Transcript Open charm reconstruction in the ALICE experiment Elena Bruna Supervisor: Prof. Massimo Masera

Open charm reconstruction in
the ALICE experiment
Elena Bruna
Supervisor: Prof. Massimo Masera
Seminar for the end of 2nd year (XIX) – Torino, Dec 2nd 2005
Outline
• Physics motivations of open charm analysis in Heavy Ion
Collisions
• D+ → K-π+π+ : overview of the kinematics
• Measurement of open charm in the ALICE experiment
• Exclusive reconstruction of D+ → K-π+π+:
• Event generation and reconstruction
• Reconstruction of the secondary vertex
• Selection strategy
• Perspectives for the measurement of D+ elliptic flow
• Summary and work plans
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Motivations for the Open Charm
physics in Heavy Ion Collisions
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Heavy quarks as probes of
nuclear medium /1
• charm, bottom produced at early stages of the collision
(timescale ~ 1/mQ < QGP ~ 10 fm at LHC)
Studies of initial state effects: nuclear shadowing
Because of the very low x down to ~10-4 at LHC the so many gluons merge
together, affecting the partons densities at low x w.r.t. protons partons ones.
• thermal production
 The c quark might be produced in the plasma phase:
mc (~ 1.2 GeV) comparable with predicted Tplasma (~
0.6-0.8 GeV)
• open QQ production (not Drell-Yan) natural normalization
for QQ studies
 Quarkonia enhancement at low PT and suppression at
high PT.
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Heavy quarks as probes of
nuclear medium /2
• charm, bottom have long lifetime (> QGP ) and can probe
the bulk, strongly interacting phase
Studies of final state effects:
1) radiative energy loss
Hard partons radiate gluons in the medium, lose energy and become
quenched. Heavy quarks are expected to lose less energy than light
quarks.
Nuclear modification factor
RD ( pT )
Rc.h. ( pT )
yield AA
RAA ( pT ) 
coll
yield pp  Nbin
High E  suppression of the produced particles (at high PT)  RAA≠1
It depends on the properties of the medium (gluon density,
temperature and volume), it provides information on such properties.
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Heavy quarks as probes of
nuclear medium /3
Studies of final state effects:
2) anisotropic flow on the transverse plane
Elliptic Flow = collective motion of particles (due to high pressure arising from
compression and heating of nuclear matter) superimposed on top of the
thermal motion
Correlation between azimuthal angles  of outgoing particles
and the direction of the impact parameter (REACTION PLANE RP)
dX X 0
 1  2v1 cos(   RP )  2v2 cos 2  RP   .... 
d 2




v
c
o
s
2



2
R
P
Elliptic flow coefficient
High opacity of the medium (strongly interacting) 
high anisotropic flow  high v2
v2 provides information
onBruna
the opacity of the medium.
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Few experimental results from RHIC /1
radiative energy loss - RAA of the D mesons
( PT spectra of e+e- from D semileptonic decays )
from QM05
from QM05
q = 0 GeV2/fm
dNg / dy = 1000
q = 4 GeV2/fm
q = 14 GeV2/fm
 Charm is suppressed! Suppression is
approximately the same as for hadrons.
 Challenge for energy loss models. Elena Bruna
Also pp and pA data are
needed as reference!7
Few experimental results from RHIC /2
anisotropic flow – v2 of the D mesons
(  spectra of e+e- from D semileptonic decays )
from QM05
from QM05
 Significant flow of charm quark as for light quarks
 Strong coupling of charm quark to the medium
 Indication for reduction of v2 at pT > 2 GeV/c
(PHENIX)
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Also pp and pA data are
needed as reference!
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D+ → K-++ : overview of the
kinematics
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Why D+ → K-++ ?
Advantages…
1. D+ has a “long” mean life (~311mm compared to ~123
mm of the D0)
2. D+ → K-++ is a 3-charge body decay  the most
promising from an experimental point of view
3. D+ → K-++ has a relatively large branching ratio
(BR=9.2% compared to 3.8% for D0 → K-+).
…drawbacks
1. Combinatorial background for this 3-body channel is
larger than for D0 → K-+.
2. The average PT of the decay product is softer (~ 0.7
GeV/c compared to ~ 1 GeV/c)
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Hadronic 3-charge-body decays of D+
D±
I(JP) = ½ (0-)
m = 1869.4 MeV/c2
c = 311.8 mm
(PDG ’04)
D+K-++
BR = 9.2 %
D+→K-++
Non Resonant BR = 8.8 %
D+→K*0(892)+→K-++
Resonant
BR = 1.3 %
D+→K*0(1430)+→K-++ Resonant
BR = 2.3 %
D+→K*0(1680)+→K-++ Resonant
BR = 3.8·10-3 %
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Kinematics (1)
PT distributions of the generated
particles (ONLY PYTHIA generation,
NO propagation and reconstruction in
the detector)
K
Mean = 0.87 GeV/c
(nonresonant events)
D
Mean = 1.66 GeV/c

Mean = 0.67 GeV/c
Knowledge of the PT shapes of the
decay products important at the level of
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the selection strategy
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Kinematics (2)

Comparing with Pb-Pb central
events (ONLY HIJING generation,
NO propagation and reconstruction
in the detector):
Mean = 0.67 GeV/c
Mean = 0.50 GeV/c
PT distributions:
nonresonant D+ decay
K
HIJING central (normalized)
Mean = 0.87 GeV/c
Mean = 0.65 GeV/c
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K and  from D+ are
harder than K and 
produced in a Pb-Pb event
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Dalitz Plots: Kinematics (3)
Non resonant
Resonant
Sharp borders due to PYTHIA cut
off on the tails of distributions
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Measurement of open charm in
the ALICE experiment
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ALICE @ LHC
setup
Time Projection Chamber (TPC)
Tracking, PID (dE/dx)
-0.9<<0.9
HMPID
TRD
MUON SPECTR..
PHOS
Inner Tracking System
(ITS):
6 SILICON layers
(pixel, drift, strip)
Vertices reconstruction,
PID (dE/dx)
-0.9<<0.9
Time Of Flight (TOF)
Tracking, PID (time)
-0.9<<0.9 Elena Bruna
Size:
16 x 26 m
Weight: ~10,000 16
tons
Track Impact Parameter d0
SIGMA (fit)
expected d0 resolution (s)
d0 – d0 sim
MEAN (fit)
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Track Impact Parameter : d0 pull
SIGMA (fit)
Calculate the pull
pull 
d 0  d 0 sim
err (d 0 )
MEAN (fit)
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Exclusive reconstruction of
D + → K-  + +
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Simulation strategy
Our purpose: exclusive reconstruction of D± in the ALICE barrel
(Inner Tracking System employed in the search for secondary vertexes)
Too large statistics
Central Pb-Pb
(108 events) would
~ 9 D+/Devent (b<3.5 fm,
be required to
in |y|<1
dN/dy = 6000,
study the signal!!
√s=5.5 TeV)
Signal and background events separately
generated with the Italian GRID
• 5’000 signal events with only D± decaying in K (using PYTHIA):
 Check the kinematics and the reconstruction
 Optimize the vertexing algorithm
• 20’000 background events (central Pb-Pb events using HIJING):
 cc pairs merged in addition in order to reproduce the charm yield
predicted by NLO pQCD calculations (≈ 118 per event)
 Tune the cuts (impact parameter cut,…) on the tracks to be
analyzed by the vertexing algorithm
 Evaluate the combinatorial background
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Reconstructed signal events:
Dalitz Plots
(
From reconstructed tracks
: the info given by the generation are taken into account)
This is done as an internal cross-check procedure
Non resonant
Resonant
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Reconstructed signal events:
D+ invariant mass
Mean
MEAN = 1.867 GeV/c2
RMS = 0.019 GeV/c2
this is not a complete
reconstruction of the
signal: tracks are grouped by means
of info. stored at generation time.
Knowledge of MINV resolution vs PT
is important when selecting the
signal candidates Elena Bruna
MINV Resolution (SIGMA
of the gaussian fit)
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Reconstruction of the secondary
vertex for
D+ → K-++
 First idea: adapting and improving the method already written
for the primary vertex finding and fitting in p-p
 Second idea: writing a new secondary vertex finder and
comparing its performace with the previous ones
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Vertex finder
•
Originally developed to find the primary vertex in p-p
 Based on the Straight Line Approximation of a track
(helix)
•
Main steps
1. The method receives N (N=3 in our case) tracks as input
2. Each track is approximated by a straight line in the
vicinity of the primary vertex
3. An estimation of the secondary vertex from each pair of
tracks is obtained evaluating the crossing point between
the 2 straight lines
4. The coordinates of secondary vertex are determined
averaging among all the track pairs:
x found 
1
N pairs
 xij
ij
y found 
1
N pairs
 yij
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ij
z found 
1
N pairs
z
ij
ij
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Improving the Straight Line
Vertex Finder
1.
Add a cut on the distance of closest approach (DCA)
between the two straight lines
 A pair of tracks is not used for the vertex estimation if
their distance of closest approach is > fDCAcut
2.
Use a weighted mean of the 2 DCA points
 In order to take into account the errors on the tracks
parameters
3.
Calculate a parameter representing the dispersion of the
vertices given by the track pairs (fSigma)
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DCA cut effect
No DCAcut
X coord
RMS=179 μm
Finder- MC (mm)
Y coord
RMS=183 μm
Finder- MC (mm)
Z coord
RMS=166 μm
Finder- MC (mm)
fDCAcut = 1.5 mm
RMS=179 μm
Finder- MC (mm)
RMS=182 μm
Finder- MC (mm)
RMS=165 μm
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FinderMC (mm)
fDCAcut = 0.7 mm
RMS=178 μm
Finder- MC (mm)
RMS=181 μm
Finder- MC (mm)
RMS=163 μm
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Weighted mean effect
Arithmetic mean
X coord
Weighted mean
RMS=179 μm
RMS=179 μm
Finder- MC (mm)
Y coord
Finder- MC (mm)
RMS=183 μm
RMS=183 μm
Finder- MC (mm)
Z coord
Finder- MC (mm)
RMS=166 μm
Finder- MC (mm)
Improved
resolution
on Z
RMS=160 μm
Elena Bruna
Finder- MC (mm)
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Vertices dispersion
Dispersion fSigma = standard deviation of the 3 vertex
estimations obtained from each track pair
The DCA cut (at
0.7 mm) reduces
the dispersion
fSigma (cm)
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All events
Cutting on fSigma
RMS=700 μm
Finder- MC (mm)
fSigma < 0.4 cm
• A cut fSigma < 0.4 cm cuts 0.5% of
the events and ≈30% of the overflows
and underflows (i.e. events for which
the VertexFinder misses the true
vertex by more than 1 mm)
RMS=224 μm
Finder- MC (mm)
• A cut fSigma < 0.07 cm (700 mm) cuts
6.4% of the events and gives a RMS
of 151 mm (for X coordinate)
fSigma < 0.07 cm
RMS=151 μm
Finder- MC (mm)
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Another improvement:
Helix vertex finder
•
Based on the Distance of Closest Approach (DCA) between
helices

•
Does not use a Straight Line Approximation as the old one
Main steps
 The method receives N (N=3 in our case) tracks as input
 For each pair of tracks, the coordinates of the 2 points of closest
approach are calculated
 An estimation of the secondary vertex from each pair of tracks is
obtained averaging the coordinates of the points defining the DCA.
Two different implemetations: arithmetic vs. wieghted mean
 The coordinates of secondary vertex are determined averaging among
all the track pairs:
x found 
1
N pairs
 xij
ij
y found 
1
N pairs
 yij
ij
z found 
1
N pairs
z
ij
ij
 The dispersion of the vertices given by the track pairs is calculated
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Results from the helix finder
Straight Line Finder
X coord
Helix Finder
RMS=169 μm
RMS=179 μm
Finder- MC (mm)
Finder- MC (mm)
Y coord
RMS=171 μm
RMS=183 μm
Finder- MC (mm)
Finder- MC (mm)
Z coord
RMS=162 μm
RMS=166 μm
Finder- MC (mm)
Helix finder
has better
resolution
and also a
lower number
of overflows
and
underflows
(≈400 instead
of ≈650)
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Finder- MC (mm)
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DCA cut effect on helix finders
fDCAcut=1 cm
X coord
RMS=169 μm
Finder- MC (mm)
Y coord
RMS=171 μm
Finder- MC (mm)
Z coord
RMS=162 μm
Finder- MC (mm)
fDCAcut=1.5 mm
RMS=168 μm
Finder- MC (mm)
RMS=170 μm
Finder- MC (mm)
RMS=161 μm
Elena MC
Bruna
Finder(mm)
fDCAcut=0.7 mm
RMS=167 μm
Finder- MC (mm)
RMS=169 μm
Finder- MC (mm)
RMS=158 μm
Finder- MC (mm)
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Weighted mean effect on helix finder
Weighted mean
Arithmetic mean
X coord
RMS=168 μm
RMS=169 μm
Finder- MC (mm)
Y coord
Finder- MC (mm)
RMS=171 μm
RMS=169 μm
Finder- MC (mm)
Z coord
Finder- MC (mm)
RMS=162 μm
Finder- MC (mm)
Improved
resolution
on Z
RMS=154 μm
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Finder- MC (mm)
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Vertices dispersion on Helix Finder
The DCA cut
reduces the
dispersion
fSigma (cm)
Same distribution as for Straight Line finder
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All events
Cutting on fSigma
RMS=480 μm
Finder- MC (mm)
fSigma < 0.4 cm
• A cut fSigma < 0.4 cm cuts 0.5% of
the events and ≈35% of the overflows
and underflows (i.e. events for which
the VertexFinder misses the true
vertex by more than 1 mm)
RMS=209 μm
Finder- MC (mm)
fSigma < 0.07 cm
• A cut fSigma < 0.07 cm (700 mm) cuts
5.6% of the events and gives a RMS
of 140 mm (for X coordinate)
RMS=140 μm
Finder- MC (mm)
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New secondary vertex finder
Straight Line Approximation used → analytic method
Vertex coordinates (x0,y0,z0)
from minimization of:
D  d  d 2  d3
2
2
1
2
2
Where: d1,d2,d3 are the distances (weighted with the
errors on the tracks) of the vertex from the 3 tracks:
 x1  x0 

d1  
 sx 
2
2
2
 y1  y0   z1  z0 
 



 s

y

  sz 
σx = σy
2
P1 (x1,y1,z1)
d1
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Secondary
Vertex
(x0,y0,z0)
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Resolution of the vertex finder
RMS x
RMS y
At high Pt of D+ (Pt>5-6 GeV/c), the RMS in the bending plane increases,
instead of going down to ~15µm (spatial pixel resolution) as expected.
RMS z
Conclusion
New method improves RMS of
~40μm for PtD+ ~ 2GeV/c for x, y
and z with respect to previous
Helix vertex finder based on DCA
of Bruna
pairs of tracks.
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Resolution at high Pt /1
Checks with events only made of pions show that the RMS on the bending
plane:
Decreases down to 50 µm if the 3 tracks have Pt ~ 2 GeV/c
Reaches a value of ~20 µm (in agreement with spatial pixel resolution) if
the 3 tracks have Pt =100 GeV/c
3 pion vertex: RMS in the bending plane vs. Pt
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Resolution at high Pt /2
In the signal events, as the Pt of the D+ increases, the “daughters” become
more and more co-linear, resulting in a worse resolution along the D+
direction.
y
y’
π+
x’
π+
K-
bending plane
rotated
D+
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x
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Resolution in the rotated frame /1
Along the Pt of the D+ (x’ coord.)
Orthogonal to the Pt of the D+ (y’ coord.)
→ Along the Pt of the D+: as Pt increases (for Pt>5-6 GeV/c) the angles between
the decay tracks become smaller: in this coordinate the RMS increases
→ Orthogonal to the Pt of the D+: the RMS decreases as expected
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Resolution in the rotated frame /2
Ratios:
RMS along Pt
RMS orthog Pt
RMS along Pt
RMS z
RMS orthog Pt
RMS z
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Vertices dispersions/1
fSigma  d1  d 2  d3
2
2
2
Δx = XVertex FOUND – XVertex MC
Δx < 1000 μm
1000<Δx <3000 μm
3000<Δx <5000 μm
Δx > 5000 μm
fSigma bigger for
bad vertices
fSigma (cm)
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Vertices dispersions/2
Vertices taken / Vertices Tot (“True” vertices)
“Fake” vertices (tracks coming from 3
different D+ vertices)
• fSigma < 0.7 cm cuts ~1% of the events
and gives a RMS of 130 μm
• fSigma < 0.5 cm cuts ~6% of the events
and gives a RMS of 110 μm
RMS x (μm)
(for X coordinate)
Mean x (μm)
Cut on fSigma
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Conclusions on the finders
The Straight Line vertex finder:
♣ DCA cut: negligible effect on the RMS of the residual distributions, slightly
reduced number of overflows and underflows
♣ The use of a weighted mean: improves Z resolution by ≈6 mm
♣ Cutting on the dispersion fSigma: removes the events for which the
VertexFinder misses the true vertex by more than 1 mm and improves the
resolution
The Helix vertex finder:
♦ Has better resolution w.r.t. Straight Line finder (by approximately 10 mm)
♦ Has less overflows and underflows w.r.t. Straight Line finder
♦ DRAWBACK: the DCA between helices is obtained by minimization
♦ DCA cut, weighted mean and fSigma cut: improve the resolution
The Minimum Distance vertex finder:
♥ Has better resolution w.r.t. Helix finder (by approximately 30 mm)
♥ Has less overflows and underflows w.r.t. previous finders
♥ Is an analytic method
♥ Weighted mean and fSigma cut: improve the resolution
♥ Is presently THE candidate for first D+ analysis
A cut on fSigma has to be tuned (it can be done at analysis level)
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D+ selection strategy
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Tuning the cuts
GOAL: tune the cuts on both signal and background events and find the
cuts giving the best S/B. (S/B = 11% was found for the D0K-+)
CUT TIPOLOGIES:
1. On the single tracks used to “feed” the vertexer (Particle Identification,
pT, track impact parameter)
 reduce the number af all the possible combinations of track-triplets
in a central Pb-Pb collision (~ 1010 without any initial cut!!). It MUST be
cut by 4-5 orders of magnitude before using the more time-consuming
vertexer.
In progress.
2. Once the triplets are combined, additional cuts (invariant mass and
eventually pT, impact parameter) are mandatory before using the
vertexer. These cuts are done on the triplets.
To be done.
3. The third kind of cuts is applied on the quality of the secondary vertices
found (vertex dispersion-fSigma, pointing angle,…)
To be done.
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Single track cuts /1
GOAL: find a compromise between the
number of background triplets and the
number of signals we want to take
HOW: for each triplet (both signal and bkg)
a loop on all the possible cuts (d0,Pt ,Pt K)
is done
%
SIGNAL
TAKEN
Cut on the track
impact parameter (d0)
Particle Id.
given by the
generation:
initial approach
Pt cut 
(GeV/c)
Pt cut K
(GeV/c)
MINIMUM
Triplet BKG
taken
d0 cut
(mm)
1-2
1,200
1,175
120
131
3-4
0,875
0,775
95
77.000
4-5
1,400
1,150
0
250.000
15 - 20
1,000
0,800
0
7.600.000
25 - 30
0,750
0,550
0
100.000.000
45 - 50
0,525
0,350
0
1.000.000.000
75 - 80
0,350
0,325
0
6.000.000.000
90 - 95
0,275
0,300
0
10.000.000.000
The number of BKG triplets is reduced by a
factor of ~100 when doing the cut on the
Invariant Mass within 3s (see slide 22)
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Single track cuts /2
Triplet BKG
Bkg=Triplets
No cut on the track
impact parameter (d0)
Particle Id.
given by the
generation:
initial approach
Pt cut 
(GeV/c)
Pt cut K
(GeV/c)
d0 cut
(mm)
% MAX
signal taken
101 - 102
1,325
1,200
105
0,9
104 - 105
0,900
0,800
85
3,1
105 - 106
1,225
1,000
0
6,0
106 - 107
0,975
0,775
0
11,0
107 - 108
0,750
0,600
0
19,4
1010 – 1011
0,000
0,000
0
100,0
The number of BKG triplets is reduced by a factor of
~100 when doing the cut on the Invariant Mass
within 3s (see slide 22)
Cut on d0  lower
cuts on Pt (useful
up to Bkg ~105)
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Tuning the single track cuts /2
When tuning a cut, one has to
keep in mind how the Pt
distribution of the D+ is modified
Pt reconstructed D+
Mean=2.5 GeV/c
Pt reconstructed D+
Pt cut (p) = 0.75 GeV/c
Pt cut (K) = 0.6 GeV/c
Mean=1.8 GeV/c
Ratio:
With cut / Wo cut
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Perspectives for the
measurement of D+ elliptic flow
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Measurement of v2
Elliptic Flow = correlation of particle emission angles with the reaction plane
(i.e. w.r.t the impact parameter of the collision)
 Calculate the 2nd order coefficient of
Fourier expansion of particle azimuthal
distribution relative to the reaction plane
v2  cos(2(  RP ))
 The reaction plane is unknown.
 Estimate the reaction plane from particle
azimuthal anisotropy:
 n = Event plane = estimator of the
unknown reaction plane
 w sin i 
1
1   i

n  tan


n
w
cos


i
i


 Calculate particle distribution relative to
the event plane
v'2  cos(2(  2 ))
 Correct for event plane resolution
v'2
v2 
cos22  RP 
 Resolution contains the unknown RP
 Can be extracted from sub-events
Event plane resolution
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Motivation and Method

•
•

GOAL: Evaluate the statistical error bars for
measurements of v2 for D± mesons decaying in K
v2 vs. centrality (pT integrated)
v2 vs. pT in different centrality bins
TOOL: fast simulation
•
•
•
Assume to have only events with signal
Generate ND±(b, pT) events with 1 D± per event
For each event
1.
2.
3.
4.
5.
Generate a random reaction plane (fixed RP=0)
Get an event plane (with correct event plane resolution)
Generate the D+ azimuthal angle (φD) according to the probability
distribution p(φ)  1 + 2v2 cos [2(φ-RP)]
Smear φD with the experimental resolution on D± azimuthal angle
Calculate v′2(D+), event plane resolution and v2(D+)
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D+ azimuthal angle resolution
MEAN
RMS
Average  resolution =
8 mrad = 0.47 degrees
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D+ statistics
bmin-bmax
(fm)
s inel
Pb-Pb
(%)
Nevents
(106)
Ncc
D±
per
event
yield
per
event
0-3
3.6
0.72
118
45.8
3-6
11
2.2
82
31.8
6-9
18
3.6
42
16.3
9-12
25.4
5.1
12.5
4.85
12-18
42
8.4
1.2
0.47
Nevents for 2·107 Minimum Bias
triggers (without any requirement on
the impact parameter of the collision)
D+ selected after all the cuts is
still missing: for the time being
 e=1.5% (same as D0)
ND±(b, pT) selected = e × D+ reconstructed
 Total number of ND±(b, pT) selected
Normalized to 2·107 Minimum Bias Events
Elena Bruna
54
Results: v2 vs. centrality
2·107 Minimum
Bias events
bmin-bmax N(D±)selected sv2)
0-3
1070
0.024
3-6
2270
0.015
6-9
1900
0.016
9-12
800
0.026
12-18
125
0.09
• Error bars quite large


Would be larger in a scenario with worse event plane resolution
May prevent to draw conclusions in case of small anisotropy of D mesons
Elena Bruna
55
Results: v2 vs. pT
2·107 MB events
pT limits N(D±)sel
sv2)
pT limits N(D±)sel
sv2)
pT limits N(D±)sel
sv2)
0-0.5
140
0.06
0-0.5
120
0.06
0-0.5
50
0.10
0.5-1
280
0.04
0.5-1
230
0.05
0.5-1
100
0.07
1-1.5
390
0.04
1-1.5
330
0.04
1-1.5
140
0.06
1.5-2
360
0.04
1.5-2
300
0.04
1.5-2
125
0.06
2-3
535
0.03
2-3
450
0.03
2-3
190
0.05
3-4
250
0.05
3-4
210
0.05
3-4
90
0.07
4-8
265
0.05
4-8
220
0.05
4-8
95
0.07
8-15
50
0.11
8-15
40
0.11
8-15
20
0.15
Elena Bruna
56
Summary and work plans
• Preparatory checks on the kinematics and on the
reconstructed signal events: completed
• Secondary Vertex: completed
 the method of the Minimum Distance of 3 tracks is presently THE
candidate for first D+ analysis
 cuts on fSigma will be tuned at the analysis level
• D+ analysis cuts
 the work on the cuts on “single tracks” to feed the vertexer is in
progress: Pt, impact parameter, PID.
 The work on the cuts in the “triplets” and on the secondary vertices has
to be done.
• Analysis on D+ elliptic flow: in progress
Elena Bruna
57