Eduardo Rodrigues NIKHEF Seminar at CPPM, Marseille, 4 th May 2007
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Transcript of Eduardo Rodrigues NIKHEF Seminar at CPPM, Marseille, 4 th May 2007
Eduardo RodriguesEduardo RodriguesNIKHEFNIKHEF
Seminar at CPPM, Marseille, 4Seminar at CPPM, Marseille, 4thth May 2007 May 2007
LHCb: a stroll from Trigger to LHCb: a stroll from Trigger to PhysicsPhysics
LHCb: a stroll from Trigger to Physics 2/54
Eduardo Rodrigues CPPM, 4th May 2007
ContentsContentsI.I. LHCb: the must knowLHCb: the must know
II.II. Detector and simulationDetector and simulation
III.III. Trigger systemTrigger system
IV.IV. Reconstruction and PIDReconstruction and PID
V.V. Analysis: tagging and event selectionAnalysis: tagging and event selection
VI.VI. Physics sensitivity studiesPhysics sensitivity studies
Disclaimer: no complete review of all aspects; emphasis put on personal work
LHCb: a stroll from Trigger to Physics 3/54
Eduardo Rodrigues CPPM, 4th May 2007
9 km diameter
GenevaGenevaJuraJura
CERN
LHCb: a stroll from Trigger to Physics 4/54
Eduardo Rodrigues CPPM, 4th May 2007
I. LHCb: the must knowI. LHCb: the must know
LHCbLHCb
Goal: B-physics studies CP violation rare B-decays
Acceptance: 1.8 < < 4.9
Luminosity: 21032 cm-2
s-1
Nr of B’s / year: 1012
How forward is LHCb?How forward is LHCb? B hadrons mainly produced in forward B hadrons mainly produced in forward region(s)region(s)
both B’s tend to be correlatedboth B’s tend to be correlated
Unique forward spectrometer
at high energy!
Excellent tracking
Excellent PID
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B-hadronsB-hadrons are heavyheavy and long-lived !long-lived !
LHC(b) environmentLHC(b) environmentLHC environmentLHC environment
pp collisions at Epp collisions at ECMCM = 14 TeV = 14 TeV
ttbunchbunch = 25 ns = 25 ns bunch crossing rate = 40 MHz bunch crossing rate = 40 MHz
<L> = 2x10<L> = 2x103232 cm cm-2-2 s s-1 -1 @ LHCb interaction region@ LHCb interaction region
10-50 times lower than for ATLAS/CMS
~ 7x1012 pairs~ 700 kHz~ 3.5 mb (c-cbar)
~ 100 kHz
~ 12 MHz
Event rate
~ 60 mb visible
~ 0.5 mb
~ 100 mb
Value
~ 1012 pairsb-bbar)
total
Yield / yearPhysical quantity
Expected B-signal ratesExpected B-signal rates branching ratios ~ 10branching ratios ~ 10-9-9 – 10 – 10-4-4
10 – 1010 – 106 6 events / year ?events / year ?
Cross sectionsCross sections
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Eduardo Rodrigues CPPM, 4th May 2007
II. LHCb detectorII. LHCb detector
(side view)
pp collision
Acceptance
10 mrad
250/300 mrad
« Tracking » detectors« Tracking » detectors Muon SystemMuon System
CalorimetersCalorimetersRing Imaging CherenkovRing Imaging Cherenkov
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LHCb LHCb caverncavern
LHCb: a stroll from Trigger to Physics 8/54
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LHCb Monte Carlo simulation software:
Pythia, EvtGen, GEANT4 and Gaudi-based reconstruction– Detailed detector and material description (GEANT)– Pattern recognition, trigger simulation and offline event selection– Implements detector inefficiencies, noise hits, effects of events from the previous
bunch crossings
SimulationSimulation
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III. The LHCb III. The LHCb TriggerTrigger
Trigger overview and strategyTrigger overview and strategy
Level-0: first level triggerLevel-0: first level trigger
HLT: High Level TriggerHLT: High Level Trigger
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HLT
Level-0 custom hardware high ET particles partial detector information
CPU farm -> software trigger high ET / IP particles full detector information
Trigger overviewTrigger overview
Storage
pp collisions
12 MHz
1 MHz
~2 kHz
event size ~35 kb
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Two-level TriggerTwo-level Trigger
L0L0 high ET / PT particles
hardware trigger, sub-detector specific implementationhardware trigger, sub-detector specific implementation
pipelined operation, fixed latency of 4 pipelined operation, fixed latency of 4 ss
(minimum bias) rate reduction ~12 MHz -> 1 MHz(minimum bias) rate reduction ~12 MHz -> 1 MHz
HLT:HLT: high ET/PT & high Impact Param. particles & displaced vertices & B-mass & …
algorithms run on large PC farm with ~1800 nodesalgorithms run on large PC farm with ~1800 nodes
several trigger streams to exploit and refine L0 triggering informationseveral trigger streams to exploit and refine L0 triggering information
software reconstruction on part/all of the datasoftware reconstruction on part/all of the data
tracking / vertexing with accuracy close to offline
selection and classification of interesting physics eventsselection and classification of interesting physics events
inclusive / exclusive streams
rate reduction 1 MHz -> 2 kHzrate reduction 1 MHz -> 2 kHz
estimated event size ~ 30kbestimated event size ~ 30kb
Trigger StrategyTrigger StrategyBe alert !Be alert !
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select high Eselect high ETT / P / PTT particles particles
hadrons / electrons / photons / 0’s / muons
reject complex / busy eventsreject complex / busy events
more difficult to reconstruct in HLT
take longer to reconstruct in HLT
reject empty eventsreject empty events
uninteresting for future analysis
L0 thresholds on ET / PT of candidates
global event variables
Level-0 Trigger strategyLevel-0 Trigger strategy
Pile-up systemPile-up system CalorimeterCalorimeter Muon systemMuon system
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L0 Pile-up system: 2 silicon planes upstream of nominal IP,
part of the Vertex Locator (VELO)
Identifies multi-PV events:- 2-interactions crossings identified with
efficiency ~60% and purity ~95%
L0 Calorimeter : Identify high-ET hadrons / e’s / ’s / 0’s
Electromagnetic and hadronic calorimeters- large energy deposits ET in 2x2 cells
Scintillator Pad Detector (SPD) and Preshower (PS)- used for charged/electromagnetic nature of clusters, respectively
L0 Muon System: M1 – M5 muon stations (4 quadrants each)
σp/p ~ 20% for b-decays
Level-0 sub-systemsLevel-0 sub-systems
Scintillator Pad Detector (SPD)
Pre-Shower Detector (PS)
ECAL HCAL
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Pile-up system
total multiplicity # tracks in second vertex
Muon system
2 candidates per each of 4 quadrants
Calorimeter
total ET in HCAL SPD multiplicity highest- ET candidates:
h, e, , 2 0‘s
L0 Decision unitL0 Decision unit cuts on global event variables cuts on global event variables thresholds on the Ethresholds on the ETT candidates candidates
L0DU reportL0DU report
Level-0 Decision UnitLevel-0 Decision Unit
1 MHz
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1302.6Photon
1104.5o local
1504.0o global
280
1002.8Electron
7007003.6Hadron
1501.3Di-muon160
1101.1Muon
Approx. rate (kHz)Threshold (GeV)Trigger
~ 13
~ 8.3
3Tracks in 2nd vertex
112 hitsPile-up multiplicity
280 hitsSPD multiplicity~ 7
5.0 GeV ET
Rate (MHz)CutGlobal event cuts
… and then cuts on the EETT / P / PTT candidates candidates
Global event variablesGlobal event variables applied first …
Di-muon trigger is specialDi-muon trigger is special
- not subject to the global event selection- PT
= PT1 + PT
2 with PT2 = 0 possible
- “tags” clean B-signatures
Decision Unit Decision Unit VariablesVariables
Redundancy:Sub-triggers overlap
Level-0 bandwidth divisionLevel-0 bandwidth division
Overall optimization given benchmark channelsOverall optimization given benchmark channels
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Level-0 performance studiesLevel-0 performance studies
45
105
50
20
5
90 90
30
60
10
70
0102030405060708090
HadronicChannels
MuonicChannels
ElectromagneticChannels
HCALECALMuonTotal
Dedicated sub-triggers most relevant for each « channel type »Dedicated sub-triggers most relevant for each « channel type »
Bs → Ds B →
B → J/(Ks
B → K* B → K* B → J/(eeKs
Typical Level-0 performanceTypical Level-0 performance
N.B.: efficiencies with respect to events selected offlineN.B.: efficiencies with respect to events selected offline
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StrategyStrategy
Independent alleysIndependent alleys::Follow the L0 triggered candidate
Muon, Muon + Hadron,
Hadron, ECal streams
~2 kHz
Summary Information:decision, type of trigger fired, info on what triggered
Partial Reconstruction: A few tracks selected per alley (cuts e.g. on PT, Impact Parameter, mass)
full reconstruction done at the end of the alleys
High Level TriggerHigh Level Trigger
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Trigger FarmTrigger Farm Event Filter Farm with ~1800 nodes
(estimated from 2005 Real-Time Trigger Challenge)
Sub-divided in 50 sub-farms
Readout from Level-0 at 1 MHz 50 Gb/s throughput
Scalable design possible upgrade
FE
Readout network
CPU
FE FE
L0 trigger
Timing and Fast Control
CPUCPUCPU CPUpermanent
storage
HLT algos CPU time tested on a real farn
will fit in the size of the farm foreseen
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Muon Alley - StrategyMuon Alley - Strategy
L0- Entry
MuonPre-trigger
MuonTrigger
~200 kHz
~20 kHz
~1.8 kHz
Muon PreTrigger Standalone reconstruction: σp/p ~ 20%
VELO tracks reconstruction Primary vertex reconstruction Match VELO tracks and muons: σp/p ~ 5%
Muon Trigger Tracking of VELO track candidates in the
downstream T stations: σp/p ~ 1%
Refine identification:
match long (VELO-T) tracks and muons
LHCb: a stroll from Trigger to Physics 20/54
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Muon Alley – PerformanceMuon Alley – Performance
Muon PreTrigger bμ ~11% Signal efficiency: ~88%
Muon Trigger Single muon
• PT> 3GeV and IPS> 3
• B content 60% Dimuon
• mass >0.5GeV and IP>100m
• J/mass>2.5GeV (no IP cut!) Signal efficiency: ~87%
J/Ψ
~20 kHz
~1.8 kHz
dimuon mass (MeV)dimuon mass (MeV)
< 1s of LHCb< 1s of LHCb
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Exclusive SelectionsExclusive Selections
Bs→DsBs→ DsK
4 tracks
Exclusive selections– Use common available reconstructed and
selected particles (Ds, D0, K*, Φ,..)
– Wide B-mass windows (typically ~ 500 MeV)
– Efficiency: e.g. ~90% for Bππ~200 Hz
Bs →
Bs →
Ds→KK
→KK
, K
Bs → Ds
Off-line B → On-line B →
LHCb: a stroll from Trigger to Physics 22/54
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IV. Reconstruction and IV. Reconstruction and PIDPID
Tracking: pattern recognition and fittingTracking: pattern recognition and fitting
VertexingVertexing
RICH, Calo. and Muon reconstructionRICH, Calo. and Muon reconstruction
Particle Identification (PID)Particle Identification (PID)
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Tracking strategyTracking strategy
A typical event:A typical event: 26 long 26 long tracks tracks best quality for physics: good P & IP resolution best quality for physics: good P & IP resolution 11 upstream tracks 11 upstream tracks lower p, worse p resol., but useful in the RICH1 pattern recognition lower p, worse p resol., but useful in the RICH1 pattern recognition 4 downtream tracks 4 downtream tracks improves K improves Kss finding efficiency (good p resolution) finding efficiency (good p resolution) 5 seed/T tracks 5 seed/T tracks used in the RICH2 pattern recognition used in the RICH2 pattern recognition 26 VELO tracks 26 VELO tracks used in primary vertex reconstruction: good IP resolution used in primary vertex reconstruction: good IP resolution
|B| (T)
Z (cm)
B-field measured to ~ 0.03% precision!B-field measured to ~ 0.03% precision!
A set of PR algorithmsA set of PR algorithms
Multi-pass strategyMulti-pass strategy
LHCb: a stroll from Trigger to Physics 24/54
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Pattern recognition - Pattern recognition - strategystrategyVELO tracking
(VELO seeds)
Forward tracking(long tracks)
Matching(long tracks)
Seeding(T seeds)
VELO-TT(upstream tracks)
Clonekilling
Set of “best” tracks
Ks tracking(downstream tracks)
LHCb: a stroll from Trigger to Physics 25/54
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Pattern recognition - Pattern recognition - performanceperformance
Eff
icie
ncy
Eff
icie
ncy
p (GeV)
Performance on B-signal samples for “long” tracks: Efficiency ~ 95 % for p > 10 GeV Ghost rate ~16.7 % Dip due to beam-pipe material
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Tracks- pattern recognition attributes detector measurements to a track- modelled with straight-line segments, the (track) states
Track fitting- determine the best track parameters and corresponding covariance matrix given the measurements on the track- take into account multiple scattering and energy losses in the detector material
“banana-shaped” Outer Tracker modules
Track fittingTrack fitting
Description of a realistic detector with mis-alignments- introduction of trajectories to model “measurements”
(concept adapted from BaBar)- trajectory = 3D curve in space (of arbitrary shape)
- detector shapes locally described with trajectories- a track state (straight-line segment) can also be
modeled as a trajectory
- any trajectory can provide a parabolic approximation of its shape at any point along itself closest approach track state – measurement becomes a general point-of-closest-approach problem!
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LHCb uses the Kalman filter technique:
Mathematically equivalent to least 2 method Adds measurements recursively starting from a initial track estimate Reconstructs tracks including multiple scattering and energy losses We use a “bi-directional” fit …
Track fitting « à la Kalman »Track fitting « à la Kalman »
direction of the filter track predictionfiltered track
direction of the reverse filter
track prediction filtered track
Bi-directional fitBi-directional fit
Filter in both directions … smoothed result = weighted mean of both filters
LHCb: a stroll from Trigger to Physics 28/54
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Fitting from a seed (track) stateFitting from a seed (track) state
• Measurements(hit & error)
• Seed State(position, direction &
momentum)
• Prediction(adaptive 5th order
Runge-Kutta method solves motion in the inhomogeneous B)
• Kalman Filtered(update prediction with
Measurement info)
LHCb: a stroll from Trigger to Physics 29/54
Eduardo Rodrigues CPPM, 4th May 2007
Fitter: prediction and Kalman filterFitter: prediction and Kalman filter
Velo TT
IT&OT
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Fitter: Kalman smootherFitter: Kalman smoother
Velo TT
IT&OT
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Bi-directional fittingBi-directional fitting
Velo TT
IT&OT
filtered state
weighted mean
filtered state
LHCb: a stroll from Trigger to Physics 32/54
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Track fitting performanceTrack fitting performance
p/p = 0.5%
Momentum resolution for “long” tracks p/p = 0.35 – 0.55 %
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Vertexing performanceVertexing performance
bt
Bs K
K
,K
Ds
Primary vertex
p p
Bs vertex resolution
Typical resolutions
z,core = 168 m
Primary vertex resolutionsx = 8 m z = 47 m
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RICH reconstructionRICH reconstruction
Algorithm: Input: all types of tracks available Search for hits assuming different hypotheses Global ring fit Cherenkov angle resolutions in the range 0.6 – 1.8 mrad
RICH1 RICH2
nc
1)cos(
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RICH performaceRICH performace
K
Particle Momentum (GeV/c)
K K or p
K or p
0
20
40
60
80
100
e, or
K e, or
Particle Momentum (GeV/c)
0
20
40
60
80
100
identification K identification
Particle identification needed over momentum range 1-100 GeV/c
Ex.: need to distinguish Bd from other similar topology 2-body decays
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Calorimeter reconstruction (1/2)Calorimeter reconstruction (1/2)
electrons: Identification with ~95% based on
- 2 of match calo. cluster energy – position of extrapolated track- Energy deposited in the preshower detector- Energy deposited in the hadronic calorimeter- Bremsstrahlung correction
ECALMagnet
EPS(MeV)
True Electronsbackgrounds
example
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Calorimeter reconstruction (2/2)Calorimeter reconstruction (2/2)
Neutral pions: Resolved 0 :
- reconstructed from isolated calo. photon clusters- mass resolution ~10 MeV, ~30%
Merged 0 :- Several clustes merged into single (high energy) cluster- mass resolution ~15 MeV , ~20%
all π0s
Merged π0
π0 from B
π0 mass (Mev/c²)
Resolved π0
all π0sπ0 from B
Bd→ π+π-π0 events
π0 mass (Mev/c²)
Merged clusterResolved cluster
LHCb: a stroll from Trigger to Physics 38/54
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Muon reconstructionMuon reconstruction
~ 94 % and ~ 1.0 % for tracks in Muon detector acceptance
~ 10 MeV/c²
Typical performancesfor b J/() X
eff ~ 94 %
misid ~ 1.0 %
Extrapolate well-reconstructed tracks to the Muon system Look for compatible hits in a “field of interest” around the extrapolated tracks
LHCb: a stroll from Trigger to Physics 39/54
Eduardo Rodrigues CPPM, 4th May 2007
Particle Identification (PID)Particle Identification (PID)
invariant mass K invariant mass
With PID With PID
invariant mass
No PIDHadrons: RICH1 and RICH2
Electrons & neutrals: Calorimeter system
Muons: Muon system
LHCb: a stroll from Trigger to Physics 40/54
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V. Physics analysisV. Physics analysis
Flavour taggingFlavour tagging
Event selection & background estimationEvent selection & background estimation
- example of the decay B- example of the decay Bss D Dss h h
LHCb: a stroll from Trigger to Physics 41/54
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Purpose / need:Purpose / need: Determination of flavour of B-mesons at production (at primary vertex)Determination of flavour of B-mesons at production (at primary vertex)
tagging gives (best estimate of) the flavour by examining the rest of the eventtagging gives (best estimate of) the flavour by examining the rest of the event
time-dependent analyses require flavour taggingtime-dependent analyses require flavour tagging
Quantifying the tagging performance :Quantifying the tagging performance :
tagging efficiencytagging efficiency
wrong tag fractionwrong tag fraction
CP asymmetries dilutedCP asymmetries diluted
with dilution factorwith dilution factor
Flavour tagging (1/2)Flavour tagging (1/2)
R Wtag
R W U
N N
N N N
Wtag
R W
N
N N
( ) ( )obsCP CPA t D A t 1 2 tagD
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Flavour tagging (2/2)Flavour tagging (2/2)
bb
ss
uu
t =0Bs
0
PV
z/c = t recKDs
t picoseconds after leaving the primary vertex, the
reconstructed B
decays.
t picoseconds after leaving the primary vertex, the
reconstructed B
decays.
K+
l (e+, )
l (e, )
K
Uses flavour conservation in the hadronization around the Brec D2 1% (B0) , 3% (Bs)
Same-side tag
ll
X b
Wc s
ll
WAssume:
Opposite side tag D2 5%
b-hadron
LHCb: a stroll from Trigger to Physics 43/54
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Event selection: example of BEvent selection: example of Bss D Dss h h (1/3)(1/3)
bt
Bs K
K
,K
Ds
Primary vertex
Bs → Ds-
Bs -> Ds∓ K±
Requirements Trigger on the B-decay of interest : high-PT tracks and displaced vertices
efficient trigger Select the B-decay of interest while rejecting the background
good mass resolution Tag the flavour of the B-decay
efficient tagging and good tagging power (small mistag rate) Time-dependent measurements
good decay-time resolution
LHCb: a stroll from Trigger to Physics 44/54
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Event selection: example of BEvent selection: example of Bss D Dss h h (2/3)(2/3)
Bs→DsK : Bs reconstructed mass signal and main background
Bs→Dsπ : Bs reconstructed mass signal and main background
Bs mass resolution ~14 MeV
LHCb note 2007-017LHCb note 2007-017
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Event selection: example of BEvent selection: example of Bss D Dss h h (3/3)(3/3)
Event yields for 2fb-1 (defined as 1 year)
Bs→Ds- π+ 140k ± 0.67k (stat.) ± 40k (syst.)
Bs→DsŦ K± 6.2k ± 0.03k (stat.) ± 2.4k (syst.)
Results for B/S ratios, no trigger applied
Channel B/S at 90% CL
(bb combinatorial)
B/S at 90% CL
(bb specific)
Bs→Ds-π+ [0.014,0.05]
C.V 0.027±0.008
[0.08,0.4]
C.V 0.21±0.06
Bs→DsŦ K± [0,0.18]
C.V 0.0
[0.08,3]
C.V 0.7±0.3
(central values used for sensitivity studies)
LHCb note 2007-017LHCb note 2007-017
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VI. Physics sensitivity VI. Physics sensitivity studiesstudies
The example of BThe example of Bss D Dss h h
MotivationsMotivations
Sensitivity studies with RooFitSensitivity studies with RooFit
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Motivations (1/2)Motivations (1/2)
B-decay channels Bs→Ds-π+ and Bs→Ds
ŦK±
• Topology is very similar
• Physics is different:
– Bs→Ds-π+ can be used to measure Δms , Δs
• CDF measurement Δms = 17.77 ± 0.1(stat.) ± 0.07(syst.) ps-1
– Bs→DsŦK± can be used to extract the CP angle +s
• Standard Model prediction ≈ 60°
LHCb: a stroll from Trigger to Physics 48/54
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Motivations (2/2)Motivations (2/2)Bs Ds mode:
Flavour-specific decay(2 decay amplitudes only)
Bs Ds K mode: 4 decay amplitudes of interest:
Bs, Bs -> Ds+K-, Ds-K+ -> 2 time-dependent asymmetries
for the 2 possible final states
Ratio of amplitudes of order 1-> large interference and asymmetry expected Bs -> Ds
∓ K±
Bs → Ds-
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Physics sensitivity studiesPhysics sensitivity studiesLHCb Sensitivity studiesLHCb Sensitivity studies
Measurement of Measurement of ++ss with combined B with combined Bss D Dss and Bs and Bs D Dss K samples K samples
Complete fit allows to obtain Complete fit allows to obtain mmss, mistag rate, etc., mistag rate, etc.
RooFit implementation for Toy MC:RooFit implementation for Toy MC: Simultaneous BSimultaneous Bss D Dss and Bs and Bs D Dss K fit: correlations taken into account K fit: correlations taken into account
All decay rate equations included All decay rate equations included (see next page)(see next page)
Using latest 2004 data challenge selection results (LHCb-note 2007-017)Using latest 2004 data challenge selection results (LHCb-note 2007-017)
Toy in propertime and mass includes:Toy in propertime and mass includes:
propertime acceptance function (after trigger & selection)propertime acceptance function (after trigger & selection)
per-event propertime errorper-event propertime error
smearing due to mis-taggingsmearing due to mis-tagging
background (rough estimate/description)background (rough estimate/description)
Fit with tagged events, and also with untagged Bs Fit with tagged events, and also with untagged Bs D Dss K events K events
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Decay rates with RooFitDecay rates with RooFit
tmStmCt
Dte
q
pAt sfsff
t
fffBsincos
2sinh
2cosh
21
22
2
tmStmCt
Dte
At sfsff
t
fffB sincos2
sinh2
cosh2
122
21
Re2
f
ffD
21
Im2
f
ffS
2
2
1
1
f
f
fC
Final state f : Ds-π+ or Ds
-K+
For charge conjugate final states:
B → B , f → f , λf → λf , Af → Af p/q → q/p
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Description in propertimeDescription in propertime
ss DB KDB ss
Acceptance function(after trigger & sel.)
Combined sample, tagged events, 5-year statistics
Proper time per-event error distribution
mean value 33fs
most probable value 30fs
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Description in massDescription in mass
Signal & background, 5-year statistics
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Results with untagged eventsResults with untagged events
Sensitivity to Error on + s (scaled to 1 year) ~ 12°
• 2 Dsπ equations, 4 DsK equations, simultaneous fit. • DC04 input, collected data from 400 “experiments” of 5y tagged data,
scaled results to 1y• Fit a Gaussian to the fitted values distribution, pull distribution
Parameter Δms (ps)-1 ωArg(λf) rad Arg(λ f ) rad |λf| +s ° ΔT1/T2 °
input value 17.5 0.328 1.047 -1.047 0.37 60 0
fitted value 17.5 0.328 1.06 -1.04 0.37 60.14 0.28
resolution 5y 0.003 0.001 0.17 0.14 0.03 5.47 5.37
resolution 1y 0.007 0.003 0.26 0.32 0.06 12.2 12.0
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Eduardo Rodrigues CPPM, 4th May 2007
Thank youThank you