Bayesian Extraction of Jet Energy Loss Distributions in Heavy-Ion Collisions
Yayun He,
1,2
Long-Gang Pang,
2,3,*
and Xin-Nian Wang
1,2,3,†
1
Key Laboratory of Quark & Lepton Physics (MOE) and Institute of Particle Physics,
Central China Normal University, Wuhan 430079, China
2
Nuclear Science Division, Lawrence Berkeley National Laboratory, Berkeley , California 94720, USA
3
Physics Department, University of California, Berkeley, California 94720, USA
(Received 29 August 2018; revised manuscript received 22 November 2018; published 27 June 2019)
Based on the factorization in perturbative QCD, a jet cross section in heavy-ion collisions can be
expressed as a convolution of the jet cross section in p þ p collisions and a jet energy loss distribution.
Using this simple expression and the Markov Chain Monte Carlo method, we carry out Bayesian analyses
of experimental data on jet spectra to extract energy loss distributions for both single inclusive and
γ-triggered jets in Pb þ Pb collisions with different centralities at two colliding energies at the Large
Hadron Collider. The average jet energy loss has a dependence on the initial jet energy that is slightly
stronger than a logarithmic form and decreases from central to peripheral collisions. The extracted jet
energy loss distributions with a scaling behavior in x ¼ Δp
T
=hΔp
T
i have a large width. These are
consistent with the linear Boltzmann transport model simulations, in which the observed jet quenching is
caused on the average by only a few out-of-cone sc atterings.
DOI: 10.1103/PhysRevLett.122.252302
Introduction.—Suppression of jets and large transverse
momentum hadrons known as jet quenching [1,2] in
high-energy heavy-ion collisions is caused by interaction
between jet-shower and medium partons and can be used
to probe properties of the quark-gluon plasma (QGP).
One such fundamental property of QGP is the jet
transport coefficient [3], which characterizes the average
transverse momentum broadening squared per unit length
of a propagating parton and is directly related to the
gluon distribution density of the QGP medium [4]. Its
value at the energy scale of thermal momentum is also
related to the shear viscosity of the QGP [5]. Among
many efforts to extract the jet transport coefficient from
experimental data on suppression of single inclusive
hadron spectra [6–9], the systematic study by the JET
Collaboration [10] has narrowed the uncertainties to
within 40%. Such a systematic approach has still yet
to be applied to other experimental measurements of jet
quenching, such as suppression of single inclusive and
γ-triggered jets.
The study of the medium modification of fully
reconstructed jets in high-energy heavy-ion collisions
[11,12] can provide additional constraints on theoretical
approaches to parton energy loss and th e jet transport
coefficient. Though a fu lly constructed jet cont ain s
partons both from the medium-modified jet-shower
and medium recoil [13–21], one can still define jet
energy loss as the difference between th e final jet
energies within the jet cone in vacuum and medium
originating from the same initial hard parton. While the
average jet energy loss is related to both jet and bulk
transport coefficients, the jet energy loss distribution
should contain additio nal information about jet-medium
interaction. It is important to extract both f rom exper-
imental data.
In this Letter, we first show that starting from the
factorized form of jet cross section, the jet production
cross section in heavy-ion collisions can be expressed as
the convolution of cross section in proton-proton collisions
and a flavor-averaged jet energy loss distribution. Based
on this simple expression, we use the Markov Chain
Monte Carlo (MCMC) method [22] to carry out the first
Bayesian analyses of experimental data on the medium
modification of both single inclusive and γ-triggered jet
spectra and extract jet energy loss distributions in heavy-ion
collisions at two colliding energies at the Large Hadron
Collider (LHC) with different centralities. Previous efforts
have been carried out to extract the averaged jet and parton
energy loss from suppression of single inclusive jet [23]
and hadron spectra [24,25] based on either a simple average
energy loss or one particular model for parton energy loss
distribution. Our study in this Letter uses Bayesian analyses
with uniform prior distributions of parameters to extract
the jet energy loss distribution assuming a p
T
-dependent
average jet energy loss and a scaling behavior of the jet
energy loss distribution.
Published by the American Physical Society under the terms of
the Creative Commons Attribution 4.0 International license.
Further distribution of this work must maintain attribution to
the author(s) and the published article’s title, journal citation,
and DOI. Funded by SCOAP
3
.
PHYSICAL REVIEW LETTERS 122, 252302 (2019)
0031-9007=19=122(25)=252302(6) 252302-1 Published by the American Physical Society
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