Measurement of the centrality dependence of inclusive jet production in p + Pb data at √

ATLAS-CONF-2013-105 04November2013

ATLAS NOTE

ATLAS-CONF-2013-10

November 2, 2013

Measurement of the centrality dependence of inclusive jet production in p + Pb data at √

s

_NN

= 5.02 TeV with the ATLAS detector

The ATLAS Collaboration

Abstract

ATLAS has measured the centrality dependence of jet production in

√

s_NN =

5.02 TeV

p+

Pb collisions at the LHC. The

p+

Pb collision centrality was characterized using the total transverse energy measured in the pseudorapidity interval 3.2

< η <

4.9 in the direction of the lead beam. Jets were reconstructed from energy deposits measured in the ATLAS calorimeter using the anti-k

t

algorithm with

R=

0.4. The per-event jet yields were measured in di

ff

erent centrality selections as a function of jet rapidity and transverse momentum (

p_T

).

The ratios of jet spectra between different centrality selections, corrected for the centrality dependent partonic luminosities, show a strong suppression of jet production at all

p_T

at forward rapidities and at large

p_T

at mid-rapidity.

c

Copyright 2013 CERN for the benefit of the ATLAS Collaboration.

Reproduction of this article or parts of it is allowed as specified in the CC-BY-3.0 license.

1 Introduction

Proton–lead ( p

+

Pb) collisions at the Large Hadron Collider (LHC) provide a unique opportunity to study possible violations of factorisation in hard scattering processes involving a nuclear projectile [1].

Previous studies in deuteron-gold (d

+Au) collisions at RHIC showed such violations in the suppressed

production of very forward hadrons with transverse momenta up to 4 GeV [2, 3, 4]. Studies of forward dihadron angular correlations at RHIC also showed a much weaker dijet signal in d

+Au collisions than in

pp collisions [4, 5]. These effects have been attributed to saturation of the parton distributions in the gold nucleus [6, 7, 8], to the nuclear parton distribution function [9], or to the higher-twist contributions to the cross-section enhanced by the forward kinematics of the measurement [10] or the presence of a large nucleus [11]. The extended kinematic reach of p

+Pb measurements at the LHC allows the study of hard

scattering processes that produce forward hadrons or jets over a much wider rapidity and p

_T

range. Such measurements can determine whether the factorisation violations observed at RHIC persist at higher energy and, if so, how the resulting modifications vary as a function of particle or jet p

_T

. The results of such measurements could test the competing descriptions of the RHIC results, and, more generally, provide new insight into the physics of hard scattering processes involving a nuclear target.

ATLAS has measured the centrality dependence of high-p

T

jet production in p

+Pb collisions at

√

s

_NN =

5.02 TeV. The measurement was performed using a data set corresponding to an integrated luminosity of 31 nb

⁻¹

recorded in 2013. Jets were reconstructed from energy deposits measured in the ATLAS calorimeter using the anti-k

t

algorithm with R

=

0.4 [12]. The centrality of p

+Pb collisions was

characterised using the total transverse energy measured in the pseudorapidity interval 3.2 < η < 4.9 in the direction of the lead beam. A Glauber model [13] was used to determine the average number of nucleon-nucleon collisions,

hN_colli, in each centrality interval. The centrality dependence of per-event

jet yields, (1/N

evt

)(d

²

N

_jet

/d p

T

dy), was evaluated using the central-to-peripheral ratio,

R

^cent_CP ≡

1 R

_coll

1/N

_evt^cent

d

²

N

_jet^cent

/d p

_T

dy 1/N

_evt^periph

d

²

N

_jet^periph

/d p

_T

dy , (1) where R

_coll

represents the ratio of the

hN_colli

value in a given centrality interval to that in the most pe- ripheral interval included in the analysis, R

_coll≡ hN_colli/hN_coll^periphi. The

R

_CP

measurements are presented as a function of the centre-of-mass rapidity, y

^∗

, and jet transverse momentum. The R

_CP

is sensitive to relative modifications in the jet rate between the p

+Pb event centralities and the geometric expectation.

In addition to R

_CP

, results are presented for the nuclear modification factor R

PYTHIA,cent

pPb ≡

1

T

_pA

1/N

_evt^cent

d

²

N

_jet^cent

/d p

_T

dy

d

²

σ

_jet^pp

/d p

_T

dy , (2) where T

_pA

is the mean value of the nuclear overlap function T

_pA

(b)

=R₊∞

−∞

ρ(b, z)dz in the given central- ity interval, where ρ(b, z) is the nucleon density at impact parameter b and longitudinal position z, and d

²

σ

_jet^pp

/d p

_T

dy is a PYTHIA MC reference for the pp jet cross-section at

√

s

=

5.02 TeV. The R

^PYTHIA_pPb

quantifies the absolute modification in the jet rate relative to the geometric expectation.

For the 2013 p

+

Pb run, the LHC was configured with a 4 TeV proton beam and a 1.57 TeV per- nucleon Pb beam that together produced collisions with a nucleon–nucleon centre-of-mass energy of

√

s

_NN=

5.02 TeV and a rapidity shift of

−0.47 relative to the ATLAS rest frame¹

. The run was split into

1ATLAS uses a right-handed coordinate system with its origin at the nominal interaction point (IP) in the centre of the detector and thez-axis along the beam pipe. Thex-axis points from the IP to the centre of the LHC ring, and they-axis points upward. Cylindrical coordinates (r, φ) are used in the transverse plane,φbeing the azimuthal angle around the beam pipe. For the p+Pb collisions, the incident Pb beam travelled in the+zdirection for the first period of data-taking and in the reverse direction for the second period. The pseudorapidity is defined in laboratory coordinates in terms of the polar angleθas η=−ln tan(θ/2).

two periods, with the directions of the proton and lead beams being reversed at the end of the first period.

The first period provided approximately 55% of the integrated luminosity with the Pb beam travelling to positive rapidity and the proton beam to negative rapidity, and the remainder with the beams reversed.

The data analysed in this note are comprised from both periods of data-taking, and the centre-of-mass rapidity, y

^∗

, is defined so that y

^∗

< 0 always refers to the downstream proton direction.

2 Experimental setup

The measurements presented in this note are performed using the ATLAS calorimeters, inner detector (ID), minimum-bias trigger scintillators (MBTS), and trigger and data acquisition systems [14]. The ID measures charged particles within

|η|

< 2.5 using a combination of silicon pixel detectors, silicon micro- strip detectors, and a straw-tube transition radiation tracker, all immersed in a 2 T axial magnetic field [15]. The ATLAS calorimeter system consists of a liquid argon (LAr) electromagnetic (EM) calorimeter covering

|η|

< 3.2, a steel-scintillator sampling hadronic calorimeter covering

|η|

< 1.7, a LAr hadronic calorimeter covering 1.5 <

|η|

< 3.2, and two LAr electromagnetic and hadronic forward calorimeters (FCal) covering 3.2 <

|η|

< 4.9. The EM calorimeters are longitudinally segmented into three compart- ments with an additional pre-sampler layer. The EM calorimeter has a granularity that varies with layer and pseudorapidity. The middle sampling layer, which typically has the largest energy deposit in EM showers, has a

∆

η

×∆

φ granularity of 0.025

×

0.025 over

|η|

< 2.5. The hadronic calorimeter has three longitudinally segments with cell sizes

∆

η

×∆

φ

=

0.1

×

0.1 for

|η|

< 2.5 and 0.2

×

0.2 for 2.5 <

|η|

< 4.9

²

. The FCal consists of two sections that cover 3.1 <

|η|

< 4.9. The FCal modules are composed of tung- sten and copper absorbers with liquid argon as the active medium, which together provide 10 interaction lengths of material. The MBTS detect charged particles over 2.1 <

|η|

< 3.9 using two hodoscopes of 16 counters positioned at z

= ±3.6 m. The events used in this analysis were recorded using a combination

of minimum-bias and jet triggers [16]. The minimum-bias trigger required hits in at least one counter in each side of the MBTS detector. The jet triggers were formed from a combination of minimum-bias or jet Level-1 triggers and high-level jet triggers implemented with a reconstruction algorithm similar to that applied in the o

ffl

ine analysis. Multiple jet trigger thresholds ranging from 20 GeV to 75 GeV were used with pre-scales that varied with time to accommodate the evolution of the luminosity within an LHC fill.

3 Data selection

In the offline analysis, charged particle tracks were reconstructed in the ID using an algorithm optimised for pp minimum-bias measurements [17]. The p

+

Pb events used for this analysis were required to have a reconstructed vertex containing at least two associated tracks, at least one hit in each of the two MBTS hodoscopes, and a difference between times measured on the two sides of less than 10 ns. Events containing multiple p

+

Pb collisions (pileup) were suppressed by rejecting events with two reconstructed vertices which were associated with

Σ

p

_T

> 5 GeV of reconstructed tracks. Events with a rapidity gap (defined by the absence of calorimeter clusters) of greater than two units on the Pb-going side of the detector were also removed from the analysis. Such events arise primarily from electromagnetic or di

ff

ractive excitation of the proton. The integrated luminosity after event selection corresponds to approximately 25 nb

⁻¹

.

The centrality of the p

+

Pb events selected for analysis was characterised by the total transverse energy in the Pb-going FCal,

ΣE_T^Pb

. The

ΣE^Pb_T

distribution for minimum-bias p

+

Pb collisions passing the above-described event selections is presented in Fig. 1. Following standard techniques [18], centrality

2An exception is the third (outermost) sampling layer, which has a segmentation of 0.2×0.1 up to|η|=1.7.

[GeV]

Pb

E

T

Σ

0 100 200

]

-1

[GeV

Pb T

E Σ /d N d

evt

N 1/

10

-6

10

-5

10

-4

10

-3

10

-2

ATLAS Preliminary

= 5.02 TeV sNN

p+Pb, = 31 nb-1

Lint

Figure 1:

ΣE_T^Pb

distribution for minimum-bias p

+

Pb collisions recorded during the 2013 run. The vertical divisions correspond to the six centrality intervals used in this work. The right-most region corresponds to the 0-10% events, and the second from left region is the 60-90%.

intervals were defined in terms of percentiles of the

ΣE^Pb_T

distribution after accounting for an estimated ine

ffi

ciency of 2

±

2% for inelastic p

+

Pb collisions to pass the applied event selections. The following centrality intervals were used in this analysis, in order from most central to most peripheral: 0–10%, 10–20%, 20–30%, 30–40%, 40–60%, 60–90%, with the 60-90% interval serving as the reference in the R

_CP

. Using procedures from Ref. [19] a Glauber Monte Carlo [13, 20] analysis was used to calculate the average number of nucleon-nucleon collisions,

hN_colli

, and T

_pA

for each of the centrality intervals. The resulting R

_coll

and T

_pA

values and corresponding uncertainties are shown in Table 1. These values agree with those obtained for the 2012 pilot p

+

Pb run [19] to better than 1%.

4 Monte Carlo sample

The performance of the jet reconstruction algorithms was evaluated using Monte Carlo (MC)

√

s

=

5.02 TeV pp dijet events generated using PYTHIA6 [21] (version 6.425, AMBT2 tune [22], CTEQ6L1 PDFs) and fully simulated using GEANT4 [23, 24]. Several samples of such events were produced for di

ff

erent intervals of generator-level R

=

0.4 “truth” jet p

_T

that spanned 10 < p

_T

< 800 GeV. Separate sets of 3.25 million events each were generated for the two di

ff

erent beam directions. For each beam di- rection, the momentum four-vectors of the generated particles were longitudinally boosted by a rapidity of

±0.465 to match the corresponding beam conditions. The simulated events were digitised using data

conditions appropriate to the two periods of the 2013 p

+

Pb run and reconstructed using the same algo- rithms that were applied to the experimental data. A separate sample of 12 million events was obtained by overlaying simulated

√

s

=

5.02 TeV pp dijet collisions on to minimum-bias p

+

Pb events recorded

during the 2013 run. These events were used to evaluate the impact of the underlying event (UE) on the

jet reconstruction for jet p

_T

< 200 GeV.

Centrality

R

_coll

T

_pA

[mb

⁻¹

] 0-90% - 0.106

⁺_−0.003^0.004_+4.0%

−3.0%

60-90% - 0.043

⁺_−0.004^0.003_+7.0%

−9.7%

40-60% 2.16

⁺₋^0.08_0.07+3.8%

−3.2%

0.092

⁺_−0.006^0.004_+4.7%

−6.8%

30-40% 3.00

^+0.21_−0.14+7.1%

−4.6%

0.126

^+0.003_{−0.004+2.7%}

−3.3%

20-30% 3.48

^+0.33_−0.18+9.4%

−5.0%

0.148

^+0.004_{−0.002+2.4%}

−1.7%

10-20% 4.05

^+0.49_{−0.21+12.2%}

−5.3%

0.172

^+0.007_{−0.003+4.1%}

−1.7%

0-10% 4.89

^+0.83_{−0.27+16.9%}

−5.5%

0.208

^+0.019_{−0.005+9.1%}

−2.3%

Table 1: Average R

_coll

and T

_pA

values for the centrality intervals used in this analysis along with total systematic uncertainties expressed both as absolute and relative uncertainties. The R

_coll

values are with respect to 60-90% events, where

hN_colli=

2.98

⁺_−0.29^0.21

.

5 Jet reconstruction

The jet reconstruction and UE subtraction procedures were adapted from those used by ATLAS in Pb+Pb collisions, which are described in detail in Refs. [25, 26], and are summarised in the following. Calorime- ter cells were combined into towers with segmentation

∆

η

×∆

φ

=

0.1

×

0.1, and the anti-k

t

algorithm was applied to the towers. A two-step iterative procedure was used to obtain an event-by-event estimate of the UE energy density while excluding contributions from jets to that estimate. This estimate of the UE was constructed separately in each calorimeter layer and in

∆

η

=

0.1 strips to accommodate the

η-dependent variations in UE activity present in p

+Pb collisions. For each tower included in a given jet,

the UE energy for cells in the tower was subtracted to correct the cell energy. The jet kinematics were then constructed to be the four-vector sum of all such cells, taking the four-vectors to be massless. The mean subtracted UE energy was 2.4 GeV (1.4 GeV) for jets with

|y^∗|

< 1 (y

^∗

<

−3).

At the analysis stage, a small correction, typically a few per cent, was applied to the transverse momentum of those jets which were erroneously included in the background estimate. Finally, the jet energies were corrected to account for the calorimeter energy response using an η- and E

_T

-dependent multiplicative factor that was derived from the MC simulations [27].

6 Performance

The jet reconstruction capabilities were evaluated in the MC samples by applying the same subtraction and reconstruction procedure as was applied to data. The resulting set of reconstructed jets was compared with their corresponding generator jets, which were produced by applying the anti-k

t

algorithm to the final-state particles produced by PYTHIA. Each generator jet was matched to a reconstructed jet and the di

ff

erence in p

_T

between the two jets was studied as a function of jet p

_T

and η. The reconstruction efficiency for p

_T

> 25 GeV jets is > 99%. The performance is quantified by the means and standard deviations of the

∆

p

_T

/ p

_T

distributions, referred to as the jet energy scale (JES) closure and jet energy resolution (JER), respectively. The JES and JER are shown in Figure 2 for selected rapidity bins. The closure is better than

≤

1% at all p

_T

> 25 GeV, and

≤

0.5% in the majority of the p

_T

and rapidity bins.

Response matrices were populated by recording each generator-reconstructed jet pair and were con-

structed separately for each y

^∗

interval used in the analysis. These are shown in Figure 3 for a selection

[GeV]

truth

pT

JES Closure

-0.02 0 0.02 0.04 0.06

20 100 1000

* < +0.3 y

-0.3 <

* < -0.8 y

-1.2 <

* < -2.1 y

-2.8 <

* < -3.6 y

-4.4 <

[GeV]

truth

pT

JER

0.05 0.1 0.15 0.2

20 100 1000

ATLAS Simulation Preliminary +Pb, 5.02 TeV

p

, R=0.4 k

t

anti-

Figure 2: Jet energy scale closure (JES Closure, left plot) and jet energy resolution (JER, right plot) for

√

s

=

5.02 TeV, R

=

0.4 jets in select rapidity bins.

of rapidity bins in the pure PYTHIA

√

s

_NN =

5.02 TeV MC. These matrices quantify the amount of p

_T

migration introduced by the reconstruction procedure and detector response. For the p

_T

ranges studied in these results, the proportion of jets with reconstructed p

_T

in the same bin as their truth p

_T

monotoni- cally increases with truth p

_T

and is 50-70%. The effects of the UE on the jet response in different p

+Pb

centralities has been evaluated using the MC overlay sample. The centrality dependence in the response decreases with increasing jet p

_T

, and the MC overlay sample is used to determine the p

_T

range for which the UE effects are negligible in all centrality intervals studied.

7 Data Analysis

Jets in p

+Pb collisions are selected by the minimum-bias triggers and jet triggers described above. In

total, six trigger thresholds are used in p

+

Pb data-taking for jets in

|η|

< 3.2 and a low-threshold trigger for jets in

|η|

> 3.2. The sampled luminosity (defined as the luminosity divided by the mean prescale) of the jet triggers increases with increasing trigger threshold. The efficiency of the various triggers was determined with respect to the minimum-bias trigger and to low-p

T

jet triggers, requiring the same association of the o

ffl

ine jet to an online trigger jet as is used to select triggered o

ffl

ine jets. For simplicity, each p

_T

bin is filled with jets selected by only one trigger. In a given p

_T

bin, jets are selected by the lowest-threshold jet trigger for which the e

ffi

ciency has been determined to be > 99%. No additional corrections for the trigger e

ffi

ciency are applied.

The detector level per-event jet yields in p

+Pb collisions are constructed via

1

N

_evt

d

²

N

^jet

d p

_T

dy

^∗ =

1

N

_evt

N

^jet

∆

p

_T∆

y

^∗

(3)

where N

_evt

is the total (unprescaled) number of MB events sampled by ATLAS, N

^jet

is the trigger-selected

yield of jets, corrected for the instantaneous trigger prescale during data-taking, and

∆

p

_T

and

∆

y

^∗

are the

widths of the p

_T

and y

^∗

bins. The centrality-dependent yields are constructed by restricting N

_evt

and N

^jet

to come from p

+Pb events with a given range ofΣ

E

^Pb_T

.

102 10³

[GeV]

reco T

p

10 100 1000

* < +0.3 y

-0.3 <

[GeV]

antikt4Truth pT

102 10³

[GeV] Tantikt4HIItrEM p

102

103

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

1 10 102

103

* < -0.8 y

-1.2 <

[GeV]

truth

p

T

[GeV]

reco T

p

* < -2.8 y

-2.1 <

10 100 1000

10 100 1000

[GeV]

truth

p

T

102

103

10-9

10-8

10-7

10-6

10-5

10-4

10-3

10-2

10-1

1 10 102

103

10 100 1000

* < -4.4 y

-3.6 <

ATLAS Simulation Preliminary +Pb, 5.02 TeV

p

, R=0.4 k

t

anti-

Figure 3: R

=

0.4 jet p

_T

response matrices in indicated rapidity intervals obtained from simulations of the ATLAS detector response to PYTHIA-generated jets (see text).

Furthermore, the per-event yields in p

+Pb collisions are restricted to the

p

_T

range where the MC studies described above have determined that the jet response in the calorimeter is independent of the p

+

Pb centrality. This range is rapidity-dependent. This range is p

_T

> 100 GeV for jets in

−0.3

< y

^∗

<

+0.3, but the lower

p

_T

cutoff decreases monotonically with more forward rapidity bins. In the most forward rapidity interval,

−4.4

< y

^∗

<

−3.6, where the centrality dependence of the underlying event

e

ff

ects is vanishing at all p

_T

, yields are reported for jets with p

_T

> 25 GeV.

The detector level measurements of the p

+Pb yields are corrected for jet energy resolution and resid-

ual distortions of the jet energy scale in each rapidity interval by the use of p

_T

-dependent bin-by-bin

correction factors C

^pPb

( p

_T

, y

^∗

) obtained from the ratio of the reconstructed and truth jet distributions,

according to

C

^pPb

( p

_T

, y

^∗

)

=

N

_truth^jet

(p

T

, y

^∗

) N

_reco^jet

(p

T

, y

^∗

)

(4) where N

_truth^jet

(N

_reco^jet

) is the number of truth jets in the given p

^truth_T

( p

^reco_T

) bin in the 5.02 TeV MC.

Since the determination of the correction factors is sensitive to the shape of the MC truth jet distri- bution, the transfer matrices used to generate them were re-weighted to provide a better match between the reconstructed MC and data distributions. A separate reweighting was performed for the p

+Pb jet

yield in each centrality interval, resulting in changes of 1-5% from the original correction factors be- fore reweighting. The final correction on the p

+

Pb yields is at most 20%, and is typically

≤

10% for p

_T

> 50 GeV. These corrections are applied to give the particle-level per-event yield in p

+Pb collisions,

1 N

_evt

d

²

N

^jet

d p

_T

dy

^∗

_corr

=

C

^pPb

( p

_T

, y

^∗

) 1 N

_evt

d

²

N

^jet

d p

_T

dy

^∗

_uncorr

(5)

8 Systematic Uncertainties

The R

_CP

and R

^PYTHIA_pPb

measurements are subject to systematic uncertainties due to uncertainties in the jet energy scale (JES) and resolution (JER), uncertainties on the bin-by-bin corrections from the di

ff

er- ences in the spectral shape between data and MC, an uncertainty from residual ine

ffi

ciency in the trigger selection, and the uncertainty on estimates of the geometric quantities R

_coll

(in the R

_CP

) and T

_pA

(in the R

^PYTHIA_pPb

).

Uncertainties in the JES and JER influence the correction of the p

+

Pb spectra. The uncertainty in the JES is taken from in situ ATLAS studies of the calorimeter response and systematic variations in the jet response in MC simulation [27], and the uncertainty in the JER is taken from in situ studies of the dijet energy balance [28]. The JES uncertainty is

.

4% for jets in the measured p

_T

range in

|y^∗|

< 2.8, and

.

11% for jets in

|y^∗|

> 2.8. The JER uncertainty is 10-20% for the kinematic range of jets used in this work. The resulting systematic uncertainties in the R

_CP

(δR

^sys_CP

) and R

^PYTHIA_pPb

(δR

^PYTHIA,sys_pPb

) were evaluated by producing new response matrices, generating new correction factors, and calculating the new R

_CP

and R

^PYTHIA_pPb

results. Since the correction factors for the p

+Pb spectra are affected to a similar

degree by variations in the JES and JER, the e

ff

ects tend to cancel in the R

_CP

ratio, and the resulting δR

^sys_CP

are small. This is not the case for the R

^PYTHIA_pPb

. Since the p

+

Pb yields are only measured in a p

_T

range where the response has been determined to be independent of the p

+Pb event centrality, no

centrality-dependent uncertainties in the JES or JER are considered.

Furthermore, di

ff

erences in the spectral shape between data and MC create the need for bin-by-bin correction factors to reweight the MC for better correspondence with the data. Conservatively, the entire change in the results introduced by the reweighting is taken as a systematic uncertainty. Thus, the R

_CP

and R

^PYTHIA_pPb

are determined using the correction factors before and after reweighting, with the di

ff

erences δR

^sys_CP

and δR

^PYTHIA,sys_pPb

added to the total systematic uncertainty.

As the jet triggers used for the data selection have been evaluated to have > 99% efficiency in the respective p

_T

regions where they are used to select jets, an uncertainty of 1% is chosen for the centrality selected p

+Pb yields in the range 20

< p

_T

< 125 GeV. This uncertainty is taken to be uncorrelated between the p

+Pb centralities, resulting in a 1.4% uncertainty on the

R

_CP

when added in quadrature from the numerator and denominator in these quantities and 1% on the R

^PYTHIA_pPb

.

Table 2 shows the typical size of the systematic uncertainty from the various sources described above on the R

_CP

and the R

_pPb

in two rapidity bins.

The geometric quantities R

_coll

and T

_pA

and their uncertainties are listed in Table 1. In general, the

uncertainties are asymmetric. Uncertainties in R

_coll

are largest for the most central to most peripheral

−0.3

< y

^∗

<

+0.3 −2.8

< y

^∗

<

−2.1 Uncertainty source

R

_CP

R

^PYTHIA_pPb

R

_CP

R

^PYTHIA_pPb

Jet energy scale 1% 7-9% 2% 15-30%

Jet energy resolution 1% 1-2% 1-4% 4-16%

Shape uncertainty 2-3% 1-2% 3-4% 1-2%

Trigger selection 1% 1% 1% 1%

Table 2: Summary of the various sources of systematic uncertainty and their estimated impact on the R

_CP

and R

_pPb

measurement in two rapidity bins.

ratio (0-10%/60-90%), where they are

+16/−

6%, and smallest in the 40-60%/60-90% ratio, where they are

+

4/

−

3%. Uncertainties in T

_pA

are largest in the most central (0-10%) and most peripheral (60-90%) centrality intervals, where they reach

±9%, and smaller for intervals in the middle of the

p

+

Pb centrality range, where the reach a minimum of

+3/−

2% for the 20-30% interval.

9 Results

The corrected R

_CP

and R

^PYTHIA_pPb

are presented in Figures 4, 5, 6 and 7. In each figure, the systematic uncertainties from the energy scale and resolution, the MC corrections and trigger efficiency are shown as boxes around each data point. The systematic uncertainties from R

_coll

(in the R

_CP

) and T

_pA

(in the R

^PYTHIA_pPb

) are independent of p

_T

and y

^∗

and are shown as shaded boxes on the edges of the horizontal dotted line at 1.

Figure 4 shows the R

_CP

for R

=

0.4 jets in fixed rapidity bins. The R

_CP

shows a strong variation with centrality relative to the geometric expectation. The 0-10%/60-90% R

_CP

is suppressed at mid-rapidity for p

_T

> 150 GeV jets and at all p

_T

at sufficiently forward rapidity. Near mid-rapidity, the 40-60%/60-90%

R

_CP

is consistent with unity up to 100-200 GeV, but indicates a small suppression at higher p

_T

. In all rapidity bins studied, the R

_CP

decreases with increasing p

_T

and in more central collisions.

To illustrate better the rapidity dependence of the R

_CP

, Figure 5 shows the R

_CP

in fixed centrality windows with multiple rapidities in each panel. The plots on the left side show that at fixed p

_T

, the R

_CP

systematically decreases with more forward rapidity. Given the suppression pattern as a function of rapidity, a natural question is if it is possible to find a single relationship in the rapidity bins as a function of jet kinematics alone. To test this, the R

_CP

in each rapidity bin is plotted against the quantity p

_T×

cosh(y

^∗

)

≈

p, where y

^∗

is the centre of the rapidity bin, and p is therefore approximately the total energy of the jet. This is plotted on the right plots in Figure 5. When plotted against this variable, the R

_CP

in each of the rapidity bins shown falls along the same line. The slope of the common R

_CP

vs.

p

_T×

cosh(y

^∗

) curve is di

ff

erent in each centrality interval (two of which are shown in the Figure).

As an evaluation of the total jet rate in p

+Pb, the

R

_pPb

is made using a PYTHIA truth jet spectrum as the reference (called the R

^PYTHIA_pPb

) and is shown in Figure 6. In all rapidity bins studied, the R

^PYTHIA_pPb

is slowly increasing with p

_T

due to a slight di

ff

erence in the spectra shape between data and MC, rang- ing from

≈

0.8-1.2 depending on the jet p

_T

. This shows that despite the strong effects observed in the centrality-dependent R

_CP

, we do not observe a modification of the total yield of jets relative to the geometric expectation.

Figure 7 shows the R

^PYTHIA_pPb

in different centrality intervals. The central (0-10%) and peripheral

(60-90%) R

^PYTHIA_pPb

are observed to have a larger and smaller slope than the inclusive R

^PYTHIA_pPb

. Thus,

CP

R

0.2 0.4 0.6 0.8 1

1.2 -0.3 < y * < +0.3

40-60%/60-90%

30-40%/60-90%

20-30%/60-90%

10-20%/60-90%

0-10%/60-90%

CP

R

0.2 0.4 0.6 0.8 1 1.2

ATLAS Preliminary

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

, R=0.4 k

t

anti-

* < -0.8 y

-1.2 <

CP

R

0.2 0.4 0.6 0.8 1

1.2 -2.1 < y * < -1.2 _R

^CP

0.2 0.4 0.6 0.8 1

1.2 -2.8 < y * < -2.1

CP

R

0.2 0.4 0.6 0.8 1 1.2

20 100 500

[GeV]

p

T

* < -2.8 y

-3.6 < R

^CP

0.2 0.4 0.6 0.8 1 1.2

[GeV]

p

T

* < -3.6 y

-4.4 <

20 100 500

Figure 4: R

_CP

for R

=

0.4 jets in

√

s

_NN =

5.02 TeV p

+Pb collisions. Each panel shows the jet

R

_CP

in multiple centrality intervals at a fixed rapidity bin. Error bars on data points represent statistical

9

CP

R

0.2 0.4 0.6 0.8 1

1.2

0-10%/60-90%

R^CP

0.2 0.4 0.6 0.8 1

1.2

0-10%/60-90%

, R=0.4 k

t

anti-

ATLAS Preliminary

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

CP

R

0.2 0.4 0.6 0.8 1

1.2 30-40%/60-90%

[GeV]

p

T

20 100 500

* < -0.3 y

-0.8 <

* < -0.8 y

-1.2 <

* < -1.2 y

-2.1 <

CPR

0.2 0.4 0.6 0.8 1

1.2

30-40%/60-90%

*) [GeV]

y cosh(

T

× p

100 1000

* < -2.1 y

-2.8 <

* < -2.8 y

-3.6 <

* < -3.6 y

-4.4 <

Figure 5: R

_CP

for R

=

0.4 jets in

√

s

_NN =

5.02 TeV p

+Pb collisions. Each panel shows the

R

_CP

in jets in multiple rapidity bins at a fixed centrality interval. The top row show the R

_CP

for 0-10%

/

60-90%

and the bottom row show the R

_CP

for 30-40%/60-90%. In the left column, the R

_CP

is plotted against jet

p

_T

. In the right column, the R

_CP

is plotted against the quantity p

_T

cosh(y

^∗

) where y

^∗

is the midpoint of

the rapidity bin. Error bars on data points represent statistical uncertainties, boxes represent systematic

uncertainties, and the shaded box on the R

_CP=

1 dotted line indicates the systematic uncertainty on R

_coll

for that centrality interval.

pPbR

0.2 0.4 0.6 0.8 1

0-10%

R^CP

0.2 0.4 0.6 0.8 1

0-10%

* < -1.2 y

-0.8 <

* < -2.8 y

-2.1 <

* < -3.6 y

-4.4 <

pPbR

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4

60-90%

[GeV]

p

T

20 100 500

CPR

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2

2.4

60-90%

*) [GeV]

y cosh(

T

× p

100 1000

, R=0.4 k

t

anti-

ATLAS for Approval

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

+0.3 < y * < +0.8

0-90%

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

-0.3 < y * < +0.3

ATLAS Preliminary

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

, R=0.4 k

t

anti-

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -1.2 < y * < -0.8

[GeV]

p

T

20 100 1000

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -2.8 < y * < -2.1

[GeV]

p

T

20 100 1000

Figure 6: R

^PYTHIA_pPb

for R

=

0.4 jets for 0-90% events in

√

s

_NN =

5.02 TeVp

+

Pb collisions. Each panel

shows the R

^PYTHIA_pPb

in jets in a di

ff

erent centre-of-mass rapidity bin. Error bars on data points represent

statistical uncertainties, boxes represent systematic uncertainties, and the shaded box on the R

^PYTHIA_pPb =

1

dotted line indicates the systematic uncertainty on T

_pA

.

pPbR

0.2 0.4 0.6 0.8 1

0-10%

R^CP

0.2 0.4 0.6 0.8 1

0-10%

* < -1.2 y

-0.8 <

* < -2.8 y

-2.1 <

* < -3.6 y

-4.4 <

pPbR

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.4

60-90%

[GeV]

p

T

20 100 500

CPR

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2

2.4

60-90%

*) [GeV]

y cosh(

T

× p

100 1000

, R=0.4 k

t

anti-

ATLAS for Approval

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

+0.3 < y * < +0.8

0-90%

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

-0.3 < y * < +0.3

ATLAS Preliminary

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

, R=0.4 k

t

anti-

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -1.2 < y * < -0.8

[GeV]

p

T

20 100 1000

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -2.8 < y * < -2.1

[GeV]

p

T

20 100 1000

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

+0.3 < y * < +0.8

0-10%

20-30%

60-90%

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8

-0.3 < y * < +0.3

ATLAS Preliminary

= 31 nb

-1

L

int

+Pb, 5.02 TeV, p

, R=0.4 k

t

anti-

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -1.2 < y * < -0.8

[GeV]

p

T

20 100 1000

PYTHIA pPb

R

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6

1.8 -2.8 < y * < -2.1

[GeV]

p

T

20 100 1000

Figure 7: R

^PYTHIA_pPb

for R

=

0.4 jets in

√

s

_NN=

5.02 TeV p

+Pb collisions. Each panel shows the

R

^PYTHIA_pPb

in jets in multiple centrality intervals at a fixed rapidity bin. Error bars on data points represent statistical

uncertainties, boxes represent systematic uncertainties, and the shaded boxes on the R

^PYTHIA_pPb =

1 dotted

line indicate the systematic uncertainties on T

_pA

for each centrality interval.

the strong modification in the R

_CP

is consistent with a combination of modifications in the R

^PYTHIA_pPb

that have opposite effects in central (a suppression relative to the inclusive R

^PYTHIA_pPb

) and peripheral (an enhancement relative to the inclusive R

^PYTHIA_pPb

) p

+Pb events.

10 Conclusions

This note has presented the results of a measurement of the centrality dependence of jet production in p

+

Pb collisions at

√

s

_NN =

5.02 TeV over a wide rapidity range. The centrality of p

+

Pb collisions was characterised using the total transverse energy measured in the Pb-going forward calorimeter covering the interval 3.2 <

|η|

< 4.9. The average number of nucleon-nucleon collisions, N

_coll

, and the nuclear thickness factor, T

_pA

, were evaluated for each centrality interval using a Glauber Monte Carlo analy- sis. Results were presented for the central-to-peripheral ratios, R

_CP

, and nuclear modification factors, R

^PYTHIA_pPb

, as a function of jet p

_T

and centre-of-mass rapidity y

^∗

. The results of the measurement indicate a strong, centrality-dependent reduction in the yield of jets in central collisions relative to that in periph- eral collisions, after accounting for the e

ff

ects of collision geometry. In addition, the reduction becomes more pronounced with jet p

_T

and at more forward (downstream proton) rapidities. When the data are re-plotted as a function of p

_T

cosh y

^∗

, the results from di

ff

erent rapidity bins fall into roughly a single trend suggesting that the mechanism responsible for the observed e

ff

ects depends on the jet energy. The R

^PYTHIA_pPb

results show a p

_T

and y

^∗

-dependent suppression in the jet yield in central collisions, and an enhancement in peripheral collisions, for high p

_T

jets relative to the T

_pA

-scaled MC jet reference.

The results have been presented here using the default Glauber model to estimate the geometric quan- tities. Using either of the two Glauber-Gribov variant models [29, 30] studied by ATLAS to determine the geometric parameters results in an increased suppression and enhancement in central and peripheral events, respectively.

References

[1] C. Salgado et al., J. Phys.

G39

(2012) 015010.

[2] BRAHMS Collaboration, I. Arsene et al., Phys. Rev. Lett.

93

(2004) 242303, arXiv:nucl-ex/0403005 [nucl-ex].

[3] PHENIX Collaboration, Phys. Rev. Lett.

94

(2005) 082302, arXiv:nucl-ex/0411054 [nucl-ex].

[4] STAR Collaboration, J. Adams et al., Phys. Rev. Lett.

97

(2006) 152302, arXiv:nucl-ex/0602011 [nucl-ex].

[5] PHENIX Collaboration, Adare, A. and others, Phys. Rev. Lett.

107

(2011) 172301.

[6] J. Jalilian-Marian and Y. V. Kovchegov, Prog.Part.Nucl.Phys.

56

(2006) 104–231, arXiv:hep-ph/0505052 [hep-ph].

[7] F. Gelis, E. Iancu, J. Jalilian-Marian, and R. Venugopalan, Ann. Rev. Nucl. Part. Sci.

60

(2010) 463–489, arXiv:1002.0333 [hep-ph].

[8] D. Kharzeev, Y. V. Kovchegov, and K. Tuchin, Phys. Lett.

B599

(2004) 23–31, arXiv:hep-ph/0405045 [hep-ph].

[9] K. Eskola, H. Paukkunen, and C. Salgado, JHEP

0904

(2009) 065, arXiv:0902.4154

[hep-ph].

[10] B. Kopeliovich, J. Nemchik, I. Potashnikova, M. Johnson, and I. Schmidt, Phys. Rev.

C72

(2005) 054606, arXiv:hep-ph/0501260 [hep-ph].

[11] J.-W. Qiu and I. Vitev, Phys.Lett.

B632

(2006) 507–511, arXiv:hep-ph/0405068 [hep-ph].

[12] M. Cacciari, G. P. Salam, and G. Soyez, Journal of High Energy Physics

2008

no. 04, (2008) 063.

http://stacks.iop.org/1126-6708/2008/i=04/a=063.

[13] M. L. Miller, K. Reygers, S. J. Sanders, and P. Steinberg, Ann. Rev. Nucl. Part. Sci.

57

(2007) 205–243, arXiv:nucl-ex/0701025.

[14] ATLAS Collaboration, JINST

3

(2008) S08003.

[15] ATLAS Collaboration, Eur. Phys. J.

C70

(2010) 787–821.

[16] ATLAS Collaboration, Eur. Phys. J.

C72

(2012) 1849.

[17] ATLAS Collaboration, New J. Phys.

13

(2010) 053033.

[18] ATLAS Collaboration, Phys. Lett.

B710

(2012) 363–382, arXiv:1108.6027 [hep-ex].

[19] ATLAS Collaboration, ATLAS-CONF-2013-096. https://cds.cern.ch/record/1599773.

[20] B. Alver, M. Baker, C. Loizides, and P. Steinberg, arXiv:0805.4411.

[21] T. Sjostrand, S. Mrenna, and P. Z. Skands, JHEP

05

(2006) 026, arXiv:hep-ph/0603175.

[22] ATLAS Collaboration, ATL-PHYS-PUB-2012-003. https://cds.cern.ch/record/1474107.

[23] S. Agostinelli et al., Nucl. Instrum. Meth.

A506

(2003) 250–303.

[24] ATLAS Collaboration, Eur. Phys. J.

C70

(2010) 823–874.

[25] ATLAS Collaboration, Phys. Lett. B

719

(2013) 220–241.

[26] ATLAS Collaboration, Phys. Rev. Lett.

111

(2013) 152301.

[27] ATLAS Collaboration, Eur. Phys. J.

C73

(2013) 2304, arXiv:1112.6426 [hep-ex].

[28] ATLAS Collaboration, Eur. Phys. J.

C73

(2013) 2306, arXiv:1210.6210 [hep-ex].

[29] V. Guzey and M. Strikman, Phys.Lett.

B633

(2006) 245–252, arXiv:0505088 [hep-ph].

[30] M. Alvioli and M. Strikman, Phys.Lett.

B722

(2013) 347–354, arXiv:1301.0728 [hep-ph].