbative phase (hadronization, underlying event)

Tuning MCs?

• LO MEs are exact (use most recent αs and MRST/CTEQ pdfs)

• everything else can be tuned!! – plenty of parameters in PYTHIA / less in HERWIG

How to tune MCs? (don’t use “hard” parameters to fix “soft” physics)

• first: find k-factor to fix normalization problem – or use normalized differential distrib.

• second: use “broad” event features to tune “hard” physics ⇐ scope of this talk

• third: tune soft physics to describe finer details


Dijet Azimuthal Decorrelations

∆φdijet

Dijet Production:

• limit: exactly two jets, no further radiation

azimuthal opening anglebetween both leading pT jets:

⇒ ∆φ dijet = π



∆φdijet

Dijet Production:


• additional soft radiation outside the jets



⇒ ∆φ dijet small deviations from π



∆φdijet

Dijet Production:



• one additional high pT jet




⇒ ∆φ dijet as small as 2π/3



∆φdijet

Dijet Production:




• multiple additional hard jets in the event





⇒ small ∆φ dijet – no limit



∆φdijet

Dijet Production:




• multiple additional hard jets in the event





⇒ small ∆φ dijet – no limit

⇒ ∆φ dijet distribution is sensitive to higher order pQCD effects without requiring thereconstruction of additional jets (Yes: this is an experimental advantage!!)

⇒ ∆φ dijet: examine transition between soft and hard physics, based on single observable


Defining the Observable

• define the jets using iterative, seed-based midpoint cone algorithmwith Rcone = 0.7 in rapidity and azimuthal angle(the “Run II cone algorithm” ⇐ Run II Workshop)

• Define the observable to be the normalized differential ∆φ dijet distribution:

1

σdijet

·dσdijet

d∆φ dijet

• measure the observable as a function of a hard scale:⇒ in four different regions of the leading jet pT – starting at pmax

T > 75 GeV

requiring the second leading pT jet to have pT > 40 GeV

• require that both leading pT jets have central rapidity |yjet| < 0.5

the ∆φ dijet distribution is a three-jet observable! the ratio is ∝ α3s/α2

s

recently available: NLO pQCD predictions for 3-jet observables: pQCD at O(α4s)

(NLOJET++, Z. Nagy)


Non-Perturbative Effects

Hadronization Corrections: Obs.hadronObs.parton

Underlying Event: Obs.with UEVTObs.w/o UEVT

0.951

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

hadr

oniz

atio

n co

rrec

tion

c =

σha

dron

/σpa

rton

pT max > 180 GeV

0.951

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

130 < pT max < 180 GeV

0.951

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

100 < pT max < 130 GeV

0.951

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

∆φ dijet (rad)

75 < pT max < 100 GeV

π/2 3π/4 π

PYTHIAHERWIG

0.95

1

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

unde

rlyin

g ev

ent c

orre

ctio

n

pT max > 180 GeV

0.95

1

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

130 < pT max < 180 GeV

0.95

1

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

100 < pT max < 130 GeV

0.95

1

1.05

1.5707 1.9634 2.3561 2.7489 3.1416

∆φ dijet (rad)

75 < pT max < 100 GeV

PYTHIA 6.225

π/2 3π/4 π

Non-perturbative effects are below 5% =⇒ only sensitive to perturbative effects


Experimental Results

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×8000)130 < pT

max < 180 GeV (×400)100 < pT

max < 130 GeV (×20) 75 < pT

max < 100 GeV

DØ

10-3

10-2

10-1

1

10

10 2

10 3

10 4

10 5

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

First Tevatron Run II QCD Jet Publicationhep-ex/0409040 submitted to PRL today!

• data in four pmaxT regions:

⇒ more strongly peaked at high pmaxT

⇒ decreasing by more than 4 orders ofmagnitude from ∆φ dijet = π to π/2


Experimental Results

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×8000)130 < pT

max < 180 GeV (×400)100 < pT

max < 130 GeV (×20) 75 < pT

max < 100 GeV

LONLO

NLOJET++ (CTEQ6.1M)µr = µf = 0.5 pT

max

DØ

10-3

10-2

10-1

1

10

10 2

10 3

10 4

10 5

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

First Tevatron Run II QCD Jet Publicationhep-ex/0409040 submitted to PRL today!

• data in four pmaxT regions:

⇒ more strongly peaked at high pmaxT

⇒ decreasing by more than 4 orders ofmagnitude from ∆φ dijet = π to π/2

• LO pQCD prediction is poor

⇒ reasonable only in limited ∆φ dijet range

⇒ ∆φ dijet < 2π/3 no phase space

⇒ ∆φ dijet → π divergence

• NLO pQCD prediction is very good

⇒ (see ratios for details)


Quantitative Comparison: Data and NLO

1

2

1.5707 1.9634 2.3561 2.7489 3.1416

pT max > 180 GeV

Dat

a / N

LO T

heor

y

DØ

1

2

1.5707 1.9634 2.3561 2.7489 3.1416

130 < pT max < 180 GeV

µr, µf dependencePDF uncertainty

1

2

1.5707 1.9634 2.3561 2.7489 3.1416

100 < pT max < 130 GeV

1

2

1.5707 1.9634 2.3561 2.7489 3.1416

75 < pT max < 100 GeV

∆φ dijet (rad)

NLOJET++ (CTEQ6.1M)

π/2 3π/4 π

• NLO pQCD:

⇒ good description of the dataon average 5–10% below data

⇒ except at ∆φ dijet close to π

(soft processes – needs resummation)

• renormalization and factorizationscale dependence:0.25pmax

T < µr,f < pmaxT

⇒ small at intermediate ∆φ dijet

⇒ large at ∆φ dijet → π (soft region)

⇒ large at ∆φ dijet < 2π/3

(only tree-level four parton final states)

• PDF uncertainty using CTEQ6.1M pdfs

⇒ dominant at intermediate ∆φ dijet

larger in high pmaxT region


Comparison: Data and MCs

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×8000)130 < pT

max < 180 GeV (×400)100 < pT

max < 130 GeV (×20) 75 < pT

max < 100 GeV

HERWIG 6.505PYTHIA 6.225

DØ

(CTEQ6L)

10-3

10-2

10-1

1

10

10 2

10 3

10 4

10 5

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

• HERWIG v6.505 (default)

⇒ good description of the dataover whole ∆φ dijet range

• PYTHIA v6.225 (default)

⇒ significantly too low at small ∆φ dijet

⇒ too narrowly peaked at π


Comparison: Data and MCs

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×8000)130 < pT

max < 180 GeV (×400)100 < pT

max < 130 GeV (×20) 75 < pT

max < 100 GeV

HERWIG 6.505PYTHIA 6.225PYTHIAincreased ISR

(CTEQ6L)

DØ

10-3

10-2

10-1

1

10

10 2

10 3

10 4

10 5

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

• HERWIG v6.505 (default)

⇒ good description of the dataover whole ∆φ dijet range

• PYTHIA v6.225 (default)

⇒ significantly too low at small ∆φ dijet

⇒ too narrowly peaked at π

• changing maximum pT in ISR shower(remember: Rick Field’s PYTHIA “tune A”)

⇒ change: PARP(67)=1.0 → 4.0

PARP(67) × hard scale (' pT ) definesthe maximum virtuality in ISR shower

⇒ directly related to max. pT in ISR shower

⇒ huge effect for ∆φ dijet distribution

⇒ best value somewhere betweenPARP(67)=1.0 and =4.0

⇒ hard processes can be adjusted!


Data and MCs — looking at ∆φ dijet ≈ π

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×30)130 < pT

max < 180 GeV (×10)

100 < pT max < 130 GeV (×3)

75 < pT max < 100 GeV

HERWIG 6.505PYTHIA 6.225 default increased pT max ISR

DØ

(CTEQ6L)

1

10

10 2

0.8125 0.875 0.9375 1

15π/167π/813π/16 π

– zoom into the peak– this is where NLO fails (soft processes!)– where parton shower should work

use same MCs as before:

• HERWIG (default)

⇒ slightly to narrow — but reasonable

• PYTHIA (default)

⇒ much too narrowly peaked at π

too low everywhere else

• PYTHIA with PARP(67)=4.0

⇒ too narrow in peak

⇒ too low at ∆φ dijet ≈ 15π/16

(low ∆φ dijet tail slightly high)

⇒ more tuning needed for PYTHIA to describe peak region (soft processes)


Tuning PYTHIA – soft processes

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×8)130 < pT

max < 180 GeV (×4)100 < pT

max < 130 GeV (×2)

75 < pT max < 100 GeV

PYTHIA 6.225 default increased pT max ISR

decreased xµ ISR

increased prim. kT

DØ

(CTEQ6L)

1

10

10 2

0.875 0.9062 0.9375 0.9688 1

15π/167π/8 π

vary PYTHIA parameters related to ISR

• pT max ISR PARP(67)=4.0 (D=1.0)

⇒ small effect at high ∆φ dijet for low pmaxT

• xµ ISR PARP(64)=0.5 (D=1.0)

⇒ effect is negligible

• primordial kT PARP(91)=4.0 (D=1.0)

upper cut-off PARP(93)=8.0 (D=5.0)

⇒ very small effect at high ∆φ dijet for low pmaxT

⇒ nothing helps!


Tuning PYTHIA – soft processes

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×150)130 < pT

max < 180 GeV (×25)100 < pT

max < 130 GeV (×5) 75 < pT

max < 100 GeV

HERWIG 6.505PYTHIA 6.225 default increased pT max FSR

DØ

(CTEQ6L)10

-1

1

10

10 2

10 3

0.75 0.8125 0.875 0.9375 1

3π/4 7π/8 π

vary PYTHIA parameters related to FSR:

• pT max ISR ↔ PARP(67) was so successful

⇒ try the same thing for FSR

• pT max FSR ↔ PARP(71)

⇒ increase: PARP(71)=8.0 (D=4.0)

⇒ zero effect!

⇒ Here we ran out of ideas...

More suggestions for PYTHIAparameters variations are welcome!!

HERWIG: we tried PTRMS=1.5 GeV (D=0)

⇒ no effect


From Tevatron to the LHC

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

75 < pT max < 100 GeV

100 < pT max < 130 GeV

130 < pT max < 180 GeV

pT max > 180 GeV

180 < pT max < 500 GeV

500 < pT max < 1200 GeV

pT max > 1200 GeV

LHC

Tevatron

NLO pQCD

(all curves: from top to bottom)

NLOJET++ (CTEQ6.1M)µr = µf = 0.5 pT

max10-4

10-3

10-2

10-1

1

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

NLO gives a very good description⇒ use NLO as a reference

compare NLO predictions for ∆φ dijet

at Tevatron and LHC

for both: Run II cone algorithm, |yjet| < 0.5

• Tevatron Run II (as: hep-ex/0409040)

⇒ pT 2 > 40 GeV

⇒ four pmaxT regions

• LHC

⇒ pT 2 > 80 GeV

⇒ three pmaxT regions

⇒ The chosen pmaxT ranges for the LHC results cover the spread of the Tevatron results


A last look at the Tevatron ...

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

pT max > 180 GeV (×103)130 < pT max < 180 GeV (×102)100 < pT max < 130 GeV (×10) 75 < pT max < 100 GeV

from top to bottom:

75 < pT max < 100 GeV (×8)

100 < pT max < 130 GeV (×4)

130 < pT max < 180 GeV (×2)

pT max > 180 GeV

NLOHERWIGPYTHIA (TeV-tuned)

Tevatron Run II

10-4

10-3

10-2

10-1

1

10

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

best description by PYTHIAfor PARP(67) between D=1.0 and 4.0

• tune PARP(67) to NLO

⇒ result: PARP(67)=2.5 (D=1.0)

⇒ this setting is now referred to as “TeV-tuned”

• (ignore the peak region...)

⇒ good agreement:HERWIG ≈ PYTHIA ≈ NLO

Question:Can this good agreement (and the tune)be transferred to the LHC?


... and a first look at the LHC

∆φ dijet (rad)

1/σ di

jet

dσdi

jet /

d∆φ

dije

t

from top to bottom:

180 < pT max < 500 GeV (×4)

500 < pT max < 1200 GeV (×2)

pT max > 1200 GeV

NLOHERWIGPYTHIA (TeV-tuned)

LHC

10-4

10-3

10-2

10-1

1

10

0.5 0.625 0.75 0.875 1

π/2 3π/4 π

... a huge success!!! – ... expected??

• PYTHIA (TeV-tuned)

⇒ the good agreement with NLOat Tevatron Run II energiesis reproduced at LHC energies!!

• HERWIG (default)

⇒ small differences:broader at low pmax

T

narrower at large pmaxT

⇒ Both Monte Carlos are in good agreement with NLO predictions


Summary and Conclusions

using Dijet Azimuthal Decorrelations to test & tune Monte Carlo event generators:

• normalized distribution⇒ not affected by poor absolute normalization of LO Matrix Elements

• not sensitive to non-perturbative effects (hadronization, underlying event)⇒ allows to tune perturbative parameters in MCs w/o interference of “soft parameters”

• strategy must be:⇒ tune “hard parameters” first — then the “soft parameters”⇒ e.g. order: Dijet Azimuthal Decorrelations → Jet Shapes → Underlying Event

• HERWIG: not much to tune (no parameters / but also: not necessary)• PYTHIA: only sensitivity: pT max ISR – result: PARP(67)=2.5 (D=1.0)

⇒ this should be the basis for a new Tevatron tune (“tune A-prime”?)

surprise: PYTHIA tuning can be transferred to LHC energies=⇒ very promising for tuning MCs for LHC!


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MC Tuning from TeV to LHC based on Dijet Azimuthal...

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