In-medium transverse momentum broadening effects on di-jet

observablesM. Rohrmosera, K. Kutaka, A. v. Hamerena, W. Płaczekb, K. Tywoniukc

a IFJ-PAN, Kraków, Polandb Uniwersytet Jagielloński, Kraków, Poland

c University of Bergen, Bergen, Norway

Rohrmoser kT broadening in dijets

based on: [arXiv:1911.05463]

Rohrmoser kT broadening in dijets 1

Jets in Heavy Ion collisions

Rohrmoser kT broadening in dijets

Jets interact with medium Jet Quenching!

leading jet

subleading jet

beam axis

pT

φ

probe of the medium

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Jet Production(1/2)

Rohrmoser kT broadening in dijets

Cross section =(u)PDF1*(u)PDF2*hard cross section*fragmentation of jet1*fragmentation of jet2

Here via KATIE

Here via MINCAS

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Jet Production (2/2)

Rohrmoser kT broadening in dijets

kT factorization:

…unintegrated parton densities

full phase space access at LOparticularly relevant at low x

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Coherent Emission

Rohrmoser kT broadening in dijets

: one scattering + radiation…Bethe-Heitler spectrum

: coherent radiation

Look at range:

need effective splitting kernel

cf. [Blaizot, Dominguez, Iancu, Mehtar-Tani: JHEP 1301 (2013) 143 ]

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…à la BDMPS-Z [Baier, Dokshitzer, Mueller, Peigné, Schiff, Zakharov]

BDIM Equation

Rohrmoser kT broadening in dijets

[Blaizot, Dominguez, Iancu, Mehtar-Tani: JHEP 1406 (2014) 075]

Induced Radiation: Scattering:

we use:

For gluon-jets:

Generalizes BDMPS-Z approachIncludes transverse momentum broadening

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Integration over

Momentum distribution:

Momentum transfer:

BDIM Equation as Integral Equation

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[Kutak,Płaczek, Straka: Eur.Phys.J. C79 (2019) no.4, 317]

Monte-Carlo algorithm

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• Select : Probability density:

• Splitting with probabilityotherwise: scattering.

• If splitting, selectprobability density:

• If scattering, selectprobability density

Set/Select and

at

Repeat fornext step in

and or

Stop once

MINCAS

Evolution of D(x,k,t) (1/2)

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Evolution of D(x,k,t) (2/2)

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k Distribution

Rohrmoser kT broadening in dijets

Figure: [Kutak, Płaczek, Straka: Eur.Phys.J. C79 (2019) no.4, 317]

always same distribution for changes→central limit theorem

Splitting à la→ perturbations of different sizes→non Gaussian behavior

Virtual emissions

For example:

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Program: KATIE+MINCAS

• Use KATIE for hard initial collisions: (u)PDFsfor colliding nucleons

Hard collision cross-section (Monte-Carlo simulation)

Resulting particles→initial particles of jets

• Jets: by MINCAS Monte-Carlo simulation of BDIM equation

Time-evolution of jets in medium

Rohrmoser kT broadening in dijets

[Kutak,Płaczek, Straka: Eur.Phys.J. C79 (2019) no.4, 317]

[van Hameren: Comput.Phys.Commun. 224 (2018) 371-380]

Other codes implementing BDMPS-Z:

MARTINI, JEWEL, QPYTHIA, …

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RAA

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Gaussian kT broadening

Rohrmoser kT broadening in dijets

Integrate over

For comparison with full equation: add selected from Gaussian! width:

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Azimuthal Decorrelations

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Azimuthal Decorrelations

Rohrmoser kT broadening in dijets

Normalized to maximum!

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Summary• MINCAS: jet evolution based on coherent emission and scattering

• Combination with KATIE: allows for calculation of jet-observables

• Results differ from pure Gaussian broadening…

• …e.g.: in angular correlations of di-jets,

• But pT distributions seem to be invariant (so far)

Rohrmoser kT broadening in dijets

Outlook• to account for quarks• to study more forward processes

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Back-up slides

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Turbulent behavior (1/2)

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Turbulent behavior (2/2)

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Jet Production

Rohrmoser kT broadening in dijets

Factorization for AA collisions:

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Processes in Jets

Rohrmoser kT broadening in dijets

scattering… …splitting… …induced radiation

Our results: combination of scattering and induced radiation processes!

Transverse momentum transfer!

Scattering Kernel:

Average transfer:

Bremsstrahlung as in vacuum. Momentum distribution:

+Momentum transfer:

Kernel:

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kT Distribution

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kT Distribution

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RAA

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Asymmetry Aj

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