Femtoscopic BEC of charged hadrons in pp collisions at 13 TeV in CMS

SANDRA S. PADULA (ON BEHALF OF THE CMS COLLABORATION)

SPR AC E & IFT – U NESP

Outline of the talkNew: Lengths of homogeneity (Rinv) and BEC intensity (!) in broad multiplicity range (≤ 250)q High multiplicity pp collisions: ridge structure and signs of collectivity (similarities with AA collisions)

◦ What femtoscoy could add to this investigation?

q Results and conclusions need to be independent on analysis technique ◦ Three analysis methods are employed

q Brief introduction to the three analysis techniques (emphasis in one of them)

q Brief summary of the systematic uncertainties

Resultsq Comparisons of the three methods

◦ Rinv and " fit parameters vs. and vs. ( , kT )

q Comparison with lower energies◦ Study Rinv vs. and ◦ Comparison with model expectations

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 2

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Outline of analysis methods

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 3

Hybrid Cluster Subtraction

(HCS) partially data-driven, as in ATLAS-CONF-2016-027

q Employs Single Ratios only

q Uses MC SR to correlate (+ –)

and ( ) background

q Non-BEC effects: estimated

from data (+ –) SR

◦ Uses MC estimate to convert this contribution into the cluster in the data ( ) SR

q Fit SR data with combined

function for signal + cluster

Double Ratio (DR),as in (*), CMS-FSQ-13-002-PAS & (**)

q Ratio of Single Ratios (SR)

◦ SR in data divided by SR in MC

◦ Non-BEC contributions: removed by directly performing the ratio of data to MC

q Fit double ratio with a function

representing the BEC signal alone

(*) PRL 105 (2010) 03200 & JHEP 05 (2011) 029

(**) CMS, arXiv: 1712.07198

Cluster Subtraction (CS) –

fully data-driven, as in CMS-HIN-14-013-PAS & (**)

q Employs Single Ratios only

q Non-BEC cluster is estimated

direcly from data (+ –) SR

◦ Estimates the amplitude (``height’’) of the cluster using ( ) SR in data

q Fit SR with functional form

combining sig+cluster

components

≠±±

±±

±±

Common to all methods – I (Coulomb and fit)One-dimensional fit to Correlation Functions

q Lévy distribution with a à index of stability;particular cases:

◦ exponential fit (a = 1)◦ Gaussian fit (a = 2)◦ ε à fit parameter (long-range correlations)

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 4

Final state (Coulomb) interactionsq Analytic formula for Coulomb correction

[HIN-14-014-PAS, arXiv: 1712.07198)

q In pp collisions à well–approximated by Gamow factors

K(qinv) = Gw(z)[1 + z qinv Rinv/(1.26 + qinv Rinv)]

z = maem/qinv

GSSw (z) = 2pz

exp(2pz)�1

GOSw (z) = 2pz

1�exp(�2pz)

CBE(qinv) = C[1 + le�(qinvRinv)a](1 + e qinv)

q2

inv = �(k1 � k2)2= M2

inv � 4mp2

[GeV]inv

q0 0.5 1 1.5 2

/ (0

.02

GeV

)±±

SR

1

1.2

1.4

1.6

1.8

79£ 0fflinetrk N£0

< 1 GeVT0 < k DataPythia6

pp (13 TeV)CMS Preliminary

Single Ratios (SR)

q Background or Reference Sample pair selection options(one of the main sources of systematic uncertainties):

◦ Same event – examples: • opp. charges ( resonances )• rotation of 1 track of the pair

◦ Mixed events ( ) – examples: • Tracks with similar multiplicity within same η range (default)• Random mixing: Mix 40 events in a given multiplicity range

Common to all methods – II (Single Ratios)

SÃO PAULO RESEARCH AND ANALYSIS CENTER 5

Different reference samples (no BEC)

Pairs of same charge tracks from the same event (with BEC)

22 May 2018

Rexp(q = k1 � k2) =

S(k1 ,k2 )B(k1 ,k2 )

=⇥ dNsignal /dq

dNref /dq⇤

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

[GeV]inv

q0 0.5 1 1.5 2

/ (0

.02

GeV

)±±

SR

1

1.2

1.4

1.6

1.8

79£ 0fflinetrk N£0

< 1 GeVT0 < k DataPythia6

pp (13 TeV)CMS Preliminary

Double Ratios (DR) Method – I

SÃO PAULO RESEARCH AND ANALYSIS CENTER 6

CMS Collab., PRL 105, 032001 (2010)CMS Collab., JHEP05(2011)29 CMS Collab., arXiv:1712.07198, to appear in PRC

22 May 2018

◦ Data ( ) SR shows BEC

◦ Data (+ –) SR: resonances + cluster (not in mixing)

◦ MC (+ –) SR: reproduces resonances + cluster

◦ Shows (non-BEC) correlation in ( ) MC

◦ To eliminate such spurious correlations:double ratio technique (DATA/MC)

±±

±±

(No BEC in MC)CBE(q) =

R(q)RMC (q)

=

⇥ dNsignal /dq

dNref /dq

⇤

⇥ dNsignal /dq

dNref /dq

⇤

Nofflinetrk

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Ref. sample: similar in same η range (default)

Double Ratios (DR) à remove non-BEC and reduce bias

R (Q

)

DATA

Q (GeV)

( ) SR (BEC)

(+ –) SR

mixing events (signal)

R(q

)

q (GeV)R

(Q)

Q (GeV)

( ) SR (no BEC)

(+ –) SR

mixing events (signal)

MC

q (GeV)R

(q)

±± ±±

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

1

1.2

1.4

1.6

1.8

79≤ 0fflinetrk N≤0

< 1 GeVT0 < k

pp (13 TeV)CMS Preliminary

ILLU

STR

ATIO

N

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Custer Subtraction (CS) method - I

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 7

b(Noffline

trk, kT) =

b0

Nofflinetrk

exp⇥�

� kTk0

�⇤

sb(Noffline

trk, kT) =

hs0 + s1 exp

��

NofflinetrkN0

�⇤knT

Remove non-BEC contributions (CSM, arXiv: 1712.07198)

q Fully data-driven techniqueq Effect of resonances: decreases with increasing q Modulation of non-BEC effect from π+ – SR in data

q b and σb can be parametrized as ◦ b à cluster amplitude:

◦ σb à cluster width:

Nofflinetrk

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C+� (qinv) = c⇢

1 + bsbp

2pexp

�

✓q2

inv2s2

b

◆��(1 + e qinv)

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Illustration from CMSPAS-HIN-14-002

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Fully Data-Driven (FDD) Method - II

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 8

Modulation of non-BEC effect in h correlations:q The cluster contribution: also present in h pairs, with similar shape but a smaller amplitude (see MC, slide#5)

q Use the form of the contribution obtained from h+ – pairs: b and σb fixed

q Assume the width is the same and determine the ( ) cluster relative amplitude z(!"#$%&'()*+)

Illustration from CMS PAS-HIN-14-013

z(Noffline

trk) =

⇣ aNofflinetrk

+b

1+Nofflinetrk

+b

⌘

±±

CBE(qinv) = [1 + l exp(�qinvRinv)]

±±

±±

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0.8

1

1.2

0 50 100 150 200 250

z(N

rec)

Nrec

0.2 < kT < 0.3 GeV/c

✩✩ PbPb, ���√sNN = 2.76 TeV

✩

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✩

pPb, ���√sNN = 5.02 TeVpp, √�s = 7 TeVpp, √�s = 2.76 TeVpp, √�s = 0.9 TeV

CMS preliminary

0

0.2

0.4

0.6

0.8

1

1.2

0 50 100 150 200 250

z(N

rec)

Nrec

0.4 < kT < 0.5 GeV/c

✩✩ PbPb, ���√sNN = 2.76 TeV

✩

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✩

pPb, ���√sNN = 5.02 TeVpp, √�s = 7 TeVpp, √�s = 2.76 TeVpp, √�s = 0.9 TeV

CMS preliminary

C±± (qinv) = c

1 + z�

N offlinetrk

� bsbp

2pexp

✓� q2

inv2s2

b

◆�CBE (q inv )

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Hybrid Cluster Subtraction (HCS) Method – I Technique used by ATLAS experiment in BEC analysis with pPb events (ATLAS, PRC 96 (2017) 064908)q Goal: remove the non-Bose-Einstein contributions

Procedureq Simulation: used to estimate Background (``Bkg”), i.e., non-femtoscopic correlations, mainly due to

jet fragmentation or Cluster (i.e., mini-jets, etc.) contribution, present in SR in the data ◦ Obtain conversion functions: relate [Bkg (+ –)] [Bkg ( )] using SR from MC

◦ Use transfer function: convert fit parameters from [Bkg (+ –) ] into Bkg ( ) in SR from data

q Final fit function in data ( ) SR: combination of “Signal + Bkg” forms◦ “Bkg” fixed with the parameters obtained in the previous step

◦ Notation: Background parameters denoted as B and σB (as defined in the next slide) ◦ Resulting “Signal”: described by free parameters (! and "#$%) fitted with exponential function

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 9

±±±±

±±

[GeV]inv

q0 0.5 1 1.5 2

SR /

(0.0

2 G

eV)

0.9

1

1.1

1.2

1.3

Pythia 6, +- / Ndof = 47 / 482χGauss Fit,

±±Pythia 6, / Ndof = 96 / 912χGauss Fit,

109≤ trkoffline N≤105 < 0.3 GeVT0.2 < k

pp (13 TeV)CMS Simulation Preliminary

Fitting Same-Sign and Opp-Sign SR in MCq In Monte Carlo: no Bose-Einstein effects à Bkg can be modeled by fit parameters

q In data: BE effect not present in [(+ –)] component – Bkg only ◦ Use the relations from MC to estimate the Bkg component in ( ) SR

Fit Functions

◦ Fit parameters relation ( !",$%&' =2 )

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 10

±±

W(qinv) = N�1 + B exp

h�

��� qinvsB

���aBi�

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B±±= µ(kT)

⇥B+�⇤n(kT )

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Hybrid Cluster Subtraction (HCS) Method – II

[GeV]inv

q0 0.5 1 1.5 2

SR /

(0.0

2 G

eV)

0.9

1

1.1

1.2

1.3

Pythia 6, +- / Ndof = 52 / 482χGauss Fit,

±±Pythia 6, / Ndof = 109 / 912χGauss Fit,

21≤ trkoffline N≤19 < 0.3 GeVT0.2 < k

pp (13 TeV)CMS Simulation Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

+-Log(B)4- 3- 2- 1- 0

±±Lo

g(B)

4-

3-

2-

1-

0

< 0.3 GeVT0.2 < k < 0.4 GeVT0.3 < k < 0.5 GeVT0.4 < k < 0.7 GeVT0.5 < k

pp (13 TeV)CMS Simulation Preliminary

[fm]+-]-1)Bs[(0.2 0.25 0.3 0.35 0.4 0.45 0.5

[fm

]±± ]

-1 ) Bs[(

0.2

0.25

0.3

0.35

0.4

0.45

0.5

< 0.3 GeVT0.2 < k < 0.4 GeVT0.3 < k < 0.5 GeVT0.4 < k < 0.7 GeVT0.5 < k

pp (13 TeV)CMS Simulation Preliminary

22 May 2018 11

Relation vs. (Pythia6 Z2*):

ρ=0.82 ± 0.04 (stat.); β = 0.077 ± 0.013 (stat.)

Relation vs. (Pythia6 Z2*):⇥�

sB

��1⇤±±

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SÃO PAULO RESEARCH AND ANALYSIS CENTER

Hybrid Cluster Subtraction (HCS) Method – III

https://cds.cern.ch/record/2318575(FSQ-15-009-pas.pdf)

[GeV]inv

q0 0.5 1 1.5 2

SR /

(0.0

2 G

eV)

1

1.2

1.4

1.6

1.8

±±Data, Data, +-

/ Ndof = 166 / 952χ Gauss) Fit, ×(Exp. / Ndof = 62 / 482χGauss Fit,

Background

21≤ trkoffline N≤19 < 0.3 GeVT0.2 < k

pp (13 TeV)CMS Preliminary

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 12

After getting relations for ``Bkg’’ fit parameters in Monte Carloq Bkg in data is estimated in (+ –) SR

q Assume relation of (+ –) SR and ( ) in data is the same as in MC

q Use conversion function to estimate ``Bkg’’ in ( ) SR in data

±±

±±

Hybrid Cluster Subtraction (HCS) Method – IV

[GeV]inv

q0 0.5 1 1.5 2

SR /

(0.0

2 G

eV)

1

1.2

1.4

1.6

1.8

±±Data, Data, +-

/ Ndof = 1028 / 952c Gauss) Fit, ´(Exp. / Ndof = 51 / 482cGauss Fit,

Background

109£ trkoffline N£105 < 0.3 GeVT0.2 < k

= 13 TeVs pp, CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Results with systematicsFor the three methods

q R"#$ and λ as functions of multiplicity and kT

Similar trends for all the methods

q R"#$ increases with multiplicity and decreases with kT

q & decreases with multiplicity (mainly for lower values) and decreases with kT

q Larger deviations in the magnitude of & for CS technique (larger uncertainties in this method)

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 13

[GeV]⟩ T k⟨0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6

λ

0

0.5

1

1.5

2

Minimum-biasCluster SubtractionHybrid Cluster SubtractionDouble Ratio

High-multiplicityCluster SubtractionHybrid Cluster SubtractionDouble Ratio

pp (13 TeV)CMS Preliminary

⟩ tracks N⟨0 50 100 150 200

λ

0

0.5

1

1.5

2 < 1 GeVT0 < k

Cluster SubtractionHybrid Cluster SubtractionDouble Ratio

pp (13 TeV)CMS Preliminary

[GeV]⟩ T k⟨0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6

[fm

]in

vR

0

1

2

3

4

5

Minimum-biasCluster SubtractionHybrid Cluster SubtractionDouble Ratio

High-multiplicityCluster SubtractionHybrid Cluster SubtractionDouble Ratio

pp (13 TeV)CMS Preliminary

⟩ tracks N⟨0 50 100 150 200

[fm

]in

vR

0

1

2

3

4

5 < 1 GeVT0 < k

Cluster SubtractionHybrid Cluster SubtractionDouble Ratio

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Comparison with CMS and ATLAS @7 TeVRinv Results from HCS compared toq Left: CMS for pp@7 TeV [arXiv: 1712.07198] using Double Ratio method (η-mixing reference sample)q Right: ATLAS for pp@7 TeV [EPJC 75(2015)466] using Double Ratio method (opposite sign reference

sample)

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 14

⟩ > 0.1 GeV) trkT

(ptracks N⟨0 50 100 150 200 250 300

[fm

]in

vR

0

1

2

3

4

5HCS Method - pp @ 13 TeV (same range)Syst.: HCSIntramethods variationATLAS - pp @ 7 TeV

CMS Preliminary

⟩ tracks N⟨0 50 100 150 200

[fm

]in

vR

0

1

2

3

4

5HCS Method - pp @ 13 TeVSyst.: HCSIntramethods variationCMS - pp @ 7 TeV

CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

vs. All the fits using only statistical uncertaintiesq Linear fit

◦ !"# $%&' = 50q Linear + Constant

◦ !"# $%&' = 40

Including systematic uncertaintiesq Not trivial to estimate point-to-point correlationsq Fit quality using fully correlated systematics is similar

as using only statistical uncertaintiesq Considering systematics fully uncorrelated

◦ Linear fit : !"# $%&' = 0.4◦ Linear + constant fit : !"# $%&' = 0.15

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 15

1/3⟩ tracks N⟨0 1 2 3 4 5 6 7

[fm

]in

vR

0

1

2

3

4

5HCS Method

Syst. : HCS

Intramethods variation

Linear fit + constant

Linear fit

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

vs. Comparison with CGC prediction [McLerran, Schenke, NPA 916 (2013) 210; P. T. A. Bzdak et al, PRC 87 (2013) 064906]

q Calculation for pp @ 7 TeV (does not include evolution of the system)

q Similar shape, but very big difference in magnitude

Above 1.7 : fit with same function obtained from CGC prediction

◦ x = #$%&'()*+ $,-//

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 16

1/3⟩ η/dtracks dN⟨0 0.5 1 1.5 2 2.5 3 3.5 4

[fm

]in

vR

0

1

2

3

4

5 1/3)η/dtracks

(dN≡HCS Method, x Syst. : HCSIntramethods variationLinear fit

(x) fitppR(x) CGCppR

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

mT dependence

!" #$%&' vs m+ = m-. + k+.

q In hydrodynamic models [Sinyukov et al., NPA 946 (2016) 227]

◦ Intercept connected with the geometrical size of the source (at freeze-out)

◦ Slope connected to the flow componentLarger slope (larger flow) for lower multiplicities (similar to peripheral AA collisions) as compared to higher multiplicities (similar to more central AA collisions)

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 17

[GeV]Tm0 0.2 0.4 0.6 0.8 1

]2 [1

/fm2 in

v1/

R0

0.2

0.4

0.6

0.8

1Hybrid Cluster Subtraction

Minimum-biasSyst. : HCSIntramethods variationHigh-multiplicitySyst. : HCSIntramethods variationLinear fitLinear fit

Hybrid Cluster SubtractionMinimum-biasSyst. : HCSIntramethods variationHigh-multiplicitySyst. : HCSIntramethods variationLinear fitLinear fit

pp (13 TeV)CMS Preliminary

[GeV]Tm0 0.2 0.4 0.6 0.8 1 1.2 1.4

]2 [1

/fm2 in

v1/

R

0

0.1

0.2

0.3

0.4

0.5

0.6

Hybrid Cluster Subtraction

19≤ offlinetrk N≤0

39≤ offlinetrk N≤20

59≤ offlinetrk N≤40

79≤ offlinetrk N≤60

99≤ offlinetrk N≤80

119≤ offlinetrk N≤100

139≤ offlinetrk N≤120

250≤ offlinetrk N≤140

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Discussion about an anticorrelation (I)Zoomed (along the y-axis) correlation functions from DR method

q Fits with exponential (red) and τ-model [Csörgö, Zimányi NPA 517 (1990) 588] (green)

q τ-model explains better the overall behavior of data

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 18

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.284≤ offline

trk N≤80

/ Ndof = 5900 / 952χ

/ Ndof = 902 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.2109≤ offline

trk N≤105

/ Ndof = 1496 / 952χ

/ Ndof = 281 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.2250≤ offline

trk N≤130

/ Ndof = 147 / 952χ

/ Ndof = 84 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.24≤ offline

trk N≤0

/ Ndof = 276 / 952χ

/ Ndof = 195 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.212≤ offline

trk N≤10

/ Ndof = 517 / 952χ

/ Ndof = 140 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

[GeV]inv

q0 0.5 1 1.5 2

DR

/ (0

.02

GeV

)

0.9

1

1.1

1.233≤ offline

trk N≤31

/ Ndof = 525 / 952χ

/ Ndof = 135 / 932χ

<1.0T k≤0.0

DataExp. Fit, model, τ

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Discussion about an anticorrelation (II)Anticorrelation depthq Integrated in kT

◦ Decreases with <Ntracks>, andtend to ~ const. above 100

q and differential in k"◦ Decrease with k" for lower

<Ntracks> ranges◦ For <Ntracks> > 30 à ~ const.

with increasing kT

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 19

[GeV]Tk0 0.2 0.4 0.6 0.8 1

∆

0

0.02

0.04

<10offlinetrk N≤0

<20offlinetrk N≤10

<30offlinetrk N≤20

<40offlinetrk N≤30

<50offlinetrk N≤40

<60offlinetrk N≤50

<70offlinetrk N≤60

<80offlinetrk N≤70

<90offlinetrk N≤80

<100offlinetrk N≤90

<110offlinetrk N≤100

<120offlinetrk N≤110

<140offlinetrk N≤120

pp (13 TeV)CMS Preliminary

⟩ Tracks N⟨0 50 100 150

∆

0

0.02

0.04Double Ratio MethodData Syst.

pp (13 TeV)CMS Preliminary

https://cds.cern.ch/record/2318575 (FSQ-15-009-pas.pdf)

Summary of results in pp collisions at 13 TeVBEC in Minimum Bias and High Multiplicity events in pp collisions at 13 TeVq First investigation with both MB and HM events à three different techniques employed:

◦ Double Ratios involving data and MC (Pythia 6 – Z2* tune) – (FSQ-13-002-PAS, arXiv:1712.07198)◦ Fully Data-driven as used in CMS – (HIN-14-013-PAS, arXiv:1712.07198)◦ Hybrid Data-driven (transfer function from Pythia 6 – Z2* tune) – as proposed in ATLAS-CONF-2016-027

q 1-D BEC (exponential fit): Rinv (and λ)◦ Scrutinized in detail as a function of multiplicity, searching for:

§ Changes of slope [PLB 703 (2011) 237]§ Continuous growth with (Ntracks)1/3 compatible with data§ Possible saturation of Rinv in the high multiplicity range also compatible with data

◦ Detailed investigation as a function of kT , searching for:§ Possible change in behavior of Rinv results while moving from event in the MB to the HM regions, etc.

◦ mT – scaling with different slopes in MB and HM: Hubble-type of flow larger in MB than in HM

q Comparison with models ◦ CGC/IP-GLASMA [NPA 916 (2013) 210; PRC87 (2013) 064906] ◦ Hydrodynamic models (with different Initial Conditions and EoS) [Sinyukov et al., NPA 946 (2016) 227]

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 20

https://cds.cern.ch/record/2318575; https://cds.cern.ch/record/2318575/files/FSQ-15-009-pas.pdf

ADDITIONAL SLIDES

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 21

Sources of systematic uncertainties Main sources of systematic uncertaintiesq Reference samples q Monte Carlo modeling of correlation functions q Cluster amplitude z(Noff

trk) in the Full Data-Driven methodq Track selections q Coulomb corrections

Other sources (less significant)q PU dependence q Z-vertex position dependenceq HM HLT trigger biasq Track corrections

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 24

Experimental cuts and definitions adoptedOther variables

q !"#$%&'()*+ = 0 − 250

q kT (GeV) < 1 GeV or

kT ε {0.2-0.3, 0.3-0.4, 0.4-0.5, 0.5-0.7}

kT (GeV) = |pT,1+ pT,2|/2

q qinv (GeV) = 0.02 − 2.0

q Fit Function used :

22 May 2018 SÃO PAULO RESEARCH AND ANALYSIS CENTER 25

!"#$%&'()*+ definitionq HighPurity

q pT > 0.4 GeV

q |η|< 2.4

q |,pT/pT|< 0.10

q |dz/,dz| < 3 wrt PV

q |dxy/,dxy| < 3 wrt PV

Track selection for BEC analysis q HighPurity

q pT > 0.2 GeV

q |η|< 2.4

q |,pT/pT|< 0.10

q |dz/ ,dz| < 3 wrt PV

q |dxy/ ,dxy| < 3 wrt PV

q pixelLayersWithMeasurement > 1

C[1 + � e�(qinv

Rinv

)] (1 + ✏ qinv)

q2= q2

inv = �(k1 � k2)2= M2

inv � 4mp2