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N ew D eve l o p m e n t s i n P a r t o n S h owe r s P. S k a n d s ( C E R N ) Goal: solve this (Request to experiments: solve this) Fields Hits Symmetries 0100110 Amplitudes Acceptance Theory Experiment Monte Carlo Feedback Loop

slide-1
SLIDE 1
  • P. S k a n d s ( C E R N )

N ew D eve l o p m e n t s i n P a r t o n S h owe r s

Wo r k i n c o l l a b o r a t i o n w i t h W. G i e l e , D. K o s o w e r, A . L a r k o s k i , J . L o p e z - V i l l a r e j o ( s e c t o r s h o w e r s , h e l i c i t y - d e p e n d e n c e ) , A . G e h r m a n n - d e - R i d d e r, M . R i t z m a n n ( m a s s e f f e c t s , i n i t i a l - s t a t e r a d i a t i o n ) , E . L a e n e n , L . H a r t g r i n g ( o n e - l o o p c o r r e c t i o n s )

Theory Experiment

Measurements corrected to Hadron Level with acceptance cuts (~ model-independent) Theory worked out to Hadron Level with acceptance cuts (~ detector-independent) Fields Symmetries Amplitudes Monte Carlo Resummation Strings ... Hits 0100110 Acceptance GEANT B-Field .... Feedback Loop

Goal: solve this

(Request to experiments: solve this)

slide-2
SLIDE 2

L = ¯ ψi

q(iγµ)(Dµ)ijψj q−mq ¯

ψi

qψqi−1

4F a

µνF aµν

2

+ quark masses and value of αs THEORY

slide-3
SLIDE 3

3 “Nothing” Gluon action density: 2.4x2.4x3.6 fm QCD Lattice simulation from

  • D. B. Leinweber, hep-lat/0004025

L = ¯ ψi

q(iγµ)(Dµ)ijψj q−mq ¯

ψi

qψqi−1

4F a

µνF aµν

slide-4
SLIDE 4

Reality is more complicated

Perturbation Theory

4

High%transverse- momentum% interac2on%
slide-5
SLIDE 5

Monte Carlo Generators

5

Improve Born-level perturbation theory, by including the ‘most significant’ corrections → complete events → any observable you want

Calculate Everything ≈ solve QCD → requires compromise!

  • 1. Parton)Showers))
  • 2. Matching)
  • 3. Hadronisa7on)
  • 4. The)Underlying)Event)
  • 1. So?/Collinear)Logarithms)
  • 2. Finite)Terms,)“K”Ifactors)
  • 3. Power)Correc7ons)(more)if)not)IR)safe))
  • 4. ?)

roughly

(+ many other ingredients: resonance decays, beam remnants, Bose-Einstein, …)

slide-6
SLIDE 6

Bremsstrahlung

Charges Stopped Associated field (fluctuations) continues I S R I S R

6

The harder they stop, the harder the fluctations that continue to become strahlung

slide-7
SLIDE 7

Bremsstrahlung

7

d σX$

dσX+1& d σX+2 & dσX+2&

Total cross section would be infinite …

This gives an approximation to infinite-order tree-level cross sections (here “DLA”) But something is not right …

slide-8
SLIDE 8

Loops and Legs

Summation

8

X(2) X+1(2) … X(1) X+1(1) X+2(1) X+3(1) … Born X+1(0) X+2(0) X+3(0) …

L

  • p

s L e g s The Virtual corrections are missing

Universality (scaling)

Jet-within-a-jet-within-a-jet-...

slide-9
SLIDE 9

Resummation

9

d σX$

dσX+1& d σX+2 & dσX+2&

Unitarity

KLN:

Virt = - Int(Tree) + F

In LL showers : neglect F → includes both real and virtual corrections (in LL approx)

σX+1(Q) = σX;incl– σX;excl(Q)

Imposed by Event evolution: When (X) branches to (X+1): Gain one (X+1). Loose one (X).

slide-10
SLIDE 10

Bootstrapped pQCD

Resummation

10

X(2) X+1(2) … X(1) X+1(1) X+2(1) X+3(1) … Born X+1(0) X+2(0) X+3(0) …

L

  • p

s L e g s Born + Shower

Unitarity Universality (scaling)

Jet-within-a-jet-within-a-jet-...

Exponentiation

slide-11
SLIDE 11

Matching

11

► A (Complete Idiot’s) Solution – Combine

  • 1. [X]ME + showering
  • 2. [X + 1 jet]ME + showering
  • 3. …

► Doesn’t work

  • [X] + shower is inclusive
  • [X+1] + shower is also inclusive

≠

Run generator for X (+ shower) Run generator for X+1 (+ shower) Run generator for … (+ shower) Combine everything into one sample What you get What you want Overlapping “bins” One sample

slide-12
SLIDE 12

The Matching Game

12

Shower off X already contains LL part of all X+n Adding back full ME for X+n would be

  • verkill
  • Solution 1: “Additive” (most widespread)

Add event samples, with modified weights

wX = |MX|2 + Shower wX+1 = |MX+1|2 – Shower{wX} + Shower wX+n = |MX+n|2 – Shower{wX,wX+1,...,wX+n-1} + Shower HERWIG: for X+1 @ LO (Shower = 0 in dead zone of angular-ordered shower) MC@NLO: for X+1 @ LO and X @ NLO (note: correction can be negative) CKKW & MLM : for all X+n @ LO (force Shower = 0 above “matching scale” and add ME there) SHERPA (CKKW), ALPGEN (MLM + HW/PY), MADGRAPH (MLM + HW/PY), PYTHIA8 (CKKW-L from LHE files), …

Only CKKW and MLM

Seymour (Herwig), CPC 90 (1995) 95 CKKW (Sherpa), JHEP 0111 (2001) 063 Lönnblad (Ariadne), JHEP 0205 (2002) 046 Frixione-Webber (MC@NLO), JHEP 0206 (2002) 029 + many more recent ...

slide-13
SLIDE 13

The Matching Game

Shower off X already contains LL part of all X+n Adding back full ME for X+n would be

  • verkill

13

  • Solution 2: “Multiplicative”

One event sample

wX = |MX|2 + Shower

Make a “course correction” to the shower at each order

RX+1 = |MX+1|2/Shower{wX} + Shower RX+n = |MX+n|2/Shower{wX+n-1} + Shower PYTHIA: for X+1 @ LO (for color-singlet production and ~ all SM and BSM decay processes) POWHEG: for X+1 @ LO and X @ NLO (note: positive weights) VINCIA: for all X+n @ LO and X @ NLO (only worked out for decay processes so far)

Only VINCIA

POWHEG Box HERWIG++ …

Bengtsson-Sjöstrand (Pythia), PLB 185 (1987) 435 + more Bauer-Tackmann-Thaler (GenEva), JHEP 0812 (2008) 011 Giele-Kosower-Skands (Vincia), PRD84 (2011) 054003

slide-14
SLIDE 14

P . Skands - New Developments in Parton Showers

Markov pQCD

14 Legs Loops +0 +1 +2 +0 +1 +2 +3

|MF|2

Generate “shower” emission

|MF+1|2 LL ∼ X

i∈ant

ai |MF|2

Correct to Matrix Element Unitarity of Shower

P | | Virtual = − Z Real

PYTHIA trick

Correct to Matrix Element

Z |MF|2 → |MF|2 + 2Re[M 1

FM 0 F] +

Z Real

POWHEG trick

R e p e a t

The VINCIA Code

MC@NLO & POWHEG MLM & CKKW LO for 1st emission LL for 2nd emission and beyond “Matching Scale” → hierarchies not matched Work in Progress

~ PYTHIA + POWHEG This Talk

GKS, PRD84(2011)054003 GKS, PRD78(2008)014026

Start at Born level

X

∈

ai → |MF+1|2 P ai|MF|2 ai →

slide-15
SLIDE 15

P . Skands - New Developments in Parton Showers

The Denominator v

15

In a traditional parton shower, you would face the following problem:

Existing parton showers are not really Markov Chains

Further evolution (restart scale) depends on which branching happened last → proliferation of terms

Number of histories contributing to nth branching ∝ 2nn!

~

+ + +

j = 2 → 4 terms j = 1 → 2 terms

~

(

+

)

Parton- (or Catani-Seymour) Shower:

After 2 branchings: 8 terms After 3 branchings: 48 terms After 4 branchings: 384 terms X

∈

ai → |MF+1|2 P ai|MF|2

(+ parton showers have complicated and/or frame-dependent phase-space mappings, especially at the multi-parton level)

slide-16
SLIDE 16

P . Skands - New Developments in Parton Showers

Matched Markovian Antenna Showers

+ Change “shower restart” to Markov criterion:

Given an n-parton configuration, “ordering” scale is Qord = min(QE1,QE2,...,QEn)

Unique restart scale, independently of how it was produced

+ Matching: n! → n

Given an n-parton configuration, its phase space weight is: |Mn|2 : Unique weight, independently of how it was produced

16

Matched Markovian Antenna Shower:

After 2 branchings: 2 terms After 3 branchings: 3 terms After 4 branchings: 4 terms

Parton- (or Catani-Seymour) Shower:

After 2 branchings: 8 terms After 3 branchings: 48 terms After 4 branchings: 384 terms

+ Sector antennae → 1 term at any order (+ generic Lorentz- invariant and on-shell phase-space factorization)

Antenna showers: one term per parton pair

2nn! → n!

Larkosi, Peskin,Phys.Rev. D81 (2010) 054010 Lopez-Villarejo, Skands, JHEP 1111 (2011) 150 Giele, Kosower, Skands, PRD 84 (2011) 054003

slide-17
SLIDE 17

P . Skands - New Developments in Parton Showers

Approximations

17

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5 Fraction of Phase Space

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

4 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z GGG

PS

ψ

  • ord

D

m ARI

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4
  • 3
  • 2
  • 1

10 1

5 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

6 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z

S T RO N G O R D E R I N G

Q: How well do showers do? Exp: Compare to data. Difficult to interpret; all-orders cocktail including hadronization, tuning, uncertainties, etc Th: Compare products of splitting functions to full tree-level matrix elements Plot distribution of Log10(PS/ME)

(fourth order) (third order) (second order) Dead Zone: 1-2% of phase space have no strongly ordered paths leading there*

*fine from strict LL point of view: those points correspond to “unordered” non-log-enhanced configurations

slide-18
SLIDE 18

P . Skands - New Developments in Parton Showers

2→4

Generate Branchings without imposing strong ordering

At each step, each dipole allowed to fill its entire phase space

Overcounting removed by matching + smooth ordering beyond matched multiplicities

18

⊥

2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/p

2 T2

p ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = (smooth)

T 2

ORD = p

>

4

<R

→ Ordered | 2nd | Unordered ← → Soft | 1st Branching | Hard ←

2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/p

2 T2

p ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = (strong)

T 2

ORD = p

>

4

<R

→ Ordered | 2nd | Unordered ← → Soft | 1st Branching | Hard ←

Dead Zone Smooth Ordering

= ˆ p2

⊥

ˆ p2

⊥ + p2 ⊥

PLL d parton triplets in = ˆ p2

⊥ last branching ⊥

+ p2

⊥

  • n triplets

current branching

slide-19
SLIDE 19

P . Skands - New Developments in Parton Showers

→ Better Approximations

19

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5 Fraction of Phase Space

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

4 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

AR

ψ GGG,

PS

ψ GGG,

KS

ψ GGG, (qg & gg)

AR

ψ ARI,

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4
  • 3
  • 2
  • 1

10 1

5 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

6 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5 Fraction of Phase Space

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

4 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z GGG

PS

ψ

  • ord

D

m ARI

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4
  • 3
  • 2
  • 1

10 1

5 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

6 → Z

Vincia 1.025 + MadGraph 4.426

Strong Ordering 3 → Matched to Z

S T RO N G O R D E R I N G S M O OT H M A R KOV

Distribution of Log10(PSLO/MELO) (inverse ~ matching coefficient)

Leading Order, Leading Color, Flat phase-space scan, over all of phase space (no matching scale) No dead zone

slide-20
SLIDE 20

P . Skands - New Developments in Parton Showers

+ Matching (+ full colour)

20

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5 Fraction of Phase Space

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

5 → Z

Vincia 1.025 + MadGraph 4.426

Color-summed (NLC) 4 → Matched to Z

AR

ψ GGG,

PS

ψ GGG,

KS

ψ GGG, (qg & gg)

AR

ψ ARI,

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

6 → Z

Vincia 1.025 + MadGraph 4.426

Color-summed (NLC) 5 → Matched to Z

Remaining matching corrections are small

(fourth order) (third order)

M AT C H E D M A R KOV

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5 Fraction of Phase Space

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

4 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

AR

ψ GGG,

PS

ψ GGG,

KS

ψ GGG, (qg & gg)

AR

ψ ARI,

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4
  • 3
  • 2
  • 1

10 1

5 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

(PS/ME)

10

log

  • 2
  • 1.5
  • 1
  • 0.5

0.5

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1

6 → Z

Vincia 1.025 + MadGraph 4.426

Smooth Ordering 3 → Matched to Z

S M O OT H M A R KOV

→ A very good all-orders starting point

slide-21
SLIDE 21

SPEED : milliseconds / Event

MS/EVENT Matched t d through: Monte Carlo

Strategy

Z→3 Z→4 Z→5 Z→6

Pythia 8

Initialization time ~ 0

TS 0.22

Z→

Matched and unw

gfortran/g++ with gcc v.4.4 -O

Z→qq (q=udscb) + show

d and unweighted. Hadroni

h gcc v.4.4 -O2 on single 3.06 GH memory

+ shower.

dronization off

3.06 GHz processor with 4GB

Vincia (sector, Qmatch = 5 GeV)

Initialization time ~ 0

GKS 0.26 0.50 1.40 6.70

Sherpa (Qmatch = 5 GeV)

CKKW

(expect similar scaling for MLM)

5.15* 53.00* 220.00* 400.00*

Initialization time =

(expect similar scaling for MLM)

1.5 minutes 7 minutes 22 minutes 2.2 hours

Generator Versions: Pythia 6.425 6.425 (Perugia 2011 tune), Pythi Pythia 8.150, Sherpa 1.3.0 1.3.0, Vincia 1.026 (without u

ut uncertainty bands, NLL/NLC=O NLC=OFF)

Efficient Matching with Sector Showers

  • J. Lopez-Villarejo & PS : JHEP 1111 (2011) 150

21

slide-22
SLIDE 22

Uncertainties

slide-23
SLIDE 23

P . Skands - New Developments in Parton Showers

Uncertainty Variations

A result is only as good as its uncertainty

Normal procedure:

Run MC 2N+1 times (for central + N up/down variations)

Takes 2N+1 times as long + uncorrelated statistical fluctuations

Automate and do everything in one run

VINCIA: all events have weight = 1 Compute unitary alternative weights on the fly

→ sets of alternative weights representing variations (all with <w>=1) Same events, so only have to be hadronized/detector-simulated ONCE!

23 MC with Automatic Uncertainty Bands

slide-24
SLIDE 24

P . Skands - New Developments in Parton Showers

Uncertainties

For each branching, recompute weight for:

  • Different renormalization scales
  • Different antenna functions
  • Different ordering criteria
  • Different subleading-color treatments

24

Weight Nominal 1 Variation

P2 = αs2a2 αs1a1 P1

For each failed branching:

P2;no = 1 − P2 = 1 − αs2a2 αs1a1 P1 lative event weight by fo

+ Unitarity

+ Matching

Differences explicitly matched out

(Up to matched orders)

(Can in principle also include variations of matching scheme…)

slide-25
SLIDE 25

0.1 0.2 0.3 0.4 0.5

1/N dN/d(1-T)

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia

1-Thrust (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + Pythia 8.145

0.1 0.2 0.3 0.4 0.5 Rel.Unc. 1

R µ

1-T (udsc)

0.1 0.2 0.3 0.4 0.5

Theory/Data

0.6 0.8 1 1.2 1.4

0.1 0.2 0.3 0.4 0.5

1/N dN/d(1-T)

  • 3

10

  • 2

10

  • 1

10 1 10

L3 =pT/2 µ =2pT µ

1-Thrust (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + Pythia 8.145

1-T (udsc)

0.1 0.2 0.3 0.4 0.5

Theory/Data

0.6 0.8 1 1.2 1.4

Automatic Uncertainties

Vincia:uncertaintyBands = on

Traditional Variaton

(two separate runs)

Automatic Variation

(one run) Renormalization Scale Uncertainty ~ constant relative size

Variation of renormalization scale (no matching)

slide-26
SLIDE 26

0.1 0.2 0.3 0.4 0.5

1/N dN/d(1-T)

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia

1-Thrust (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + Pythia 8.145

0.1 0.2 0.3 0.4 0.5 Rel.Unc. 1

Finite

1-T (udsc)

0.1 0.2 0.3 0.4 0.5

Theory/Data

0.6 0.8 1 1.2 1.4

0.1 0.2 0.3 0.4 0.5

1/N dN/d(1-T)

  • 3

10

  • 2

10

  • 1

10 1 10

L3 a=Max a=Min

1-Thrust (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + Pythia 8.145

1-T (udsc)

0.1 0.2 0.3 0.4 0.5

Theory/Data

0.6 0.8 1 1.2 1.4

Automatic Uncertainties

Non-Singular terms only important in “hard multi-jet region”

Traditional Variaton

(two separate runs)

Vincia:uncertaintyBands = on

Automatic Variation

(one run)

Variation of “finite terms” (no matching)

slide-27
SLIDE 27

Putting it Together

VinciaMatching:order = 0 VinciaMatching:order = 3

0.1 0.2 0.3 0.4

T

1/N dN/dB

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia

Total Jet Broadening (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + Pythia 8.150

0.1 0.2 0.3 0.4 Rel.Unc. 1

Def R µ Finite QMatch Ord

2 C

1/N

(udsc)

T

B

0.1 0.2 0.3 0.4

Theory/Data

0.6 0.8 1 1.2 1.4 0.1 0.2 0.3 0.4

T

1/N dN/dB

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia

Total Jet Broadening (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + MadGraph 4.426 + Pythia 8.150

0.1 0.2 0.3 0.4 Rel.Unc. 1

Def R µ Finite QMatch Ord

2 C

1/N

(udsc)

T

B

0.1 0.2 0.3 0.4

Theory/Data

0.6 0.8 1 1.2 1.4

slide-28
SLIDE 28

28

http://projects.hepforge.org/vincia

Next steps

Multi-leg one-loop matching

(with L. Hartgring & E. Laenen, NIKHEF)

Helicity-dependent Showers

(with A. Larkoski, SLAC, & J. Lopez-Villarejo, CERN)

→ Initial-State Showers

(with W. Giele, D. Kosower, S. Mrenna, M. Ritzmann)

VINCIA Status

Plug-in to PYTHIA 8 Stable and reliable for Final- State Jets (E.g., LEP)

Automatic matching and uncertainty bands improvements in shower

(smooth ordering, NLC, Matching, …)

FAST

slide-29
SLIDE 29

Conclusions

  • QCD Phenomenology is witnessing a rapid evolution: LO & NLO

matching, better showers, tuning, interfaces ...

  • Driven by demand for high precision in complex LHC environment with huge

phase space

  • BSM Physics
  • Generally relies on chains of tools (MC4BSM)
  • Sufficient to reach O(10%) accuracy, with hard work, though must be careful

with scale hierarchies, width effects, decay distributions, …

  • Next machine is a long way off → must strive to build capacity for yet higher

precision, to get max from LHC data.

  • Ultimate limit set by solutions to pQCD (getting better) and then the

really hard stuff

  • Like Hadronization, Underlying Event, Diffraction, … (& BSM equivalents?)
  • For which fundamentally new ideas may be needed

For more, see the MCnet Review: General-purpose event generators for LHC physics : arXiv:1101.2599

slide-30
SLIDE 30

Backup Slides

slide-31
SLIDE 31

P . Skands - New Developments in Parton Showers

Simple Solution

Generate Trials without imposing strong ordering

At each step, each dipole allowed to fill its entire phase space

Overcounting removed by matching (revert to strong ordering beyond matched multiplicities)

31

2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/p

2 T2

p ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = ORD = PHASESPACE

>

4

<R

→ Ordered | 2nd | Unordered ← → Soft | 1st Branching | Hard ←

2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/p

2 T2

p ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = (strong)

T 2

ORD = p

>

4

<R

→ Ordered | 2nd | Unordered ← → Soft | 1st Branching | Hard ←

Dead Zone Overcounting

slide-32
SLIDE 32

P . Skands - New Developments in Parton Showers

(Subleading Singularities)

Isolate double-collinear region:

Z→4 : [q,g,g,qbar] with mgg = mZ

32

T1 2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/4p

2 gg

m ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = (smooth)

T 2

ORD = p

>

4

<R

2 Z

/m

2 T1

4p ln

  • 5
  • 4
  • 3
  • 2
  • 1

2 T1

/4p

2 gg

m ln

  • 5
  • 4
  • 3
  • 2
  • 1

1 2 3 4 5 6

q qgg → Z

VINCIA 1.025 ANT = DEF

AR

ψ KIN = (strong)

2 g

ORD = E

>

4

<R

Energy Ordering VINCIA

(before matching)

αs2 ln2

slide-33
SLIDE 33

LEP event shapes

0.1 0.2 0.3 0.4 0.5

1/N dN/d(1-T)

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia Pythia 8

1-Thrust (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + MadGraph 4.426 + Pythia 8.145

0.1 0.2 0.3 0.4 0.5 Rel.Unc. 1

Def R µ Finite QMatch Ord

2 C

1/N

1-T (udsc)

0.1 0.2 0.3 0.4 0.5

Theory/Data

0.6 0.8 1 1.2 1.4 0.2 0.4 0.6 0.8 1

1/N dN/dC

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia Pythia 8

C Parameter (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + MadGraph 4.426 + Pythia 8.145

0.2 0.4 0.6 0.8 1 Rel.Unc. 1

Def R µ Finite QMatch Ord

2 C

1/N

C (udsc)

0.2 0.4 0.6 0.8 1

Theory/Data

0.6 0.8 1 1.2 1.4 0.2 0.4 0.6 0.8

1/N dN/dD

  • 3

10

  • 2

10

  • 1

10 1 10

L3 Vincia Pythia 8

D Parameter (udsc)

Data from Phys.Rept. 399 (2004) 71 Vincia 1.025 + MadGraph 4.426 + Pythia 8.145

0.2 0.4 0.6 0.8 Rel.Unc. 1

Def R µ Finite QMatch Ord

2 C

1/N

D (udsc)

0.2 0.4 0.6 0.8

Theory/Data

0.6 0.8 1 1.2 1.4

PYTHIA 8 already doing a very good job VINCIA adds uncertainty bands + can look at more exclusive observables?

slide-34
SLIDE 34

Multijet resolution scales

y45 = scale at which 5th jet becomes resolved ~ “scale of 5th jet”

4 6 8 10 12

Rate

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1 10

ALEPH Vincia Pythia 8

Ln(1/y45)

Data from Eur.Phys.J.C 35 (2004) 457 Vincia 1.025 + MadGraph 4.426 + Pythia 8.145

4 6 8 10 12

Rel.Unc.

1

Def R µ Finite QMatch Ord

2 C

1/N

Ln(1/y45)

4 6 8 10 12

Theory/Data

0.6 0.8 1 1.2 1.4 4 6 8 10 12

Rate

  • 4

10

  • 3

10

  • 2

10

  • 1

10 1 10

ALEPH Vincia Pythia 8

Ln(1/y56)

Data from Eur.Phys.J.C 35 (2004) 457 Vincia 1.025 + MadGraph 4.426 + Pythia 8.145

4 6 8 10 12

Rel.Unc.

1

Def R µ Finite QMatch Ord

2 C

1/N

Ln(1/y56)

4 6 8 10 12

Theory/Data

0.6 0.8 1 1.2 1.4

Hard Soft Hard Soft

slide-35
SLIDE 35

4-Jet Angles

0.2 0.4 0.6 0.8 1

Rate

1 2 3 4

Delphi Vincia Pythia 8

Bengtsson-Zerwas Angle

Data from Herwig++ source code Vincia 1.025 + MadGraph 4.426 + Pythia 8.145 0.2 0.4 0.6 0.8 1 Rel.Unc. 1 Def R µ Finite QMatch Ord 2 C 1/N

)

BZ

Χ cos(

0.2 0.4 0.6 0.8 1

Theory/Data

0.6 0.8 1 1.2 1.4

  • 1
  • 0.5

0.5 1

Rate

0.5 1 1.5

Delphi Vincia Pythia 8

Korner-Schierholz-Willrodtorner Angle

Data from Herwig++ source code Vincia 1.025 + MadGraph 4.426 + Pythia 8.145
  • 1
  • 0.5
0.5 1 Rel.Unc. 1 Def R µ Finite QMatch Ord 2 C 1/N

)

KSW

Φ cos(

  • 1
  • 0.5

0.5 1

Theory/Data

0.6 0.8 1 1.2 1.4 0.2 0.4 0.6 0.8 1

Rate

0.5 1 1.5 2 2.5

Delphi Vincia Pythia 8

Nachtman-Reiter Angle

Data from Herwig++ source code Vincia 1.025 + MadGraph 4.426 + Pythia 8.145 0.2 0.4 0.6 0.8 1 Rel.Unc. 1 Def R µ Finite QMatch Ord 2 C 1/N

)|

NR

Θ |cos(

0.2 0.4 0.6 0.8 1

Theory/Data

0.6 0.8 1 1.2 1.4

  • 1
  • 0.5

0.5 1

Rate

0.5 1

Delphi Vincia Pythia 8 34

α

Data from Herwig++ source code Vincia 1.025 + MadGraph 4.426 + Pythia 8.145
  • 1
  • 0.5
0.5 1 Rel.Unc. 1 Def R µ Finite QMatch Ord 2 C 1/N

)

34

α cos(

  • 1
  • 0.5

0.5 1

Theory/Data

0.6 0.8 1 1.2 1.4

Interesting to look at more exclusive observables, but which ones?

4-jet angles

Sensitive to polarization effects

Good News

VINCIA is doing reliably well Non-trivial verification that shower+matching is working, etc.

Higher-order matching needed?

PYTHIA 8 already doing a very good job

  • n these observables