Pythia 8 status report

ATLAS Process Modelling GroupSeptember 04, 2018Stefan Prestel (Lund/Fermilab)

Accurate Monte Carlo predictions

Accurate pseudodata from theory tools → better analyses of backgrounds,better analyses of signals

Colliding composite objects kick-startsmany processes:

hard scatteringradiation cascademultiparton interactionshadronization and decay

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PYTHIA in a nutshell

Beams ee, ep, pp, γx, pA, AA, DMHard scattering Core library of internal processes, oth-

erwise from external tools. NLO+PSmatching/merging with both aMC@NLO andPOWHEG-BOX processes.

Parton shower Three alternative models: Default (w/ andw/o dipole recoil), Vincia and Dire plugins.

Multiparton interactions Regularised secondary 2 → 2 SM scatterings,interleaved with shower evolution.

Soft physics Regge-based diffraction and cross sectionmodels

Fragmentation String hadronization with Schwinger-basedor thermal transition probabilities.

PYTHIA8 convenience features: “Automatic” PS uncertaintiesPYTHIA8 news: PS developments, improved elastic & diffractive crosssections, heavy ions and photons

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I) Hard scattering

Domain of fixed-order and precision calculations. Big community effort,including POWHEG-BOX, MADGRAPH, aMC@NLO & Pythia.

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Matching & merging

Philosophy: Combine multi-jet calculations with each other and with subsequentshower for maximal accuracy.

Matching: Combine {n, n + 1}-partonstates with shower. Overlap handled bysubtraction. Increase precision of inclusiven-parton observables to NLO.

Merging: Combine {n, n+1, . . . , n+m}-parton states with shower. Overlaphandled by cuts & vetoes.

NLO merging: Same as merging, but withsome overlap handled by subtraction. NLOprecision of inclusive n + i-parton observ-ables for well-separated n + i jets.

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Matching & merging: Availability through Pythia + friends

Matchingthrough POWHEG-BOX: works with Pythia shower variations.through aMC@NLO: requires global recoil for first emission.

MergingCKKW-L:default in ATLAS. Partially combined with EW corrections. Currentlynot working with shower variations.MLM: not clear if can work with shower variations.FxFx: more heavily used since more streamlined on aMC-side. not clear ifcan work with shower variations.UNLOPS: implementation in ATLAS underway. Currently not working withshower variations.

OtherDefault Pythia often includes matrix element corrections for 1st splittings.Vincia plugin contains iterated ME corrections as alternative to merging.

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Matching & merging sample plots

…you probably have more than I do.

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Cautionary tales…

EPJC 76 (2016) 1, 39

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Default scheme

EW-improved

10−4

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W → eν (MC) vs W → ℓν (data), dressed level

dσ

W+≥

2j/

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T

200 400 600 800 1000 1200 1400 1600 1800 20000.60.70.80.91.01.11.21.31.4

HT [GeV]

MC

/D

ata

Higher-orders for QCD- and EW corrections very different!Be holistic when e.g. choosing scales (Merging:allowWeakClustering = on)8 / 33

Matching/Merging Questions or Discussion?

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II) Parton showering

Crucial part of physics modeling, as required for jet structure andevolution. NLO+PS only as good as the PS

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Parton shower intro

a

Showers “dress” partons withradiation by iteratively generatingbranchings.

Each generated exclusive state is asolution to an evolution equation.

Summed semi-inclusively, this solu-tion recovers DGLAP evolution.

Summed fully inclusively, the inputcross section is not changed.

These boundary conditions do not determine the cascade completely→ different choices beyond simplest leading terms allowed(ordering/radiation functions/phase space mapping)

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Shower options for Pythia

Current default⋄ Improved DGLAP evolution in p⊥⋄ ME corrections for 1st splitting.⋄ QCD, QED, EW, hidden valley⋄ Extensive tuning expertise.

a

Default with new recoil⋄ Improved DGLAP QCD evoln in p⊥.⋄ Improved (dipole) recoil forDIS/VBF-like processes.⋄ No realistic tune yet.

Vincia plugin⋄ Soft/collinear QCD evolution in1/eikonal⋄ Implements iterated LO matrix el-ement corrections.⋄ Detailed handcrafted tune.

a

Dire plugin⋄ Soft/collinear QCD evolution in1/eikonal⋄ Implements NLO corrections toevolution.⋄ Simple (LO) Professor tune.

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Differences between parton shower optionsarXiv:1803.07977 (LH proceedings 2017)

Le

sHo

uc

he

sS

MW

G2

01

8

CSS

1/4 t ≤ µ2R ≤ 4 t

Dire

1/4 t ≤ µ2R ≤ 4 t

Pythia

1/4 t ≤ µ2R ≤ 4 t

0

0.005

0.01

0.015

0.02

0.025

dσ

/d

ph ⊥

[pb

/G

eV]

a

Theory of default and plugins differs. . . in ordering. . . in radiation functions. . . in treatment of coherence.leading to visible differences.

Shower plugins further handle onuncertainty for shower-sensitiveobservables (jet substructure…)

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Shower variations in PYTHIAarXiv:1605.08352

PYTHIA allows UncertaintyBands:doVariations = on for automatic variations of⋄ µr in shower (fsr:muRfac=0.5 isr:muRfac=0.5…)⋄ finite pieces of splitting kernels (fsr:cNS=2.0 isr:cNS=-2.0…)⋄ PDF members in shower (e.g. isr:PDF:plus, isr:PDF:minus…)VINCIA includes vincia24.cc as illustration (slightly different syntax)DIRE includes dire03.cc as illustration (syntax slightly different) 14 / 33

Peculiarities when varying µP Sq and µP S

r arXiv:1605.08352

µP Sr/q variations will often yield regions with vanishing uncertainty band.

This is expected from “shower unitarity” (area under curve = inclusive x-section)

p⊥evol

dσ/dp ⊥

evol

µpsr =

1

2p⊥evol

µpsr = p⊥evol

µpsr = 2p⊥evol

a

PDF variations can “fill in” some regions. 15 / 33

Parton shower variations with compensation terms

arXiv:1803.07977 (LH proceedings 2017)

Le

sHo

uc

he

sS

MW

G2

01

8

CSS

1/4 t ≤ µ2R ≤ 4 t

Dire

1/4 t ≤ µ2R ≤ 4 t

Pythia

1/4 t ≤ µ2R ≤ 4 t

1 2

10−5

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/d

ph ⊥

[pb

/G

eV]

1 2

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S

1 2

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e

1 10 1 10 2

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[GeV]

Py

thia

a

PS includes many improvementsbeyond leading-order, that mightbe nice to retain when performingvariations

→ Introduce compensating terms.

Drastic reduction realistic?

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(Almost) complete NLO shower vs. uncertainty estimatesarXiv:1805.03757 (S. Höche, F. Dulat, SP)

Dir

eP

S

LO⊕NLO soft

κ/2 ≤ µ ≤ 2κ

LO

κ/2 ≤ µ ≤ 2κ

LO no CMW

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/d

log

10(y

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[nb

]

-4 -3.5 -3 -2.5 -2 -1.5 -1

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log10(y34)

Ra

tio

Le

sHo

uc

he

sS

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G2

01

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CSS

1/4 t ≤ µ2R ≤ 4 t

Dire

1/4 t ≤ µ2R ≤ 4 t

Pythia

1/4 t ≤ µ2R ≤ 4 t

4 3 2 1

10−2

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10 1

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/d

y3

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4 3 2 1

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e

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yDurham34

Py

thia

→ Reduced uncertainty in NLO calculations.→ “Compensated” LO scale variation attempts give much too small &→ distorted band.

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Parton shower Questions or Discussion?

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III) Tuning

A collision is more than “just” perturbative QCD. Heuristic models neededto fill the gaps. Inherent parameters need to be extracted from data →Tuning. 19 / 33

Correlations between pQCD and soft/non-perturbative modelling

Uncertainties:Short-distance cross section:µH

r , µHf , PDFH , αH

s

Parton shower:µP S

q , µP Sr , µP S

f , µP Scut, PDFP S , αP S

s

Multiple interactions:µMP I

q , PDFMP I , αMP Is …

…correlated with:µH

f with shower starting scaleµH

f , PDFH with MPIµP S

q /µHf and PDFP S/PDFH

µP Sr /µH

r and αP Ss /αH

s for NLO+PSµP S

cut with “string p⊥” & “primordial k⊥”αMP I

s and αP Ss

αMP Is and “string tension”

Tough to describe all phenomena, let alone with satisfactory uncertainty.20 / 33

Tuning and correlationsarXiv:1803.07977 (LH proceedings 2017)

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P8, ξ = 2, central

P8, ξ = 2, retune

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Durham jet resolution 3 → 2 (ECMS = 91.2 GeV)

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σd

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(y23)

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MC/Data

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P8, ξ = 2, retune

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MC/Data

Naively, would want to tune only soft/NP parameters using “specialized” observables(nch, nπ,K... scaled momentum). But NP models are very sensitive to perturbativeinput state. ⇒ Soft/NP & perturbative parameters very correlated!

Also, “perturbative” observables can have NP regions as well. Should perturbativevariations degrade the accuracy there? ⇒ One tune per variation?

Results of joint tune/scale variation seem reasonable at LEP. Run once per variation :(21 / 33

Fitting MPI at hadron colliders

Scattering composite objects adds more complexity:Underlying event, modelled by multiparton interactionsAs for fragmentation, fit MPI on “specialized” measurements (chargedmultiplicities, divided into MPI-sensitive and MPI-insensitive regions)

Transverse

Away

Toward

Leading object

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Fitting MPI → Tuning perturbative physics?Plot from arXiv:1512.00815

Hard QCD has considerable impact on tailored MPI observables!But no generator/merging allows consistent transitionMinimum Bias → Dijets with UE → Multijets with UE. 23 / 33

Tuning Questions or Discussion?

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IV) Semi-soft and non-perturbative effects

Non-perturbative models needed to describe the bulk of cross sections atLHC and beyond & offer exciting insights into emergent phenomena.

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Color reconnectionIllustrative plot from arXiv:1505.01681

Many overlapping QCD interactions → collective behavior from colorrearrangement:

→ Reconnection necessary to describe data.New model of arXiv:1505.01681 emphasizes SU(3) selection rules to arrange inputcolor states for string hadronization. Feedback welcome!

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NP processes: Total, elastic and diffractive cross-sectionsPlots from arXiv:1804.10373

Accurate modelling of complete scatteringcross section crucial to understand Min-Bias & UE, and hence jet profiles + pile-up.

Difficult to describe all LHC data w/ oldsingle Pomeron exchange model.⇒ Total + elastic σ updated to two mod-ern parametrizations w/ ≥ 4 exchanges.

Also need to dissect σ into diffractiveand non-diffractive parts to describescatterings with (partially) intact p-beams.⇒ Unification of soft & hard diffraction.

Ready for serious use + feedback fromexperimental bird’s-eye view welcome!

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/GeV

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ABMST

ABMST modified

pp data

√s = 23.7 GeV, t = −0.05 GeV2

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Datab

SaS

SaS + CSCR

ABMST

ABMST mod

10−1

1

10 1

10 2

Rapidity gap size in η starting from η = ±4.9, pT > 200 MeV

dσ

/d

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F[m

b]

0 1 2 3 4 5 6 7 80.50.60.70.80.9

11.11.21.31.4

∆ηF

MC

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ata

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NP processes: Ultra-peripheral collisionsFigures by I. Helenius, arXiv:1510.05900, arXiv:1806.07326

In ultra-peripheral pA or AA collisions, colliding photons can also havenon-perturbative structure & illuminate nuclear PDFs.

1/N

evtdN/d

xA

PbPb,√sNN = 5.02 GeV

anti-kT, R = 0.4pleadT > 20 GeV/cmjets > 35 GeV

PythiaNNPDF2.3EPPS16resolveddirect

Ratio

toNNPDF2.3

xA

PYTHIA implementation ready to use for measurements at pp LHC, e.g.dijets in UPC. Sample usage, see main70.cc. Feedback welcome!

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NP processes: Heavy ion cross sectionsarxiv:1806.10820

High-multiplicity (MinBias) pp collisions already suggest extreme QCDbehavior. How does that relate to the state of matter in heavy ioncollisions?

pA and AA collisions includedthrough Angantyr model:◦ Gives complete event-by-eventfinal state of nucleon-nucleonsubcollisions and of total collision◦ Includes event-by-event fluctua-tions of nucleon wavefunctions.

Pythia ready for pA and AAcollisions (see main112.cc andmain113.cc) 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 b b b b b b b b b b b b b b b b b b b b

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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 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 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 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 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 b b b b b b b bb 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 b b b

ATLASb

Pythia8/Angantyr (generated centrality)

Pythia8/Angantyr (∑ EPb⊥ bins from data)

-2 -1 0 1 20

20

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100(a) Centrality-dependent η distribution, pPb,

√SNN = 5 TeV.

η

(1/

Nev)

dN

ch/

dη

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Collective effects

Collisions at LHC are packeddensely with color.

CR mimics collective effects,but not dynamics.

Model string interactions→ Microscopic model ofcollectivity!

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Collective effectsPlots from arXiv:1710.09725

In 2010, CMS measured long-range azimuthal multiplicity correlations.Repulsive string interactions can reproduce the “ridge” in CMS pp datawith only one parameter on top of PYTHIA.

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IV) Plans

Perturbative side:▶ Consistently combine shower variations and merging▶ Implement matching/merging for Vincia and Dire▶ Improve shower evolution beyond leading color/order (Vincia & Dire)▶ Include Vincia & Dire as core Pythia functionality

Non-perturbative side:▶ Unified photo-production and diffractive framework▶ Extend spacetime picture of hadronization▶ Combine “ropes” with heavy-ion modelling

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V) Summary

▶ Pythia contains sophisticated matching/merging facilities forfixed-order calculations.No real news – need to understand uncertainties & correlation withshowers and tuning. Need to consolidate UNLOPS functionality inATHENA!

▶ Renewed interested in advanced parton shower models:Vincia, Dire, improvements to default shower. Global assessment ofnew models necessary. Use for jet (sub)structure encouraged.

▶ Significant expansion in non-perturbative physics:Better diffraction, new photo-production processes, new heavy ioninteractions. Need feedback from experiment!

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