Performance of the ALICE
silicon detectors
R. Santoro
On behalf of the ITS collaboration in the ALICE experiment at LHC
Outlook
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System overview
Main components
ITS performance with p-p and Pb-Pb data
Upgrade plans
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
2
The ALICE experiment
Dedicated heavy ion experiment at LHC
 Study of the behavior of strongly interacting matter under extreme conditions of high energy density and
temperature
Proton-Proton collisions
 Reference data for heavy-ion program
 Genuine physics (momentum cutoff <100MeV/c, excellent PID, efficient minimum bias trigger)
Barrel Tracking requirements (|η| < 0.9 )
 Robust tracking for heavy ion
environment
 Mainly 3D hits and up to 150 points
along the tracks
 Wide transverse momentum range (100
MeV/c – 100 GeV/c)
 Low material budget (13% X0 up to
the end of TPC)
 Large lever arm to guarantee good
tracking resolution at high pt
PID requirements over the large
momentum range
 Combined PID based on several
techniques: dE/dx, TOF, transition and
Cherenkov radiation
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
3
The ALICE Inner Tracking System
The ITS role in ALICE
 Secondary vertex reconstruction (c, b decays)
 Good track impact parameter resolution (< 60 µm
(rφ) for pt > 1 GeV/c in Pb-Pb)
 Improve primary vertex reconstruction and
momentum resolution
 Tracking and PID of low pt particles
 Prompt L0 trigger capability (<800 ns)
 Measurements of charged particle pseudorapidity
distribution
 First Physics measurement both in p-p and Pb-Pb
ITS: 3 different silicon
detector technologies
Strip
Drift
Pixel
Detector requirements
 Two dimension detectors to handle high particle
density
 Good spatial precision
 High efficiency
 High granularity (≈ few % occupancy)
 Minimize distance of innermost layer from beam
axis (mean radius ≈ 3.9 cm)
 Limited material budget
 Analogue information in 4 layers (Drift and Strip)
for particle identification in 1/β2 region via dE/dx
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
4
ITS parameters
Material budget measured
with  conversions
Accurate description of
the material in MC
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
5
Pixel detector (SPD)
Half-barrel:
outer surface
2 layers of pixels grouped in 2
half barrels mounted face to face
around the beam pipe
beam pipe
Half-stave
Total surface: ~0.24m2
 Power consumption ~1.4kW
 Evaporative cooling C4F10
 Operating at room temperature
 Fast two-dimensional readout
(256µs)
 High efficiency (> 99%)
L0 trigger capability
 Material budget per layer ~1% X0
Vertex,
(Austria), 19- 24 June 2011
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≈ 1200 Rust
wire-bonds
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R. Santoro
Drift detector (SDD)
Cooling (H2O) tubes
SDD
Barrel
Cables to power
supplies and DAQ
Carbon fiber support
HV supply
Front-end electronics (4 pairs of ASICs)
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Amplifier, shaper, 10-bit ADC, 40 MHz sampling
R. Santoroanalog memory
Vertex, Rust (Austria), 19- 24 June 2011
Four-buffer
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LV supply
Commands
Trigger
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Data
Strip detector (SSD)
•carbon fibre support
•module pitch: 39.1 mm
•Al on polyimide laddercables
Hybrid:identical for P- and N-side
Al on polyimide connections
6 front-end chips HAL25
water cooled
R. Santoro
Sensor:
double sided strip:
768 strips 95 um pitch
P-side orientation 7.5 mrad
Vertex, Rust (Austria), 19- 24 June 2011
N-side orientation 27.5 mrad
End ladder electronics
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ITS installation: summer 2007 (phase 1)
SPD Internal mean radius  3.9 cm
Beam pipe radius  3 cm
1st half-barrel
Beryllium Beam pipe
R. Santoro
1st half-barrel
in place
ITS upgrade plenary meeting
2nd half-barrel
in place 9
ITS installation: summer 2007 (phase 2)
SPD fully connected
on side C
SDD + SSD
SDD+SSD moved over the
SPD to form the ITS
ITS fully connected
on side C
TPC
TPC moved over the ITS
R. Santoro
ITS upgrade plenary meeting
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ALICE data taking: 2008 – 2011
Cosmic (2008)
Offline event display for a
typical ITS cosmic event
100 K events in the ITS using the
pixel L0 dedicated trigger
p – p collisions (2010 – 2011)
 900 GeV (300 K + 8 M events MB)
 2.36 TeV (40 K events)
 2.76 TeV (70 M events MB)
 7 TeV ( 800 M events MB in 2010)
 7 TeV ( 550 M events MB in 2011)
R. Santoro
Pb – Pb collisions (2010)
2.76 TeV/nucleon (≈ 30 M events MB)
Vertex, Rust (Austria), 19- 24 June 2011
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ITS performances with p-p and Pb-Pb data
Alignment
Vertex capability
Transverse impact parameter
PID performances
Alignment (I)
To exploit the excellent spatial resolution and material budget a
good alignment is crucial to achieve the required track impact
resolution
Data sample
 100k cosmic tracks collected in 2008 with dedicated pixel L0 trigger
 p-p data with / without magnetic field
 Significant improvement in statistics and detector coverage
Two independent track-based alignment methods
 global: Millepede (default method)
 local: iterative method based on residuals minimization
General strategy
 Validation of survey measurements
 Start with layers easier to calibrate: SPD and SSD
 Include SDD as last
 Longer calibration needed (interplay between alignment, drift
velocity and time-zero calibration)
 Align the whole ITS wrt TPC
For details on the procedure: “Alignment of the
ALICE Inner Tracking System with cosmic-ray
tracks”, JINST 5, P03003
R. Santoro
ITS coverage with the cosmic
tracks used for the alignment
2198 modules to be
aligned: more than 1300
parameters in total
Vertex, Rust (Austria), 19- 24 June 2011
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Alignment (II)
The achieved alignment is very close to the expected residual misalignment obtained from
Monte Carlo studies
Examples of performance plots used to qualify the alignment in each sub-system
 SPD: σ of residuals Gaussian fit measured in the overlap regions after the alignment
 SDD: σ of track-to-point residuals in the bending plane (before and after the Vdrift correction)
Residual
misalignment <10µm
R. Santoro
Residual misalignment
≈35µm in the drift direction
Vertex, Rust (Austria), 19- 24 June 2011
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SPD Tracklets
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The “SPD Vertex” is calculated with all possible pairs of 2
aligned hits in the SPD (one hits per layer) with cuts in φ
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A tracklet is defined by a pair of hits (one per SPD layer)
aligned with the reconstructed vertex
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Hits selection is based on fiducial windows in φ (bending
plane) and η (non-bending plane)
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Optimized selection criteria for p-p and Pb-Pb
The imposed cut efficiently selects charged particles with
transverse momentum (pt) above 50 MeV/c.
Fast measurement of charged particle
multiplicity density at mid-rapidity
 “Charged-particle
multiplicity measurement in proton–proton
collisions at √s=0.9 and 2.36 TeV with ALICE at LHC”, Eur. Phys. J.
C (2010) 68: 89–108
 “Charged-particle
multiplicity measurement in proton-proton
collisions at √s = 7 TeV with ALICE at LHC”, Eur. Phys. J C68
(2010) 345-354
 “Charged-particle
multiplicity density at mid-rapidity in central PbPb collisions at sqrt(sNN) = 2.76 TeV”,
Phys.Rev.Lett.105:252301,2010
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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Tracking and primary vertex capability
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Primary vertex reconstructed with tracklets
Tracks reconstruction starts from outside (TPC) towards ITS using the vertex as seed
TPC reconstructed tracks are matched with SSD outer layer
Once the reconstruction reaches the first SPD layer it is back-propagated
Re-fit from outside and the vertex is recalculated using the tracks
TPC - ITS track
matching
pp 7 TeV
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
16
Transverse impact parameter
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A key plot to quote the tracker performance in terms of
track and vertex reconstruction is the transverse impact
parameter in the bending plane: d0(rφ)
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Distance between the track projection and the vertex position
reconstruction in the bending plane
The material budget mainly affect the performance at low
pt (multiple scattering)
The point resolution of each layers drives the asymptotic
performance
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
17
Particle identification
4 out of 6 silicon layers with analogue information (SDD and SSD)
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Energy loss (dE/dx)
Truncated mean to account for long tails in the Landau distribution
Tracks path length correction
Results for particle identification in p-p and Pb-Pb data
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ITS standalone tracks
Hadron separation below 100 MeV/c
Good pions / kaons separation up to 0.5 GeV/c
Good pions and protons separation up to 1 GeV/c
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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D0 and D+ reconstruction in Pb-Pb
Pb – Pb collisions (2010)
2.76 TeV/nucleon (≈ 30 M events MB)
How to find a charm decay in such an environment?
Thanks to the ITS impact parameter resolution this is
possible
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
19
ITS upgrade
The goal for the ITS upgrade is to improve the impact parameter resolution by
factor 2-3 to identify short displaced secondary vertices
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Get closer to the interaction point
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Material budget less than 0.5% X0 especially in the first layers (≈1.1% X0 at present)
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Beam pipe with reduced radius 20 mm (30 mm at present)
First pixel layer at less than 25 mm (39 mm at present)
Reduce mass of silicon, power and signals bus, cooling, mechanics
Monolithic Pixels
Pixel size of the order of 50 x 50 µm2 (425 x 50 µm2 at present)
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Main improvement in z
Main impact on medium / high pt particles
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
20
Summary
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ALICE ITS performance well in agreement with the requirements
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The achieved alignment in agreement with the expected residual
misalignment
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Track reconstruction & primary vertex reconstruction is in good agreement
with Monte Carlo
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Good description of the ITS in terms of detector space resolution, efficiency and
material budget
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Standalone PID capability by the dE/dx measurement down to 0.1 GeV/c
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ITS upgrade under study to improve the impact parameter resolution
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R&D activity on-going
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Conceptual design report being prepared
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
21
Thanks for your attention
Spares
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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Data samples
Beam
Energy
# of Events
pp
900 GeV
300 k MB
2009, analysis finished
pp
900 GeV
~ 8 M MB
2010, partially analyzed
pp
2.36 TeV
~ 40 k MB
2009, only ITS, dNch/dh
pp
7 TeV
2010
PbPb
2.76 TeV/N
~ 800 M MB
~ 50 M muons
~ 20 M high Nch
~ 30 M MB
pp
2.76 TeV
~ 70 M MB
~ 20 nb-1 (rare triggers)
2011, analysis started
R. Santoro
2010
Vertex, Rust (Austria), 19- 24 June 2011
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SDD calibration strategy (1)
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Online calibration, using dedicated runs,
performed at every LHC fill
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Baseline, noise, tag of noisy channels for each
of the 133120 anodes
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<Noise> ≈ 2.5 ADC counts
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Signal for a MIP on anodes ≈ 100 ADC
Channel gain, tag of dead electronic channels
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Display of 1 injector event
on 1 drift side of 1 module
Fraction of bad channels in active modules ≈1.7%
Drift speed from MOS injectors implanted on
the sensor surface
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Crucial to have a 0.1% precision on drift speed to
reach the nominal resolution of 35 mm along the
drift direction
R. Santoro
Drift speed on 1 drift side
from fit to 3 injector points
vdrift = mE T-2.4
Lower e- mobility / higher
temperature on the edges
Vertex, Rust (Austria), 19- 24 June 2011
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SDD calibration strategy (2)
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Offline calibration
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From Track-to-point residuals:
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Geometrical alignment
Calibration of :
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Time Zero
Drift speed (for modules with
malfunctioning injectors)
Drift field non uniformity (due to
non-linearity in voltage divider)
dE/dx calibration
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Correction of drift time
dependence of detected charge
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Due to diffusion + zero
suppression thresholds
ADC absolute calibration
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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The SSD Calibration
Calibration procedure
 Pedestal run at each LHC fill
 Unsuppressed data processed by Detector Algorithm
 Computed parameters uploaded in the read-out electronics and
stored in the Offline Conditions Database
Bad Channel Map
Computed parameters for each channel
 pedestal (baseline)
 total noise
 common mode corrected noise
→ tag as bad channel and mask it if:
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noise > 20 ADC ch. (noisy)
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noise < 1 ADC ch. (dead)
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pedestal > 512 ADC ch. (overflow)
 90% good channels
p side
n side
Cluster charge distribution measured from
collision data with all the SSD modules
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the gain can be calibrated at the module
level
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
27
Pixel L0 trigger capability
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Pixel chip prompt Fast-OR
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Overall latency constrain 800 ns (CTP)
Hardware space occupancy (1 crate)
Key timing processes are data deserialization and Fast-OR extraction
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Algorithm processing time < 25 ns
10 Algorithms provided in parallel: useful for detectors commissioning, p-p and Pb-Pb physic
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Active if at least one pixel hit in the chip matrix
10 signals in each half-stave (1200 signals in total)
Transmitted every 100 ns
Cosmic, minimum bias and multiplicity algorithms
FPGA remote programmable to guarantee maximum flexibility
R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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Fast-OR Algorithms
1
Minimum Bias
(I+O)thIO,mb and IthI,mb and OthO,mb
2
High Multiplicity 1
IthI,hm1 and OthO,hm1
3
High Multiplicity 2
IthI,hm2 and OthO,hm2
4
High Multiplicity 3
IthI,hm3 and OthO,hm3
5
High Multiplicity 4
IthI,hm4 and OthO,hm4
6
Past Future Prot
(I+O)thIO,pfp and IthI,pfp and OthO,pfp
7
Background(0)
I  O+ offsetO
8
Background(1)
O  I+ offsetI
9
Background(2)
(I+O)  th(I+O),bnd
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Cosmic
Selectable coincidence, see following list
Cosmic algorithms:
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TOP_outer and BOTTOM_outer
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OR_OUTER and OR_INNER
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DLAYER ( ≥ 2 FOs in the INNER and ≥ 2 FOs in the OUTER)
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TOP_outer and BOTTOM_outer and TOP_inner and BOTTOM_inner
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TOP_outer and BOTTOM_outer and OR_INNER
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R.GLOBAL_OR
Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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R. Santoro
Vertex, Rust (Austria), 19- 24 June 2011
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