Open charm reconstruction in the ALICE experiment

1
Secondary vertex reconstruction in the central
region
Elena Bruna
University of Torino
ALICE progress report CERN, Jan 9th 2006
2
Outline

• Precise secondary vertex determination needed
  for open charm analysis
• Physics motivations of open charm analysis in
  Heavy Ion Collisions
• Measurement of open charm in the ALICE
  experiment
• Channel under study D ? K-pp
• Event generation and reconstruction
• Kinematics
• Reconstruction of the secondary vertex
• Selection strategy
• Summary and work plans

3
Heavy flavour reconstruction in ALICE

• Weakly decaying charm and beauty states

• Need for high precision vertex detector
• tracks from heavy flavour weak decays are
  typically displaced from primary vertex by
  100s µm
• resolutions of a typical heavy flavour apparatus
  10s µm

4
Motivations for the Open Charm physics in Heavy
Ion Collisions
5
Heavy quarks production

• Parton processes (gluon fusion) at early stages
  of the collision (timescale 1/mQ lt ?QGP 10 fm
  at LHC)

• ? Presence of nuclear shadowing
• PDFs in the nucleus different from PDFs in free
  proton
• R ratio of nuclear to nucleon PDFs

charm

• 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)

6
Heavy quarks as probes of nuclear medium /1

• open QQ production (not Drell-Yan) natural
  normalization for QQ studies
• ? Quarkonia enhancement at low PT and
  suppression at high PT.

• c, b have long lifetime (gt ?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 are quenched.
• Heavy quarks are expected to lose less energy
  than light quarks.
• High ?E ? suppression of the produced particles
  (at high PT) ? RAA?1

Nuclear modification factor
It depends on the properties of the medium (gluon
density, temperature and volume), it provides
information on such properties.
7
Heavy quarks as probes of nuclear medium /2

• Studies of final state effects
• 2) anisotropic flow on the transverse plane
• 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)
Elliptic flow coefficient
High opacity of the medium (strongly interacting)
? high anisotropic flow ? high v2
v2 provides information on the opacity of the
medium.
8
PHENIX results
Azimuthal anisotropy
Nuclear modification factor
The medium is so strongly interacting that c
quarks suffer significant rescattering and
develop azimuthal anisotropy
The medium is so dense that c quarks lose energy
(by gluon radiation)
9
Measurement of open charm in the ALICE experiment

10
Time Projection Chamber (TPC) Tracking, PID
(dE/dx) -0.9lt?lt0.9
ALICE _at_ LHCsetup
HMPID
B 0.5 T
TRD
MUON SPECTR..
PHOS
Inner Tracking System (ITS) 6 SILICON layers
(pixel, drift, strip) Vertices reconstruction,
PID (dE/dx) -0.9lt?lt0.9
Time Of Flight (TOF) Tracking, PID
(time) -0.9lt?lt0.9
Size 16 x 26 m Weight 10,000 tons
11
Detector performance PT
MEAN (Pt-Ptsim)/Ptsim
Mean 2/ RMS 1
Charmed mesons ct 100-300 mm A
good tracking system is required to separate
primary and secondary vertex this is done mainly
by ITSTPC
Different Pt ranges
RMS (Pt-Ptsim)/Ptsim
Different Pt ranges
Magnetic field 0.5 T
12
Detector performance d0
SIGMA PULL (fit)
d0 track impact parameter
Primary vertex
Reconstructed track
0.4ltPtlt0.6 GeV/c
MEAN PULL (fit)
13
Channel under study D ? K-pp
14
Why D ? K-pp ?
Advantages

• D has a long mean life (ct 311mm compared to
  123 mm of the D0)
• D ? K-pp can be fully reconstructed in the
  detector
• D ? K-pp has a relatively large branching
  ratio (BR9.2 compared to 3.8 for D0 ? K-p).

drawbacks

• Combinatorial background for this 3-body channel
  is larger than for D0 ? K-p.
• The average PT of the decay product is softer (
  0.7 GeV/c compared to 1 GeV/c for the D0)

15
Hadronic 3-charge-body decays of D

D?K-?? BR 9.2
16
Simulation strategy
Our purpose exclusive reconstruction of D in
the ALICE barrel (Inner Tracking System employed
in the search for secondary vertices)
Too large statistics (108 events) would be
required to study the signal!!
Central Pb-Pb event (blt3.5 fm, dN/dy 6000,
vs5.5 TeV)
9 D/D- in ylt1
Signal and background events separately generated
with the Italian GRID

• 5000 signal events with only D decaying in Kpp
  (using PYTHIA)
• Check the kinematics and the reconstruction
• Optimize the vertexing algorithm
• 20000 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

17
Kinematics
p
Comparing with Pb-Pb central events (ONLY
generation, NO propagation and reconstruction in
the detector) PT distributions
Mean 0.67 GeV/c Mean 0.50 GeV/c
nonresonant D decay (PYTHIA)
K
HIJING central (normalized to the same area)
Mean 0.87 GeV/c Mean 0.65 GeV/c
K and p from D are harder than K and p produced
in a Pb-Pb event
18
Analysis strategy

• PT of the decay tracks is soft 0.7-0.8 GeV/c
• The magnetic field is low - 0.5 T - to allow the
  reconstruction of soft particles ( 7000 in
  ylt1) ? huge combinatorial background
• A devoted trigger for D ?
  K-pp seems not possible.
• Only the centrality trigger
  is considered.
• For each kind of event (Pb-Pb, p-p) the
  signal selection strategy is based on
• Good secondary vertex reconstruction capability
  (c? (D) 300mm ? resolution of 200mm would be
  bad, 50mm would be a dream)
• Efficient system of cuts to discriminate the
  signal from the background
• On the single track (PT,d0, Particle
  Identification)
• On the signal candidates (invariant mass,
  distance between primary and secondary vertices,)

19
Reconstruction of the secondary vertex for D ?
K-pp

• 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

20
Vertex finder

• Originally developed to find the primary vertex
  in p-p
• Based on the Straight Line Approximation of a
  track (helix)

• Main steps
• The method receives N (N3 in our case) tracks as
  input
• Each track is approximated by a straight line in
  the vicinity of the primary vertex
• An estimation of the secondary vertex from each
  pair of tracks is obtained evaluating the
  crossing point between the 2 straight lines
• The coordinates of secondary vertex are
  determined averaging among all the track
• pairs

track1
track3
track2
21
Results with the Straight Line Vertex Finder
Straight Line
Improvements
RMS179 µm
X coord

• Add a cut (DCAcut) on the distance of closest
  approach (DCA) between the two straight lines
• negligible effect on RMS,
• cuts only 1 of good vertices
• to be tested on background events
• Use a weighted mean of the 2 points defining the
  DCA (take into account the errors on the tracks
  parameters)
• improves Z resolution by 6mm

Finder- MC (mm)
Y coord
RMS183 µm
Finder- MC (mm)
RMS166 µm
Z coord
Finder- MC (mm)
22
From Straight Line to Helix
Straight Line
Helix
RMS169 µm
RMS179 µm
Further development use of the track as helix,
without the straight line approximation (no
longer analytic, minimization is required)
X coord
Finder- MC (mm)
Finder- MC (mm)
RMS171 µm
Y coord
RMS183 µm
Result very small improvement (10mm) WHY?
Finder- MC (mm)
Finder- MC (mm)
RMS166 µm
Z coord
RMS162 µm
Finder- MC (mm)
Finder- MC (mm)
23
Straight Line Approximation
Straight Line Approximation
Decay dist 300 mm
track
d (µm)
Secondary vertex
d (µm) is the distance between the secondary
vertex and the tangent line
Primary vertex
PT (GeV/c)

• d is of the order of tens of nm
• the small differences between Helix and Straight
  Line Finder seem not to be due to the linear
  approximation, but rather to the fact that in the
  Helix method the errors on the track parameters
  are considered in the minimization

PT 0.5 GeV/c
d (µm)
Decay dist (µm)
24
New secondary vertex finder

• Straight Line Approximation used ? analytic
  method
• The 3 tracks are taken at the same time, no
  pairs of tracks

Vertex coordinates (x0,y0,z0) from minimization
of
Where d1,d2,d3 are the distances (weighted with
the errors on the tracks) of the vertex from the
3 tracks
P1 (x1,y1,z1)
SecondaryVertex (x0,y0,z0)
sx sy
d1
25
Resolution of the vertex finder
RMS x
RMS y
At high Pt of D (Ptgt5-6 GeV/c), the RMS in the
bending plane increases, instead of going down to
15µm (spatial pixel resolution) as expected.
RMS z
New method improves RMS of 40µm for D Pt
2GeV/c for x, y and z with respect to previous
Helix vertex finder based on DCA of pairs of
tracks.
26
Resolution at high Pt
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.
p
p
K-
bending plane
D
27
Resolution in the rotated frame
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
Ptgt5-6 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

• 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

28
Track dispersion cut on fSigma
(for X coordinate)
Accepted Vertices / Tot Vertices (True vertices)
Fake vertices (tracks coming from 3
different D vertices)

• fSigma lt 0.7 cm cuts 1 of the events and gives
  a RMS of 115 µm

• fSigma lt 0.4 cm cuts 30 of the events and
  gives a RMS of 100 µm

29
Conclusions on the finders

• The Straight Line vertex finder
• DCA cut negligible effect on the RMS of the
  residual distributions, slightly reduced number
  of good vertices (1)
• The use of a weighted mean improves Z resolution
  by 6 mm
• Cutting on the dispersion fSigma improves the
  resolution (by 30mm)

• The Helix vertex finder
• Has better resolution w.r.t. Straight Line
  finder (by approximately 10 mm)
• DRAWBACK the DCA between helices is obtained by
  minimization
• Weighted mean improves Z resolution by 8 mm
• fSigma cut improves the resolution (by 30 mm)

• The Minimum Distance vertex finder
• Has better resolution w.r.t. Helix finder (by
  approximately 40 mm)
• Has less overflows and underflows w.r.t.
  previous finders
• Is an analytic method
• Weighted mean and fSigma cut improve the
  resolution (by 20mm)
• Is presently THE candidate for first D analysis

A cut on fSigma has to be tuned (it can be done
at analysis level)
30
Secondary vertex for pp

• Better detector performance
• Charm yield lower than central Pb-Pb events
• Lower combinatorial background
• S/B larger by a factor of 106
• Higher uncertainity of the primary vertex position

31
D selection strategy
32
Before tuning the cuts /1
Reconstructed signal events D invariant mass
Mean
Integrated over PT
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.
MINV Resolution (SIGMA of the gaussian fit)
Knowledge of MINV resolution vs PT is important
when selecting the signal candidates
33
Before tuning the cuts /2
Reconstructed signal events Dalitz Plots
From reconstructed tracks ( the info
given by the generation are taken into account)
Resonant
Non resonant
M2Kp2
M2Kp2
M2Kp1
M2Kp1
Knowledge of Dalitz Plot shape is important when
selecting the signal candidates
34
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-p)

• CUT TYPOLOGIES
• 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.
• Once the triplets are combined, additional cuts
  (invariant mass, Dalitz plots and, possibly,
  impact parameter based) are mandatory before
  using the vertexer. These cuts are done on the
  triplets.
• Under study. Also the possibility of
  starting from a pair of opposite sign tracks.
• The third kind of cuts is applied on the quality
  of the secondary vertices found (fSigma, distance
  between primary and secondary vertices, pointing
  angle,)
• To be done.

35
Single track cuts
Cut on the track impact parameter (d0)
Pions
Kaons
Particle Id. given by the generation initial
approach
107 central events
First choice for D analysis
36
Tuning the single track cuts
When tuning a cut, one has to keep in mind how
the Pt distribution of the D is modified
Pt reconstructed D Mean2.66 GeV/c
Pt reconstructed D Pt cut (p) 1.275 GeV/c Pt
cut (K) 1.25 GeV/c d0 cut 105 mm Mean7.9
GeV/c
Ratio With cut / Wo cut
37
D elliptic flow measurement perspectives
2107 Minimum Bias events

• 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

38
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
• secondary vertex for pp still to do the
  feasibility study
• 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 is in progress.
• Analysis on D elliptic flow in progress

Thanks to Karel Safarik, Massimo Masera and
Francesco Prino
39
Backup slides
40
(No Transcript)