Trigger Strategy and Performance of the LHCb Detector Mitesh Patel (CERN) (on behalf of the LHCb Collaboration) Thursday 7 th July 2005.

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Presentation transcript:

Trigger Strategy and Performance of the LHCb Detector Mitesh Patel (CERN) (on behalf of the LHCb Collaboration) Thursday 7 th July 2005

7th July 2005HCP Mitesh Patel2 Introduction LHCb experimental goals : –Precision measurements of CP Violation in B decays –Aim to (over-)constrain the unitarity triangle by making measurements in multiple channels b production predominately at small polar angles → LHCb optimised as single forward arm spectrometer To meet the physics goals require a trigger which can select : – Multitude of signal channels in the LHCb experimental environment – Channels required for calibration, alignment and systematic studies – Channels that allow the efficiency of the tagging of B flavour to be evaluated – Unbiased control channels System must be simple, robust and flexible

7th July 2005HCP Mitesh Patel3 The LHCb Trigger Environment LHC Bunch crossing frequency: 40 MHz Non empty bunches → 30 MHz LHCb Luminosity : 2×10 32 cm -2 s -1 –10-50 times lower than ATLAS, CMS –B decays → displaced secondary vertex, need ~1 interaction/event ‘Visible’ interactions at 10 MHz –100 kHz bb events (800 kHz cc) –15% of bb events: all decay products of at least one B in detector –Branching ratio of interest : to Use information from a variety of LHCb’s detectors to reduce 10 MHz …

7th July 2005HCP Mitesh Patel4 Detectors in the LHCb Trigger VErtex LOcator primary vertex impact parameter displaced vertex Trigger Tracker p, p T Calorimeters PID: e, ,  0 Trigger on hadr. Muon System Scintillator Pad Detector Charged multiplicity Pile-up system multiple interactions, charged multiplicity

7th July 2005HCP Mitesh Patel5 Trigger Strategy The physics goals of LHCb motivate : –Exclusive triggers : ‘hot’ physics eg. B s  D s h, B s  B 0  J/  K S, B 0  D * , B (s)  h  h   B 0  K *    ,  B 0  D 0 K*, B s      B s  J/  B s  –Inclusive triggers : Inclusive single-muon sample [independent of signal type ] –Sample triggered independent of signal type – unbiased on the signal side –Signal trigger efficiencies Inclusive di-muon sample [selected without lifetime information] –Clean mass peaks for alignment, momentum (B field) calibration –Proper time resolution using prompt J/  events Inclusive D* sample [selected without RICH information] –Clean signal of D*   D  (K    )   –Measure PID performance as a function of momentum → Data mining

7th July 2005HCP Mitesh Patel6 Trigger Overview –Level 0 Trigger[4  s][hardware] ‘high’ p T particles in calorimeters and  detector Pile-up System throws away busy events –Level 1 Trigger[~1 ms] [software] Partial read-out: Vertex Detector (VeLo), Trigger Tracker (TT) and L0 summary Find high IP tracks, estimate p T of tracks, link to L0 objects p T of the two highest p T tracks –High Level Trigger [~10 ms] [software] Confirmation of L1 decision then full reconstruction of event Exclusive selections for most important physics channels Inclusive selections Already well developed, relatively fixed Now being developed LHCb will use three levels of trigger : L1 and HLT will be run on a single ~1600 CPU PC farm 10 MHz 1 MHz 200 Hz 1800 Hz 40 kHz +

7th July 2005HCP Mitesh Patel7 The Level 0 Trigger: Overview Fast search for ‘high’ p T particles Cut on global variables L0 has 4  s latency Highest E T , electron,  0, hadron candidates CALORIMETERS 2 highest p T muons  CHAMBERS z and # trks in 1 st, 2 nd vtx PILE-UP SYSTEM Charged particle multiplicity SPD, PILE-UP SYSTEM L0 decision unit L0DU “L0 OBJECTS”  E T CALORIMETERS GLOBAL VARIABLES

7th July 2005HCP Mitesh Patel8 Level 0: Muon Trigger Search for high p T muons –Five muon stations M1-5 –Variable granularity –Projective geometry 2 highest p T candidates per quadrant sent to L0 decision unit  p/p ~ 20% for b-decays Typical Performance: ~88% efficiency on B→J/  (µµ)X

7th July 2005HCP Mitesh Patel9 Level 0: Calorimeter Trigger Scintillator Pad Detector (SPD) Pre-Shower Detector (PS) ECALHCAL Validation cards SPD mult. e±e±  00 hadr E T tot Selection crates ECAL: 6000 cells, 8x8 to 24x24 cm 2 HCAL: 1500 cells, 26x26, 52x52 cm 2 Look for high E T candidates in the calorimeters : –In regions of 2x2 cells –Particle identification from ECAL / HCAL energy PS and SPD information –E T threshold ~ 3 GeV Sent to L0 decision unit: –Highest E T candidate of each type –Global variables Total calorimeter energy SPD multiplicity Typical Performance: 30-50% efficiency on hadronic channels for about 700 kHz bandwidth 00

7th July 2005HCP Mitesh Patel10 Level 0 : Performance L0 Decision unit : –OR of high E T candidates –Applies cuts on global variables Performance : –Efficiency ~50% for hadronic channels, 90% for  channels, 70% for radiative channels –1% bb → 3% after L0 –8% cc → 10% after L0 Type Threshold (GeV) Rate (kHz) Hadron Electron Photon  0 local  0 global Muon Di-muon Global Variable Cut Tracks in 2 nd vtx3 Pile-Up multiplicity 112 hits SPD multiplicity280 hits Total E T 5 GeV

7th July 2005HCP Mitesh Patel11 Multiple routes through L1 : – Generic Line : L1-Variable: log(pt1)+log(pt2) pt1,2 two highest p T tracks – Muon lines : Single muon: p T >2.3 GeV, IP >0.15 mm Dimuons: J/  ± 500 MeV window OR : m µµ >500MeV and IP>0.05mm OR : m µµ >2.5GeV – Photon, electron lines : L1-Variable (relaxed) + E CAL >3.1 GeV The Level 1 Trigger: Overview Find high IP tracks (VErtex LOcator) –Confirm track / Estimate p T from Trigger Tracker –Link VELO tracks to L0-objects L1 algorithm run on PC Farm –Average latency: 1 ms (max 50 ms) 2D (rz) tracking in VELO Primary Vertex search Allow up to 3 PV 2D track selection 0.15mm < IP < 3mm L0  match 3D (r  z) VELO tracking Confirm IP L0  match p, p T estimation Use VELO-TT track + fringe B field OR : VELO track + L0 muon L1 decision

7th July 2005HCP Mitesh Patel12 Level 1: Event Reconstruction L1 relies on the LHCb VErtex LOcator (VELO) : –Silicon tracker before the LHCb magnet –Angular coverage of full angular range of downstream detector –Sensors ~7mm away from beam, retractable (injection), in secondary vacuum –Foils protect against RF pickup from the LHC beam –21 sensor stations : 2 R- and 2  -measuring sensors per station –Gradual increase of pitch (40  m to 103  m) 100 cm Interaction region  sensor R sensor Si Sensors RF foils

7th July 2005HCP Mitesh Patel13 z-vertex histogram xy-vertex Example: 2D tracks in 45 o  z ~60  m  x,y ~20  m Level 1: Event Reconstruction The Trigger Tracker Fast tracking strategy : –~70 tracks/event after L0 : perform tracking in R-z view (using only R sensors) –Primary vertex σ Z ~ 60  m, σ X,Y ~ 20  m –Select 2D tracks with 0.15 < IP < 3 mm → 8.5 tracks/event –3D tracking for selected tracks p T measurement using Trigger Tracker –TT : two layers of Si detectors with 200  m pitch –Only 0.15Tm of B field between VELO and TT →  p T / p T ~ 20-40% allows rejection of low p tracks which can fake high IP Matched L0-  : →  p T / p T ~ 5%

7th July 2005HCP Mitesh Patel14 L1 decision : –Take OR- of the multiple routes through L1 –Tuned for retention of 4% of minimum bias L0 triggers (40 kHz L1 output rate) Performance : Level 1 : Performance L0 efficiency L1 efficiency L0  L1 eff ChannelGeneric Single  Di-  J/  ElectronPhotonTotal Bd0→ +-Bd0→ +- 81.8%1.6%0.1% 4.3%2.7%82.6% B s 0 → D s - K %4.0%0.7%0.8%4.4%2.9%80.9% B d 0 → D 0 (K +  - )K * 83.5%2.0%0.4%0.1%5.0%3.3%85.4% B s 0 →J/  (     )  74.3%42.8%25.0%45.5%1.9%1.7%87.2% B d 0 → K *  54.9%2.4%0.4%0.3%17.3%30.9%67.2% Minimum Bias2.9%0.7%0.2% 0.4% 4.0% 3% bb after L0 → 16% after L1 10% cc after L0 → 18% after L1 log(pt1)+log(pt2) eg. Generic L1-Variable: log(pt1)+log(pt2)

7th July 2005HCP Mitesh Patel15 The High Level Trigger: Overview High Level Trigger (HLT) : –Generic Algorithm: repeat L1 then full readout of the detector –Muon Highway feeds inclusive muon modes –Form basic particles, composites, search for signatures of hot physics channels (exclusive), D* inclusive –10ms to run (in 2007) – algorithm run on same CPU farm as L1 B s →  B d → D*  B d → D 0 K* B d →  K* B → J/  X B s → D s  B s →  Exclusive HLT Inclusive di-  Inclusive D* Inclusive B →  D s → KK   → KK D 0 → K  KK Loose D 0 → hh Loose dimuons K* → K  muons Photons, electrons , K Generic HLT Muon Highway

7th July 2005HCP Mitesh Patel16 HLT Generic Redo “L1” with improved: –momentum resolution –muon matching HLT generic reconstructs ~1/3 of tracks in the event and redoes L1 in ~4 ms Reduces rate from 40 kHz input from L1 to 10 kHz: –16% bb after L1 → 38% after HLT Generic –18% cc after L1 → 27% after HLT Generic Then have ~24 ms for further HLT selections

7th July 2005HCP Mitesh Patel17 HLT Exclusive HLT Exclusive being tuned for ~10 core physics channels In these channels cuts tuned to take ~15Hz MB / channel B mass resolutions ~30 MeV Mass windows >±500 MeV D s →KK  Bs→DsBs→Ds B s →  Bd→D*Bd→D* B s → D s K Bs→KBs→KBd→KBd→K B s → KK B d →  B → hh reconstructed as B → 

7th July 2005HCP Mitesh Patel18 HLT : Performance Channel Efficiencies w.r.t. Offline and L0xL1 selected signal GenericTracking Total Efficiencies Excl. B  D*Total Bs  +-Bs  +- 99%93%91%90%94% Order of 1% 98% B d  K*  +  - 98%82%73%62%58%91% B d,s  h + h - 94%95%88% Order of 0.5% Order of 2% 88% B s   71%93%61%62% B s  D s h 93%82%60%62% B d  D*  94%58%48%43%55% HLT still under study, efficiencies on L0L1 and offline selected events 60-90% Philosophy to try and trigger channels in many ways Further inclusive triggers will make us more robust to the unknown Limited time available for online tracking → different to offline : inefficiency in high multiplicity channels – strategies being explored to resolve this …

7th July 2005HCP Mitesh Patel19 B s →  selection on L0L1 and offline selected events : –Online tracking  tracking = 0.73 –HLT selection cuts  selection = 0.97 → HLT exclusive selection efficiency  = 0.71 Select only 3 of the 4 tracks (  K), use online RICH to control the background : –Online tracking  tracking = 0.93 –HLT selection cuts  selection = 0.94 → HLT exclusive selection efficiency  = MeV  K mass  mass 3 track 4 track 1000MeV Before RICH cut After RICH cut

7th July 2005HCP Mitesh Patel20 Overall Trigger Performance B d   +  - ~37% B s  D s K ~23% B s  J/  ~70% Total 2 KHz bb 900 Hz cc 600 Hz Level-0 Level-1 HLT

7th July 2005HCP Mitesh Patel21 Trigger Robustness Several scenarios considered : –Event multiplicity –Noise, misalignment, resolution –Increased material –LHC beam position –LHC background –Size of the CPU farm The performance of L0 is stable within 10%, L1 is stable within 20% The execution time and L1 event size is stable to within 30%

7th July 2005HCP Mitesh Patel22 Real Time Trigger Challenge But will it work … ?! The Real Time Trigger Challenge : –Operate one (few) subfarms of the DAQ under realistic conditions –44 double CPU boxes –Full-speed Data Input –Long-term operation (hours) –Exercise realistic Level-1/HLT code –Exercise/evaluate realistic overheads –Establish performance of ‘modern’ CPUs compared to (today’s) standard CERN Happening now !

7th July 2005HCP Mitesh Patel23 Conclusions LHCb will use three level of trigger to deliver inclusive and exclusive samples of B decays suitable for it’s physics goals : –Exclusive selection of core physics channels –Samples to allow calibration/alignment studies –Data that allows the trigger efficiencies to be determined The L0 and L1 triggers are well developed and performance is good The High Level Trigger continues to evolve as our understanding of the LHCb physics potential evolves The trigger system is robust and flexible

7th July 2005HCP Mitesh Patel24 Level 0: Pileup System Two planes of Silicon sensors upstream of the interaction point Used to identify and reject multi-Primary- Vertex events : –Measure R coordinate (-4.2<  <-2.9) –From hits on two planes  produce a histogram of z on beam axis –Remove hits contributing to largest peak, look for 2 nd peak above threshold –L0 Decision Unit cuts on # of tracks in the second peak + hit multiplicity Performance : –Vetoes 60% of double interactions keeping 95% of single interactions R A Z PV - Z A R B Z PV - Z B = k k  RARA Z PV’ k’ ZBZB ZAZA RBRB Z PV B A k Silicon r-sensors