A vertex trigger for LHCb

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A vertex trigger for LHCb

• Vertex2002
• Hawaii, 7 Nov 2002
• Niels Tuning (CERN)
• (on behalf of LHCb)

• The trigger for LHCb
• .. and the use of the Si vertex detector at the
  first and second trigger levels

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LHCbA Large Hadron Collider Beauty Experiment
for Precision Measurements of CP-Violation and
Rare Decays

• Colliding beams
• 25 ns
• 7 TeV x 7 TeV pp
• L 2.1032 cm-2 s-1
• ?(visible) 68 mb
• ?(pp?b?bX) 0.5 mb
• ? 1012 b?b / year
• BR(interesting channels) 10-2 10-9
• Finding B-mesons
• High PT decay products
• Large lifetime ? sec.vertex
• Invariant mass

A low multiplicity B???- event
LHCb trigger looking for a needle in a
haystack every 25 ns!
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LHCb Trigger Overview

• L0 high PT
• Pile-up Veto, using VETO detector
• High ET calorimeter objects
• High PT muons
• L1 high PT impact parameter
• High impact parameter tracks, using VELO detector
• High PT tracks, using TT detector and L0 info
• L2L3 high PT displaced vertex B-mass PID
• Use tracking stations and RICH

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LHCb detector
TT
T1 T2 T3
L0 veto
L1
L0 trigger
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L0 Pile-up VETO(L0 first trigger level)

• Purpose remove multiple interactions
• Nominal luminosity L 2.1032 cm-2 s-1
• Single Double Triple ? 16 4 1 ? 75
  20 5
• Why?
• More difficult to find high IP tracks at L1
• Reduce bandwidth for L0
• Detector
• 2 Si disks (4 sensors)
• Same sensors as VErtex LOcator (see
  talk J.Palacios)
• Only R information
• Use Beetle chip
• OR of 4 strips comparator
  output of 4 channels
• ? 1280 channels for 2 disks

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L0 Pile-up VETO algorithm

• Calculate vertex for all combinations of 2 points
  a and b.
• Find highest peak (PV)
• Remove the hits and find 2nd peak
• Veto if peakgtthreshold
• ?(Zvtx) ? 2.8 mm, ?(beam) ? 53 mm

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L0 Pile-up VETO performance

• B???- L0 efficiency increase
• from 50 to 60
• ? the L0 PT,HADR threshold can be lowered from 4
  GeV to 3.6 GeV
• Reduce bandwidth and enhance purity
• Pileup VETO vetoes 15 of all events
• Vetoed events are more likely to trigger
• Only small inefficiency for single interactions
  5
• Reject 30 of multiple interactions (NB
  
  multiple interactions include inelasticelastic !)

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L1 trigger vertex trigger(L1 second trigger
level)

• Implementation
• Clustering in FPGA on front-end
• Send data to RU (3-4 GB/s)
• CPU-farm
• 300 400 CPUs
• 2D torus
• Use scheduler
• Prototype with 32 CPUs
• running at 1.24 MHz
• Buffer depth 1820 events ? Latency 1.65 ms
• Strategy
• Find 2d-tracks with R-sensors and reconstruct
  vertex
• Reconstruct high-impact parameter tracks in 3d
• Extrapolate to TT through small magnetic field ?
  PT
• Match track to L0 Muon objects ? PT and PID
• Select Bevents using impact parameter and PT
  information

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L1 VErtex LOcator(see talk by Juan Palacios)

• Si 220 ?m thick, n-on-n,
• Pitch ? 3798 ?m, R 4092 ?m
• Sens. area 0.8 cm lt R lt 4.2 cm
• 21 stations (84 sensors)
• -17.5 cm lt Z lt 75 cm
• 170,000 channels

RF foil Very thin beampipe to separate prim.
and sec. vacua
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L1 input data
Cluster resolution (testbeam) ?14 ?m

• Velo clusters
• Clusters are found in FPGAs per groups of 32
  strips.
• Digital (offline is analog)
• 1000 clusters
• 0.1 noise clusters (?200)
• TT clusters
• 300 clusters
• L0 objects
• ? 3 muons
• Some calorimeter data

Resolution (?m)
Pitch (?m)
1000 clusters (simulation)
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L1 track reconstruction
60

• Look only for R-clusters? 2d RZ-tracks
• Fast!
• Find triplets of clusters
• Combine triplets
• 98 efficiency for B-tracks

multiplicity
2d tracks in a 90o sector

• VELO is being redesigned to 45o sectors
• faster L1 tracking
• lower noise
• less 2d tracks

Z vtx histogram
X,Y vtx
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L1 primary vertex

• Primary vertex reconstructed with 2d tracks
• XY information from ? segmentation
• Flight direction of B is forward ? RZ projection
  of impact parameter contains most information

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L1 PT information L0
CAL

• Match VELO track to Muon from L0
• ? PID
• ? Momentum
• Efficient selection of
• Bs?J/?(??) ?
• Bd?J/?(??) Ks

VELO
TT
MUON
MAGNET
dp/p4.8

• Enhance ?-tagged sample

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L1 algorithm (1)Preliminary
J/? mass

• Good momentum resolution, cut on J/? mass
• 60 of events contain both muons
• lt1 min.bias retention
• OR require 1 muon with high PT, high IP
• 75 efficiency
• 3 retention
• Work ongoing
• achieved 90 eff. using neural net

Performance with all event info (except TT)
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L1 Trigger Tracker

• TT Tracking station before the magnet
• Design still under study
• Si 400 - 500 ?m thick
• Wide pitch 200 ?m
• Sensor dimensions 7.8 x 11.0 cm2
• 4 layers (x,u 30 cm gap v,x)
• Stereo angle 00, -50, 50, 00
• To be optimized
• 836 sensors (7 m2)

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L1 PT information TT

• High impact parameter 2d tracks are reconstructed
  in 3d and extrapolated to TT1
• Magnetic field between VELO and TT
• ? B dl ? 0.1 Tm
• Ensures momentum information
• dp/p 30

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L1 algorithm (2)Preliminary

• Get two highest PT tracks, using TT
• Consider impact parameter and PT of these tracks
• Look in plane ?IP/?(IP) vs ?PT

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L1 performance - timing

• Remember latency 1.7 ms
• Possibly x32 more.
• A more flexible system is under study were CPUs
  from DAQ can be used for the TRIGGER and vice
  versa
• TrackingVertexing lt 20 ms
• 2007 CPUs x8 faster
• Optimize algorithmcode
• ? in the right ballpark!
• 2d tracking 70
• Vertex 15
• 3d tracking (a few) 15

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L1 performance

• Efficiency vs retention (Example B???- )

• Expected overall trigger performance (cumulative)

Bd???-
L1L0 info
L1 output rate (MHz)
40 kHz
L1PT info
Bd???- efficiency
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Conclusions

• The pileup-VETO detector efficiently rejects
  multiple primary vertices _at_ 40 MHz at L0
• The VELO detector reconstructs primary vertices
  at L1 with excellent resolution
• ?(Zvtx) ? 60 ?m
• ? high impact parameter tracks can be identified
• The TT detector - or L0 information - enables
  measuring the momentum of tracks
• ? Efficient L1 selection algorithms under study
• Efficiency of 70 (90) for B???- ( B?J/?(??)
  Ks) reachable at 4 minimum bias retention