Study of the
B  J/ decays in pp collisions
(B  J/ + X  e+e- + X)
Carmelo Di Giglio
Università di Bari & INFN - Italy
OUTLINE:
 Physics motivations.
 Analysis strategy.
 Status of the analysis:
 measuring the fraction of J/ from B (i.e secondary J/ ).
 background analysis.
 Outlook
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Physics motivations
The study of the channel B  J/ +X is an
important issue since:
e+e
A large fraction ( ≈ 40% ) of total J/ come
from beauty hadron decays.

It provides another measurement of the sbb
cross-section in the central barrel besides the
single electron channel (B  e +X)
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B  J/ w.r.t B  e +  + X
 Being the J/ much heavier than the electron, it
resembles more an “exclusive” channel.
 It can allow a determination of the dsbb/dpt crosssection down to pt≈0.
 Invariant mass analysis is possible.
 Branching ratio:
Be++X
B  J/ + X
J/   e+eB  J/   e+ePalau - 29 Sept. 2008
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10.8%
1.16 ± 0.10 %
5.94 ± 0.06 %
0.069 ± 0.007 %
3
Strategy

Analysis of total J/ relies on:
 Combinatorics
between + and - tracks.
selection of e+e- pairs (in this analysis based
on the parametrised response of TRD + TPC).
 PID
 Invariant

mass analysis.
Goal: separate secondary J/ from prompt J/:

it relies on the spatial resolution of the ITS.
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Measuring the fraction of
J/ from HB
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MC samples used for the analysis


7.3*104 PDC’06 p-p events with secondary
J/
 equivalent to 9.9·109 min. bias pp events
3*105 PDC’06 p-p events with prompt J/
 equivalent to 14.9·109 min. bias pp events.
dedicated
PDC’06
prod in
the Bari
farm.
2.8*106 min. bias pp events. from the Cern
Analisys Facility (CAF) for the bkg. study

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PID scheme adopted
 TPC-TRD parametrization of the probability to
 Each particle is assigned a weight, depending
misidentify
the specie: a  as an electron:
 TPC
eff

+
 TRD
from ALICE Physics
0.9(TPC)*
0.9(TRD)
Week
(March 2008)
and -
 effTPC(p) * effTRD(p)
the others
 0.
1
-1
10All
Pion contamination
same as for the B in the
semielectronic
e+ and e-channel 
on
10-2
10-3
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Kinematical distributions:
prompt J/ Vs. secondary J/


Impact parameters d0(e)
rapidity
and transverse momentum
(all distribution
normalized to 1- m.b. event)
+
e
e
Primary J/
y

Secondary J/
Product of impact parameters d0(e+)*d0(e-) Secondary dominant
at high pt
Primary J/
J / from b
 40.1%
tot J /
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Secondary J/
but pT dependent
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Kinematical distributions:
prompt J/ Vs. secondary J/
 Invariant Mass
 Pseudo-proper decay
 
L  pT ( J / )
Lxy ( J / )  
pT ( J / )
Primary J/
Secondary J/
Primary J/
Secondary J/
M J /
x  Lxy ( J / ) 
pT ( J / )
  sec The
 primshape is due to:
L  rvtx  rdetector
vtx
resolution
 bremsstrahlung
process on the path
through the detector
material
 long tail at low
time:
invariant mass
values.
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Background components

The dominant background component in the J/ invariant
mass window (after PID), is e+e-


9 events:
What is expected from a real MB
sample
of
N
~10
The available statistics  3*106 pp @ 14 TeV MB
N ~events
106 pp
min bias
(stored on CAF) wastot
not enough
e+e- to study combinatorial
Events on
Tot
background properly.
eh
CAF
J/
+h- (normalized to the total bkg) used
(prompt+sec
 BkgS equal
to
h
so far to
 34  6
ondary)
+
S  B analysis tools.
develop
h h
Bkg (h+h- norm)
In the selected
mass window
Normalized to
1 m.b event
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How to measure the fraction of secondary J/
order to extract the fraction fB of J/
from b-hadron decays, one should fit
simultaneously:
 the
invariant mass spectrum
 one
distribution which can discriminate
prompt from detached J/ (e.g. x or
product of impact parameters d0e+·d0e-)
 the
Events/10 MeV
 In
analysis should be performed in pt
bins. Final goal: measure fB(pt)  ds bb
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dp t
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How to measure the fraction of secondary J/

Approach used: simultaneous mass and
lifetime fit using the log-likelihood function [1] :
N
ln L   ln F( x, mee )
i 1
F( x, mee )  f Sig  FSig ( x)  M Sig (mee )  (1  f Sig )  FBkg ( x)  M Bkg (mee )
N is the number of events in |mee-MJ/|<D,
D=200 MeV
[1] Acosta et al.,CDF Collaboration, PRD 71 032001 (2005)
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How to measure the fraction of secondary J/
F( x, mee )  f Sig  FSig ( x)  M Sig (mee )  (1  f Sig )  FBkg ( x)  M Bkg (mee )
FSig ( x)   f B  FB ( x)  (1  f B )  FP ( x)
fB fraction of
secondary J/
FP ( x)  R( x)
R(x) resolution function
FB ( x)  R( x  x)   MC ( x)
MC (x,pt) MonteCarlo
templates (as obtained by
PYTHIA) of the x distribution
13 parameters at all.
More details in the extra slides.
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Improvements on the method to extract the
fraction of secondary J/:

 New parametrization of the signal mass
distribution Msig(mee).
 New parametrization of the x resolution R(x).
 Analysis performed in pt bins (9 bins).
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Parametrization of R (x )
R (x ) resolution function
 determined
from prompt J/
 distribution of X / RMS(X) parametrized as sum of
2 Gaussian + 1 exponential centered at 0 (5
params) to account for the long tails observed at
high values
Pt > 0
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
To reduce the n. of parameters the fit in individual
pt bin is performed by:

fixing, from fit on the distribution integrated
over pt , two parameters: sigma of one gaussian
and  of the exponential

leaving free the remaining three, i.e:


the sigma of the main gaussian.
the relative weights among two components of the
fitting function.
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Result of the fit
Pt>0
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Pt < 1GeV
1 < Pt < 1.5
1.5 < Pt < 2
2 < Pt < 2.5
2.5 < Pt < 3
3 < Pt < 3.5
3.5 < Pt < 4.5
4.5 < Pt < 5.5
Pt > 5.5
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Parametrization of
M sig (mee )

New parametrization:
Based on the Crystall Ball function as introduced for the first
time in [2]
 ( m  m) 2 
for m  m  

exp  
2

2
s
s


4 params
F (m;  , n, m, s )  N
n
mm

mm


for
A   B 

s
s 

N = normalization factor
 n
A  

B
n

 2


  exp  

 2 



n

= 0.5
 = 1.
 = 1.5
 = 2.
s = 0.1
s = 0.2
s = 0.7
s = 0.9
 = 2.5
[2] J.E.Gaiser, Charmonium Spectroscopy from Radiative Decays of the J/Psi and Psi-Prime,SLAC-R-255, (1982)
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The fit has been successfully performed on all
the three samples:
Secondary J/
Primary J/
whole pt
range…

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Total J/
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Extracted
invariant mass
M = 3.091GeV
19

… and in nine pt bins
Total J/
Prompt
J/
Secondary
J/
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Pt < 1GeV
Pt < 1GeV
Pt < 1GeV
1 < Pt < 1.5
1 < Pt
1.5< 1.5GeV
1 << Pt
1.5 < Pt < 2
1.5 <1.5
Pt << Pt
2 < 2GeV
2 < Pt < 2.5
2 < Pt
2.5< 2.5GeV
2 << Pt
2.5 < Pt < 3
2.5 <2.5
Pt << Pt
3 < 3GeV
3 < Pt < 3.5
3 < Pt
3.5< 3.5GeV
3 << Pt
3.5 < Pt < 4.5
3.5 <3.5
Pt << Pt
4.5< 4.5GeV
4.5 < Pt < 5.5
4.5 <4.5
Pt << Pt
5.5< 5.5GeV
Pt > 5.5
Pt > Pt
5.5> 5.5GeV
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How to measure the fraction of secondary J/
a C++ program has been implemented to
perform the fit, based on the Root module
Minuit2
 The fit is a multidimensional one:

 13
parameters.
 Analytical
calculation of convolution integrals.
 The
code written to execute minimization in pt bins
automatically.
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How to measure the fraction of secondary J/

Optimization is ongoing:
 A first
check performed to test convergence of
the minimization procedure:
consider in input prompt J/ only, sec. J/ only,
bkg only and check weather the algorithm
converges to reasonable values (i.e fB  0, fSIG  1,
ecc…)
 Still
some problems of convergence occurred in
few bins.
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Background shape
analysis
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The likelihood fit provides the amount of bkg as well
In order to reduce the number of parameters one can:

determine a priori the shape and (eventually) the amount of
the background invariant mass spectrum under J/ peak.

impose (fix) them in the likelihood fit.
To study bkg:

Like Sign (LS) pair technique:

Uncorrelated bkg in the unlike-sign pair sample estimated by the number
of like-sign pairs ++ and -- within each event.

Event Mixing technique:

Uncorrelated bkg in the unlike-sign pair sample estimated by an unlike-
sign pair spectrum for which the two particles are taken from different but
similar (as far as vtx-position and multiplicity is concerned) events.
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Pros & Cons of Like Sign w.r.t of Event Mixing
 Event Mixing:
 Appropriate to study comb. bkg in case of low statistics
and in the continuum.
 Can introduce bias in this analysis, which aims at
separating prompt from detached (hundreds of microns)
since it mixes events with diff primary vtx-positions.
 Like Sign
 Easier from a computational point of view.
 Feasible to reproduce the shape of the bkg. invariant
mass spectrum under J/ peak.
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Data samples used:

2.5*104 pp @ 14 TeV minimum bias events
3*105 pp @ 14 TeV events with 1 prompt J/ per
event forced to dielectrons (in the “barrel”, | y | < 2)

 Is not a minimum bias sample.
 No CC couples explicitly present in the sample
1.6*106 pp @ 14 TeV events with 1 CC / event
(PWG3 production 2006 generated on the Italian Grid,
Torino-CNAF-Padova).

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
prompt J/
No PID
Like Sign
Unlike Sign
Ratio US/LS
D0
J/
Log scale
M (Gev)
M (Gev)
N.B: Normalization performed so far on the integral of the curves  tot #
of US and LS pairs respectively.

D0 mass also shown: LS should reproduce well bkg spectrum under
corresponding peak (not shown here).

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After PID
Like Sign
Unlike Sign
Log
scale
M( GeV)
M( GeV)

Normalization performed integrating
curves in the region:
0.5 Gev < M < 1.3 GeV
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Under J/ peak
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M( GeV)
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Results for sample with 1 cc/ev.
normalized to 1 MB event.
No PID
Like Sign
Unlike Sign
Ratio US/LS
 Only e-e and e-h couples have been selected:
tot
e+eeh
h-h contribution after PID is negligible.
h +h -
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After PID
Invariant mass
Plots normalized to 1 Min Bias event
Like Sign
Unlike Sign
M (GeV)
Two plots have the same variable binning.
Good result from
Kolmogorov test:
probability P Kolm~ 81%
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2 of the ratio US/LS w.r.t
= 1 curve:
20 = 2/ ndf = 1.099
P(2 > 20 ) ~ 40-50%
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r
Conclusions & Outlook




Method to extract the fraction of secondary J/ improved:
 New parametrization of the signal mass distribution and x
resolution R(x).
 Code algorithm improved: multidimensional fit (13
parameters) performed in about one hour for a statistics
equivalent to 10*109 min bias event
 Try other variables to separate J/ from B, e.g. d0xd0
Robustness of the minimization to be investigated:
 Try to reduce n. of parameters (as for the bkg invariant mass
shape study).
Performance on GRID data(2*105 pp events with J/ from
Beauty hadrons)
Performance in Pb-Pb.
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Extra slides
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Experience at colliders:
CDF @ Tevatron , √sNN=1.96TeV

CDF measures J/ in the dimuon channel using
SVX II (five layers) to separate primaries from
secondaries (i.e. from B decays).
 the channel e+e- has a worsen mass resolution
than the , due to bremsstrahlung.

Performance of CDF:
 CDF resolution on primary vertex is 30.

CDF s(pt)/pt2 = 0.0017 GeV/c-1 .
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How to measure the fraction of secondary J/
F( x, mee )  f Sig  FSig ( x)  M Sig (mee )  (1  f Sig )  FBkg ( x)  M Bkg (mee )
M Bkg (mee ) 

meemax

meemax  meemin
1
 M slope  mee 
min
2
 mee




The mass background is modeled using a linear
distribution
 function
normalized to unity over the mass range
[meemin, meemax]
The only parameter is Mslope
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How to measure the fraction of secondary J/
F( x, mee )  f Sig  FSig ( x)  M Sig (mee )  (1  f Sig )  FBkg ( x)  M Bkg (mee )
 x 
f
FBkg ( x)  (1  f   f   f sym ) R( x)  exp    ( x)  R( x  x) 
    
 x 
f sym
 x 
f
 ( x)  R( x  x) 
exp   ( x)  R( x  x) 
exp  
    
2sym  sym 
 x 
 ( x)  R( x  x)
exp 
2sym  sym 
f sym
Parameters: f+ ,f- ,fsym ,+, -, sym, params of R(x)
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Old parametrization of
M sig (mee )
Parametrization previously used:
Ad hoc parametrization taken as the sum of 2 Landau
with same mpv, one of them square-rooted and
reflected about mpv (4 params)

Failed when
trying to perform
the fit also in pt
bins.
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R LL
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LR
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
Simple cuts on reconstructed tracks, excluding


tracks with any kink (GetKinkIndex(0) > 0).
tracks not reconstructed at the level of:
• ITS
• TPC
• TRD

Like Sign candidates ++ and -- constructed
within each event:

using the same classes in AliROOT code (in PWG3)
used to build unlike-sign pairs candidates, i.e.
• AliBtoJPSItoEleAnalysis
• AliBtoJPSItoEle
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(search for candidates)
(stores & describes candidates)
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Contributions to the background
tot
e+ eeh
hh
MB
Contribution
to the total
bkg from
events with
1 cc pair.
The band accounts for the inefficiency factor ~ 15 %
due to TPC parametrization in the used sample.
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