Transcript The Physics of the ALICE Inner Tracking System

THE PHYSICS OF
THE ALICE INNER
TRACKING
SYSTEM
Elena Bruna, for the ALICE Collaboration
Yale University
24th Winter Workshop on Nuclear Dynamics, South Padre
Island 5-12 April 2008
OUTLINE
The ALICE Inner Tracking System (ITS)
 Performance of the ITS

Tracking
 Primary vertex reconstruction
 Secondary vertex reconstruction (from heavy flavor decays)
 Particle identification

Physics analyses with the ITS
Hadronic and semi-leptonic decays of heavy-flavor particles
 Multiplicity studies


Conclusions
2
Elena Bruna, Yale University

THE INNER TRACKING
SYSTEM (ITS)

SSD
SDD
6 layers of
Silicon
detectors:
Pixel Chambers
(SPD): 2
innermost layers
 Drift Chambers
(SDD): 2
intermediate
layers
 Double-sided
Strip Chambers
(SSD): 2
outermost layers

Lout=97.6 cm
Rout=43.6 cm
SSD
SPD
3
SDD
Elena Bruna, Yale University
SPD
ALICE @ LHC
setup
B = 0.5 T
HMPID
TRD
PHOS
TOF
Inner Tracking System
(ITS):
6 SILICON layers (pixel, drift,
strip)
Vertices reconstruction, PID
(dE/dx)
4
-0.9<<0.9
MUON SPECTR..
Elena Bruna, Yale University
TPC
Size:
16 x 26 m
Weight: ~10,000 tons
STATUS OF THE ITS

The ITS was put inside the TPC
in March-April 2007

First cosmics seen in February!
• Tracking worked in the SPD
• Aligned clusters seen in SPD
and SDD
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
The ITS is ready to collect the first pp collisions!
Elena Bruna, Yale University
SPD+SDD
ITS PERFORMANCE:
TRACKING (1 of 3)

Tracking is the major challenge in
ALICE: ~7000 tracks in a central
HIJING Pb-Pb event at 5.5 TeV in the
ITS + TPC acceptance
RICH
ITS
TOF
TPC
Elena Bruna, Yale University
TRD
PHOS
Tracking strategy:
• from TPC ‘seeds’, tracks are extrapolated towards the ITS with the
Kalman filter technique and then backpropagated to the outer
detectors
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TRACKING (2 OF 3)

Elena Bruna, Yale University
Tracking Stand-alone in the ITS:
•
used in the reconstruction software
•
tracks not reconstructed by the TPC
•
first day physics (track multiplicity and
PID), both in pp and Pb-Pb
•
useful in case of initial alignment
problems with the TPC
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ITS PERFORMANCE:
TRACKING (3 OF 3)
Elena Bruna, Yale University
impact parameter resolution
(on the bending plane) vs pT
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ITS PERFORMANCE:
PRIMARY VERTEX



Primary vertex reconstruction: more problematic in pp than in Pb-Pb
Pb-Pb: primary vertex resolution dominated by the mis-alignment
pp: 2 steps for primary vertex finding:
Before tracking: using ITS pixels (“tracklets”)
 After tracking: using tracksbetter
Elena Bruna, Yale University

Tracks from ITS+TPC
Pixels from ITS
(w. beam line
constraint)
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# tracklets
# tracklets
ITS PERFORMANCE:
SECONDARY VERTEX
(my thesis work)
Xfound-Xtrue



Yfound-Ytrue
Zfound-Ztrue
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Elena Bruna, Yale University

Charmed mesons: ct ~ 100-300 mm
A good tracking system is required to
separate primary and secondary vertex
Good resolution on primary and
secondary vertices
RMS ~ 120 mm: good to measure vertices
displaced of 300 mm
SECONDARY VERTEX
FINDER
y
y’
π+
x’
KElena Bruna, Yale University
bending plane
rotated
π+
D+
x
Along Pt D+ coord
Orthog Pt D+ coord
z coord
Elena Bruna
ITS PERFORMANCE: PID



Elena Bruna, Yale University
Based on specific ionization (dE/dx) in the SDD and SSD (4 Silicon
layers)
Add information to the PID given by the TPC (combined-Bayesian
PID)
Identify tracks not reconstructed by the TPC:
 Low momentum
 Out of TPC acceptance
 Dead zones of TPC (between sectors)
Protons
Kaons
Pions
electrons
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PHYSICS ANALYSES RELATED
WITH THE ITS
 Measurement




D0
D+
D+s
Λc
Kπ (B.R. 3.8%)
Kππ (B.R. 9%)
KKπ (B.R. 5.2%, through ϕ or K0*)
Kpπ (B.R. 5%)
 Semi-leptonic

B
decays of beauty mesons:
e+X (B.R. 10%)
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Elena Bruna, Yale University
of the charged particle multiplicity
with the silicon pixel detector of the ITS
 Exclusive reconstruction of open-heavy-flavor
particles:
SPD

Why multiplicity with pixels:
 available in a short time
 advantages over reconstructed tracks (ITS+TPC)


Elena Bruna, Yale University

Why multiplicity:
 first measurement in pp collisions for ALICE

global observable characterizing the event

comparison with results obtained at lower energies
larger acceptance coverage
only alignment of the two pixel layers required
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D0 K-Π+
S/B ≈ 10%
 Significance for 1 month
Pb-Pb run: S/√(S+B) ≈
40

Elena Bruna, Yale University
statistical.
systematic.
15
+
+
+
D K Π Π (1)

Analysis strategy (1)
Cuts on single tracks (pT, transverse impact parameter)
primary
 Cuts on pairs:
K
vertex
p
 distance primary vertex-Kπ vertex:δ
d

Elena Bruna, Yale University

Product of impact parameters:
Background
d0K X d0π2
d0K X d0π2
Signal
d0K X d0π1
When (d0K x d0p1)<0 & (d0K x d0p2)<0:
empty region kinematically not allowed
d0K X d0π1
 selection based on the products of
impact parameters of the two Kp pairs:
25% of BKG triplets rejected
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D+K-Π+Π+ (2)

Cuts on the triplets Kππ :
Quality of the secondary vertices
 Global optimization on a hyper-surface of:

Distance between prim and sec vertices
 Maximum transverse momentum among
the 3 tracks pM=Max{pT1,pT2,pT3}
 cosϑpoint
2
2
2
 s=d01 +d02 +d03

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Results for Pb-Pb
D+K-π+π+ produced in 4π
3 dau in acceptance
3 dau reconstructed
D+ sel (Id. PID)
D+ sel (Real PID)
D+ sel (No PID)
17
Elena Bruna, Yale University
qpoint
pT D+
D+K-Π+Π+ (3)
Results for pp (No PID)
Elena Bruna, Yale University
0<pT<2 GeV/c
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
DS+K-K+Π+
WHY?


To measure charm yield more precisely we need to measure as many channels as we can
Study of different ways of hadronization:
Significance
 String fragmentation:
Ds+ (cs) / D+ (cd) ~ 1/3
DsϕπKKΠ
 Recombination:

Analysis:

Resonance separation:



DsϕπKKΠ (2.16%)
DsK0*KKKΠ (2.5%)
Variables considered:






Elena Bruna, Yale University
Ds+ (cs) / D+ (cd) ~ N(s)/N(d) (~ 1 at LHC?)
cos ϑpoint
cos φopening
Distance between primary and secondary vertex
Sum of impact parameters squared
Dispersion of secondary vertex
Results:
Analysis feasible in Pb-Pb down to
pT=3GeV/c
pT(GeV/c)
Significance
DsK0*KKKΠ
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
pT(GeV/c)
B MESONS VIA B e e X

Inclusive measurement of electrons coming from
semi-electronic decay of beauty hadrons
need good electron identification: combined PID in
TPC (dE/dx) + TRD (+EMCal in future)
 good measurement of the track impact parameter

Elena Bruna, Yale University
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SUMMARY

Interesting analyses will be possible with the ITS,
thanks to its excellent vertexing and tracking
capabilities and PID:
Heavy flavor physics:



Elena Bruna, Yale University

Hadronic and semi-leptonic decays of charm and beauty particles
Charged multiplicity, the “day one” measurement
ALICE is looking forward to collecting wonderful data.
Thank you
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Elena Bruna, Yale University
BACKUP SLIDES
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ITS ALIGNMENT
Elena Bruna, Yale University
xy
250 mm
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Significance
normalized to 109 pp
MB events
d
s=d02
cosqpoint
RESULTS FOR 3< PT(D+)<5
GEV/C
Elen
a
Bru
na
cosqpoint
ITS DETECTOR
RESOLUTIONS
SPD
SDD
SSD
(r = 4 & 7 cm)
(r = 14 & 24 cm)
(r = 39 & 44 cm)
spatial resolutions
Rφ  z [mm3]
12  120
38  20
20  830
Two-track resolution
(rφ) [mm]
100
200
300
Two-track resolution
(z) [mm]
850
200
300
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ITS DIMENSIONS
type
R (cm)
± z (cm)
1
Pixel
3.9
14.1
2
pixel
7.6
14.1
3
drift
15.0
22.2
4
drift
23.9
29.7
5
strip
37.8/38.4
43.1
6
strip
42.8/43.4
48.9
Elena Bruna, Yale University
layer
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SECONDARY VERTEX
FINDER


Tracks (helices) approximated with Straight Lines: analytic
method
Vertex coordinates (x0,y0,z0) from minimization of:
D  d  d 2  d3
2
2
1
2
d1 d3
d2
Secondary
Vertex (x0,y0,z0)
2
2
 xi  x0   yi  y0   zi  z0 
2
 

where:d i       
   
xi
yi
zi

 

 
2


xi, yi, zi are the errors on the track parameters
Quality of the vertexer (not weighted):
 2  d12  d 2 2  d32
2
E.Br
una
COMBINING KP PAIRS
primary
vertex
K and p have opposite charge sign
d
 Cut on the distance d between the vertex of the 2
tracks and the primary vertex

K
p
• Working point: d>700 mm
• Selected SIG=67%
• Selected BKG=5%
d (mm)
SECONDARY VERTEX FINDER ON
THE TRIPLETS
Secondary vertex resolution: ~120 mm
 Cut on the quality of the Vertex:

 2  d12  d 2 2  d32
BLACK: signal
• Working point:  < 200 mm
RED: BKG Kpp
Triplets

(optimized in pT ranges of D+)
• Selected SIG=50%
• Selected BKG=1%
• S/B~3 x 10-4: still too small
RESULTS:
+
+
+
D K P P IN
PB-
PB

Selection efficiency and pT spectra:

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selected D 
 
D with 3 reconstructed daughters
pT integrated ε (D+) ≈ 1.5% (Ideal PID), 0.6% (Real PID), 1% (no
PID)
E.Br
una
FEED-DOWN FROM
BEAUTY


D+ from B are more displaced
The cut on distance between primary to secondary vertex
increases the fraction of selected D+ coming from B decay
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Histograms
normalized to the
same area
Contamination K vs d
d~1000mm  K
E.Br
=10%
una
Hadronic 3-charge-body decays of D+
D±
I(JP) = ½ (0-)
Elena Bruna
m = 1869.4 MeV/c2
ct = 311.8 mm
(PDG ’04)
D+K-p+p+
BR = 9.2 %
D+→K-p+p+
Non Resonant BR = 8.8 %
D+→K*0(892)p+→K-p+p+
Resonant
BR = 1.3 %
D+→K*0(1430)p+→K-p+p+ Resonant
BR = 2.3 %
D+→K*0(1680)p+→K-p+p+ Resonant
BR = 3.8·10-3 %
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Kinematics (1)
Elena Bruna
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
p
Mean = 0.67 GeV/c
Knowledge of the PT shapes of the
decay products important at the level of
the selection strategy
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Kinematics (2)
Mean = 0.67 GeV/c
Mean = 0.50 GeV/c
Elena Bruna
Comparing with Pb-Pb central
events (ONLY HIJING generation,
NO propagation and reconstruction
in the detector):
p
PT distributions:
K
nonresonant D+ decay
HIJING central (normalized)
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
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Dalitz Plots: Kinematics (3)
Resonant
Elena Bruna
Non resonant
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Sharp borders due to PYTHIA cut
off on the tails of distributions