Vertex Detector: Engineering Issues

1
Vertex Detector Engineering Issues

• Craig Buttar
• University of Glasgow
• Cambridge GLDC meeting
• Sept 07

2
Design Features

• Outer radius 6 cm
• Barrel length 14 cm
• Ladder widths 1-2 cm
• Disks to cover forward region

(GLD)
(LDC)
A bit larger than this
(SID)
3
Optimizing Vertex Performance

• Close to IP
• Reduce extrapolation error
• Inner radius 1.5cm
• Position resolution (lt5 microns)
• Impact parameter resolution 5µm ? 10µm/(p
  sin3/2 ?)
• Minimise multiple scattering
• Material 0.1X0/layer
• 5 ?m resolution or better is possible with
  current sensor technology
• Need good alignment to exploit this
• Minimal mass is crucial
• Constraints on mechanics
• Constraints on power
• Cooling
• Power delivery
• Alignment

ILC target

• Parametric simulation assuming
• 0.1 RL per layer
• 5 micron resolution
• 1.4 cm inner radius
• Varying each parameter

4
Material budget
ATLAS Tracker
cosq0.95
cosq0.95

• Service handling at ends of barrel are the
  problem
• The boring stuff is important!
• Breakdown for pixels

Sensors (300mm) 1.1
Robump bonds 1.4
Hybrid 1.0
Local supportcooling 5.4
Cables 0.3
Global support 1.5
Total for 3 layers 10.7
5
Mechanical Support

• 0.1 X0/layer ? 100mm of Si
• Need to start with thin Si, typically 20mm
• Thin supports
• Carbon fiber-based supports, similar to D0 layer
  0/CDF Layer00
• Foam-based (SiC, RVC) supports (LCFI)
• Silicon picture frame (MPI)
• System Issues
• Planarity of the sensors
• Bonding to thin silicon
• Thermal bowing
• Connection to external cables

(University of Washington)
(LCFI)
MPI Design
(SID inside support cylinder)
6
SiC Foam Ladder

• 20 um thick silicon
• 1.5 mm thick SiC foam
• 8 relative density
• Silicone adhesive pads
• 1mm diameter 200 microns high on 5mm pitch
• 0.14 X0

um
mm
SiC ladder
um
glue
ladder block
annulus block
mm
LCFI
7
RVC Foam/Silicon Sandwich Ladder

• 20 micron thick silicon
• 1.5 mm thick RVC foam
• 3 relative density
• Silicone adhesive pads
• on 5mm pitch
• Tension 1.5 N
• 0.08 X0

um
mm
um
RVC sandwiched ladder
Tension
silicon spacer
glue
ladder block
annulus block
mm
LCFI
8
Air Cooling
(Cooper, SID)

• Air cooling is crucial to keep mass to a minimum
• Require laminar flow through available apertures
• This sets total mass flow other quantities
  follow
• Implies a limit on power dissipation
• For SiD design
• Use the outer support CF cylinder as manifold
  (15mm Dr)
• Maintain laminar flow (Remax 1800).
• Total disk (30W) barrel (20W) power 50W
  average
• For SiD 131 µW/mm2.
• Max ?T 8 deg

9
Cooling Studies

• Test model of 1/4 Barrel
• Cold nitrogen cooling
• Heaters at ladder ends
• Parallel CFD simulations

Power Extracted (W)

• Flow 5-20 SLM
• 0.5?2 g/s whole detector
• Laminar flow

LCFI
Temperature Difference (K)
10
Alignment is critical

• ILC physics programme depends on identification
  of secondary vertices
• Ability to do this depends on tracking resolution
• Tracking resolution dependent on alignment
  precision
• Individual hit resolution may be O(5) ?m
• Alignment must be better, so that contribution in
  quadrature does not degrade hit resolution

11
Alignment LHCb VELO
Hardware Design
Software
Metrology
Measurement machine Individual modules during
assembly Complete system 10?m alignment
BEFORE / AFTER
Rigidity low CTE overlaps 10?m alignment
Alignment at few ?m level Iterative / non
-iterative methods
For ILC vertex detector Position of detectors on
ladders to 10mm Thin detectors ? Warping
(SLD) Thin ladders ? not rigid Low mass beam pipe
? Vertex detector will move wrt experiment
12
Design

• Design into system features for alignment
• Rigidity, thermal and humidity expansion
• This is difficult at low mass
• Overlaps not just for coverage, e.g.
• VELO left, right half overlap
• SLD CCDs

13
Metrology - importance

• Starting point for alignment parameters
• Constrains degrees of freedom not accessible from
  alignment system
• e.g. large systematic on particle lifetimes is
  radius of barrel e.g. /- 40 um on 4cm 1
• e.g. aspect ratio of vertex detector gives ?
  systematic important for FB asymmetries
• Define/understand elements
• Ladders
• Ideally rigid, 6 dof/ladder (372 for LCFI barrel)
• Ladders are not a rigid object eg detector bow,
  CTE
• Develop models? Difficult to measure during
  construction need to understand effect of thermal
  changes eg CTE, tension due to mechanics and
  services? (CTE studies by LCFI)
• Greater no. of degrees of freedom than ladders x
  6 (ATLAS has 34,992 dof)
• Requires good initial survey and understanding of
  changes
• Difficult to do under in-situ conditions

14
Power delivery

• High currents to drive CCD clock pulses
• Minimise voltage drop on power cables
• Low resistance ? more conductor mass (Cu)
• 0.5V drop at 6cm 0.5X0
• Use serial powering
• Power at higher voltage, locally regulate at
  detector
• Reduces conductor mass
• 0.5V drop at 6cm 0.04Xo
• Issues
• Failure in string
• Coherent noise
• Increase complexity of interconnects
• UK-ATLAS activity for sLHC upgrade

15
UK Experience

• ATLAS barrel and endcap silicon tracker, LHCb
  VELO
• Sensors (strips)
• Readout electronics
• Module construction
• Engineering
• Cooling liquid based
• Alignment
• LCFI
• SLD CCD based vertex detector
• ALEPH, DELPHI, OPAL strip-based vertex detectors
• CDF Layer-00 strip-based vertex detector

16
Summary/conclusions

• Low mass critical to achieve required IP
• Challenging eg ATLAS is 10.7X0 for 3 pixel
  layers
• Dominated by support and cooling
• Target layer thickness 0.1X0 (100mm Si)
• Thin sensors
• New support materials
• Air cooling ? limits power to O(10W)
• Also implications for services ? serial powering
• Need to consider alignment in hardware
• Design overlaps in system (increase material)
• Metrology during assembly
• Warping of thin detectors and ladders
• Report of LHC alignment workshop CERN yellow
  report 2007-004
• Thanks to Mark Thomson, Tim Greenshaw, Joel
  Goldstein, Chris Parkes, Val OShea, Richard Bates

17
Barrel Layout
Beryllium support shell
Foam cryostat
Beam pipe
Ladder (detector element)
Fixed end
Sliding end
Spring
Annulus block
Substrate
Annulus and ladder blocks
Ladder block
Beryllium support shell
Silicon sensor
Readout and drive chips
18
Barrel Layout

• Looking at
• the radius of the layers
• width of elements
• tilt angle

Layer no No of Ladders Radius (mm) Active length (mm) Active width (mm) Tilt angle Overlap (mm)
1 8 15(19) 100 13 0 0
2 8 26(28.5) 250 22 0 0.42
3 12 37 250 22 15 1.3
4 15 48 250 22 15 0.86
5 19 60 250 22 15 1.2
19
Metrology - Equipment

• Smartscope
• Small scale items not full system
• High precision O(2) ?m XY O(10) ?m Z
• Optical head
• Automatic pattern recognition
• Excellent for measuring sensor curvature
• Individual sensors not double sided modules no
  alignment to reverse side

20
Software Alignment
? Alignment principle
From this
Each individual unit has six degrees of
freedom Need to apply global transformation
constraints
21
Iterative / Not Iterative

• All software alignment procedures follow one of
  these two forms

Iterative fit biased tracks then fit alignment
constants, iterate to reduce bias Non-Iterative
fit tracks and alignment constants simultaneously
conclusion both methods can be made to work
well.
22
Global Alignment Method H1, LHCb, ATLAS

• Establish linear expression of residuals
• as a function of mis-alignments.
• Fit the tracks simultaneously with the alignment
  constants

xclus xtrack ex
rclus (xclus - x)
Alignment ? minimise c2res ? ?wclusr2clus
? Get all track parameters and all misalignment
constants simultaneously ? 1 single system to
solve. ? But this system is huge !
(NtracksNlocalNglobal equations)
BUT
23
Matrix Inversion
? The matrix to invert has a very special
structure
Nglobal
Nlocal x Ntraces
? Inversion in section (implemented in the code
MILLEPEDE V.Blobel - NIM. A 566), The problem
becomes only Nglobal x Nglobal
? If Nglobal ? 100 , the problem can be solved in
seconds
24
Other Interesting Techniques

• Kalman Filter Alignment CMS
• Iterative
• Updates alignment constants immediately after
  each track
• SLD
• Residuals as a function of misalignments
• Fit residuals as a function of position
• Determine alignment constant from matrix
  inversion