7 Nov 2002 Niels Tuning - Vertex 2002 1

A vertex trigger for LHCb

The trigger for LHCb …

.. and the use of the Si vertex detector at the first and second trigger levels

Vertex2002 Hawai’i, 7 Nov 2002 Niels Tuning (CERN) (on behalf of LHCb)

7 Nov 2002 Niels Tuning - Vertex 2002 2

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 (ppbbX) = 0.5 mb ~1012 bb / 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!

7 Nov 2002 Niels Tuning - Vertex 2002 3

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

L2+L3: high PT + displaced vertex + B-mass + PID

Use tracking stations and RICH

Bunch crossing rate 40 Mhz

Non empty bc rate 30 MHz

Visible interaction rate ~12 MHz

Input to L0 ~10 MHz

Input to L1 1 MHz

Input to higher level

40 kHz

Writing to disk 0.2 kHz

7 Nov 2002 Niels Tuning - Vertex 2002 4

LHCb detector

L0 veto L1 L0 trigger

TT

T1 T2 T3

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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

320 strips

84

mm

16

mm

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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 peakVeto if peak>threshold(Zvtx) 2.8 mm, (beam) 53 mm

vtxa

vtxb

a

b

ZZ

ZZ

R

R

Z vtx (cm)

Ra (cm)

Rb

(cm

)com

bin

ati

on

s

true all

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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 inelastic+elastic !)

2events singlefor accept L0events for vetoedaccept L0

Same L0 output rate!

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CPU

SCI

Scheduling network

RU

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 msStrategy:

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 B–events 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: 37–98 m, R 40–92 m Sens. area: 0.8 cm < R < 4.2 cm

21 stations (84 sensors) -17.5 cm < Z < 75 cm 170,000 channels

RF foil: Very thin “beampipe” to separate prim. and sec. vacua

R sensor2048 strips

sensor: stereo angle +10o,-20o

R sensor: 4 inner and 2 outer sectors

sensor2048 strips

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L1: input data

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

Cluster resolution:(testbeam)

=14 m

1000 clusters(simulation)

Pitch (m)

Reso

luti

on (m

)

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multiplicity

~60

L1: track reconstruction

Look only for R-clusters: 2d RZ-tracks Fast!

Find “triplets” of clustersCombine triplets~98% efficiency for B-tracks

Z vtx histogram X,Y vtx

VELO is being redesigned to 45o sectors:

faster L1 tracking

lower noise less 2d tracks

2d tracks in a 90o sector:

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L1: primary vertex

Primary vertex reconstructed with 2d tracksXY information from segmentationFlight direction of B is forward RZ projection of impact parameter contains most information

X Z

Vertex resolution:Impact parameter:

2d 3d

Lifetime

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L1: PT information – L0

Match VELO track to Muon from L0: PID Momentum

Efficient selection of BsJ/() BdJ/() Ks

Enhance -tagged sample

VELO

MAGNETMUON

dp/p=4.8%

TT

CAL

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Good momentum resolution, cut on J/ mass:

~60% of events contain both muons

<1% min.bias retention

OR require 1 muon with high PT, high IP

~75 % efficiency ~3% retention

Work ongoing: achieved 90% eff. using

neural net

L1: algorithm (1)Preliminary

J/ mass

Performance with all event info (except TT)

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L1: Trigger Tracker

TT = Tracking station before the magnet

Design still under studySi: 400 - 500 m thickWide 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)

141 cm

11

6 c

m

VELO

TT M

AG

NE

T

RICH-1

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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%

30% ---

p (GeV)

30

GeV

---

d

p/p

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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

Bd+-BsDs

-K+

Signal

Minimum bias

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Tracking+Vertexing

time (ms)

Even

ts

----

17 m

s

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

Tracking+Vertexing: < 20 ms2007 CPUs: x8 fasterOptimize algorithm+code 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+-

L1+L0 info

L1+PT info

40 kHz

L0L1 L1L2

L1 o

utp

ut

rate

(M

Hz)

Bd+- efficiency

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Conclusions

The pileup-VETO detector efficiently rejects multiple primary vertices @ 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+- ( BJ/() Ks)

reachable at 4% minimum bias retention