SAC Review Meeting May 20, 2005 Marcel Merk LHCb Simulation Studies: From Detector Optimization to Data Preparation SAC Review Meeting May 20, 2005 Marcel Merk

The “Tracking and Physics” Team The NIKHEF LHCb software “team” 2005: Staff: M. M., G. Raven Postdoc (CERN based): E. Rodrigues Graduate students: E. Bos, B. Hommels, S. Klous, J. Nardulli, G.Ybeles Smit, J.v.Tilburg, M. Zupan. Undergraduate students: J. Amoraal, B. M’charek NIKHEF software activities embedded in: The LHCb Computing Project (M.M. convenor “Track Fitting”) The Physics Planning Group (G.Raven convenor “Proper time and mixing”) Graduate Student “Model” ~ 2 years contribution to hardware or software ~ 1 year contribution to physics studies ~ 1 year thesis writing + other

Past Studies Theses Past Simulation studies to optimize LHCb (2001) Thesis N. Zaitsev (Pile-up and Bs→J/yf) (2002) Thesis R. v.d. Eijk (OT and tracking) (2003) Thesis R. Hierck (Tracking and Bs→DsK/p) (2004) Thesis N. v. Bakel (Velo and Bs mixing) Past Simulation studies to optimize LHCb Event yields vs. hadronic interaction lengths Pattern recognition vs. detector occupancy Resolutions vs. multiple scattering LHCb Classic => LHCb Light …

Evolution since Technical Proposal Reduced material Improved level-1 trigger

Present Studies Present Studies: preparations for data OT DAQ simulation and decoding Track pattern recognition Track fitting and alignment Lifetime reconstruction Bs oscillation and CP violation extraction Our physics motivations include: Bs oscillation with Bs→ Dsp Dms CP violation with with Bs → DsK CP angle g – 2c Search for new physics with Bs → J/yf Bs mixing angle 2c Study of rare decays with b→s l+l- b→s penguin Illustrate our studies using the example of the decays Bs → Dsp and Bs → DsK

bt The Decay Bs→Ds h Two decays with identical topology: Bs → Ds- p + Bs -> Ds∓ K± bt Bs K K ,K  Ds Primary vertex p p Experiment: Trigger on B decay of interest. “high” Pt tracks and displaced vertices displaced vertices Efficient trigger Select the B decay, reject background: Mass resolution Tag the flavour of the B decay Tagging power Plot the tagged decay rate as function of the decay time Decay time resolution

Physics with Bs-→Ds- p+ : Dm u Bs Ds- p+ BR~10-4 Dilutions: A(t) : Trigger acceptance Wtag : Flavour Tagging dt : Decay time Resolution Fit them together with Dm Measure Oscillation Frequency! 1 year data LHCb

Physics with Bs→Ds∓ K± : g u Bs Ds- K+ BR~10-5 Ds- b s u c Bs K+ Vub + Bs s b Introduce also: d = strong phase difference ; r = ratio between amplitudes

Physics with Bs→Ds∓ K± : g u Bs Ds- K+ BR~10-5 Ds- b s u c Bs K+ + Bs s b Measure Oscillation Amplitude! 4 decay rates to fit the unknown parameters: Ration between diagrams: r Strong phase: d Weak phase: g Same experimental dilutions as in Dsp should be added: Use the value of A, wtag and dt as obtained with Dsp fit… Bs→ Ds- K+ Bs→ Ds-K+ Bs→ Ds+ K- Bs→ Ds+K-

The expected signal for Dsp and DsK Nominal expectations for Efficiency Background Resolution Tagging power Etc. Bs mixing relatively easy CP signal is not self-evident Use full statistical power in the data 5 years data: Bs→ Ds-p+ Bs→ Ds-K+ (Dms = 20) (g = 65 degrees) Measure frequency Measure amplitude

Simulation Software: “Gaudi” Applications Event Generator: Pythia: Final state generation Evtgen: B decays Detector Simulation: Gauss: GEANT4 tracking MC particles through the detector and storing MC Hits J.Nardulli, J.v.Tilburg: Geometry and MC Hits for the Outer Tracker Detector Response (“digitization”): Boole: Converting the MC Hits into a raw buffer emulating the real data format B.Hommels, J.Nardulli, A.Pellegrino: L1 and DAQ data format Outer Tracker Reconstruction: Brunel: Reconstructing the tracks from the raw buffers. E.Bos, H.Hommels, M.M., J.Nardulli, G.Ybeles Smit, J.v.Tilburg Physics: DaVinci: Reconstruction of B decays and flavour tags. LoKi : “Loops and Kinematics” toolkit. J.Amoraal, S.Klous, B.M’charek, G.Raven, J.v.Tilburg, M.Zupan, Visualization: Panoramix: Visualization of detector geometry and data objects J.v.Tilburg: Display of tracks

The LHC environment pp collisions @ s=14 TeV s (inel)=79.2 mb, s (bb)=633 mb Bunch crossing @ 40MHz 25 ns separation sinelastic = 80mb At high L >>1 collision/crossing Prefer single interaction events Easier to analyze! Trigger Flavor tagging Prefer L ~ 2 x 1032 cm-2s-1 Simulate 10 hour lifetime,7 hour fill Beams are defocused locally Maintain optimal luminosity even when Atlas & CMS run at 1034

Simulation: Switched from GEANT3… TT RICH1 VELO

…to GEANT4 (“Gauss”) Note: simulation and reconstruction use identical geometry description.

Event example: detector hits J.v.Tilburg

Event example (Vertex region zoom)

Detector Response Simulation: e.g.: the Outer Tracker J.Nardulli, J.v.Tilburg OT double layer cross section 5mm straws pitch 5.25 mm Track e- Geant event display TDC spec.: 1 bunch + Spill-over + Electronics + T0 calibration

Track finding strategy T track Upstream track B. Hommels G. Ybeles Smit N. Tuning T seeds VELO seeds Long track (forward) Long track (matched) J.v.Tilburg VELO track Downstream track R.Hierck Long tracks  highest quality for physics (good IP & p resolution) Downstream tracks  needed for efficient KS finding (good p resolution) Upstream tracks  lower p, worse p resolution, but useful for RICH1 pattern recognition T tracks  useful for RICH2 pattern recognition VELO tracks  useful for primary vertex reconstruction (good IP resolution)

Result of track finding On average: 26 long tracks 11 upstream tracks 4 downstream tracks 5 T tracks 26 VELO tracks T3 T2 T1 Typical event display: Red = measurements (hits) Blue = all reconstructed tracks TT VELO 2050 hits assigned to a long track: 98.7% correctly assigned Efficiency vs p : Ghost rate vs pT : Ghost rate = 3% (for pT > 0.5 GeV) Eff = 94% (p > 10 GeV) Ghosts: Negligible effect on b decay reconstruction

Robustness Test: Quiet and Busy Events J.v.Tilburg Monitor efficiency and ghost rate as function of nrel: “relative number of detector hits” <nrel> = 1

Kalman Track Fit E.Bos. M.M., E.Rodrigues, J.v.Tilburg Reconstruct tracks including multiple scattering. Main advantage: correct covariance matrix for track parameters!! z Impact parameter pull distribution: s = 1.0 Momentum pull distribution: s = 1.2

Experimental Resolution dp/p = 0.35% – 0.55% p spectrum B tracks sIP= 14m + 35 m/pT 1/pT spectrum B tracks Momentum resolution Impact parameter resolution

Trigger L0 pT of m, e, h, g L1 Level-0: Level-1: Impact parameter pile-up L0 40 MHz Calorimeter Muon system Pile-up system Level-0: pT of m, e, h, g 1 MHz Vertex Locator Trigger Tracker Level 0 objects Level-1: Impact parameter Rough pT ~ 20% L1 B->pp Bs->DsK 40 kHz ln IP/IP ln IP/IP HLT: Final state reconstruction Full detector information Signal Min. Bias 2 kHz output OT in L1: B.Hommels, N.Tuning ln pT ln pT

B Mass Reconstruction p d ,K K Bs K Ds  J.v.Tilburg, B.M’charek S.Klous, J.Amoraal M.Zupan Final state reconstruction Combine K+K-p- into a Ds- Good vertex + mass Combine Ds- and “bachelor” into Bs Pointing Bs to primary vtx Ds Bs K K ,K  d p 47 mm 144 mm 440 mm Mass distribution: K/p separation

Annual Yields and B/S for Bs→Dsh Efficiency Estimation: edet (%) erec/det (%) esel/rec (%) etrg/sel (%) etot (%) Bs→Dsp 5.4 80.6 25.0 31.1 0.337 Bs→DsK 82.0 20.6 29.5 0.269 Background Estimation: Currently assume that the only background is due to bb events Background estimates limited by available statistics Decay Annual yield B/S Bs→Dsp 82k 0.32 ± 0.10 Bs→DsK 5.4k <1.0 (90%) C.L. Estimation of Bs→Dsp background in the Bs→DsK sample: B/S = 0.111 ± 0.056

Decay time reconstruction: t = m d / p Error distribution B decay time resolution: As an illustration, 1 year Bs→Ds-p+ Pull distribution: Measurement errors understood!

Sensitivity Studies Many GEANT events generated, but: M.M., G.Raven, J.v.Tilburg Many GEANT events generated, but: How well can we measure Dms with Bs→Dsp events? How well can we measure angle g with Bs→DsK events? as function of Dms, DGs, r, g, d, and dilutions wtag, dt, …? Toy MC and Fitting program: Generator: Generate Events according to theory B decay formula An event is simply a generated B decay time + a true tag. Simulator: Assign an observed time and an error Use the full MC studies to do the smearing Fitter: Create a pdf for the experimentally observed time distribution and fit the relevant parameters

Toy Generator Generate events according to the “master” formula for B decay Bs→Ds-K+ Relevant physics parameters: Bs→Ds+K Bs→Ds+K- With: For Ds+K-: replace g by -g For Dsp: Simplify: r=0

Dilutions in Bs→Dsp Plot the MC toy decay rate with the following situation: 1 year data Bs→Ds-p+ Experimental Situation: Ideal resolution and tag

Dilutions in Bs→Dsp Plot the MC toy decay rate with the following situation: 1 year data Bs→Ds-p+ Experimental Situation: Ideal resolution and tag Realistic tag

Dilutions in Bs→Dsp Plot the MC toy decay rate with the following situation: 1 year data Bs→Ds-p+ Experimental Situation: Ideal resolution and tag Realistic tag Realistig tag and resolution

Dilutions in Bs→Dsp Plot the MC toy decay rate with the following situation: 1 year data Bs→Ds-p+ Experimental Situation: Ideal resolution and tag Realistic tag Realistig tag and resolution Realistic tag + reso + background

Dilutions in Bs→Dsp Plot the MC toy decay rate with the following situation: 1 year data Bs→Ds-p+ Experimental Situation: Ideal resolution and tag Realistic tag Realistig tag and resolution Realistic tag + reso + background Realistic tag+reso+bg+acceptance

Fitting time dependent decay rates Use unbinned Likelihood fitter Why use complicated method? Weigh precisely measured events differently from badly measured events Rely on the reconstructed event error Allow for a scale factor and bias in the analysis Error distr Pull distr

Fit the Physics parameters in Dsp and DsK M.M. Use the 4 tagged (B) and (B) Dsp decay rates to fit Dms and Wtag fraction Use the 4 tagged DsK events to fit r, g, d 5 years data: Bs→ Ds-p+ Bs→ Ds-K+ (Dms = 20) Actually perform the Dsp and DsK fits simultaneous For each setting of the parameters repeat ~100 toy experiments A task for the GRID

The sensitivity of Dms after 1 year Precision on Dms in ps-1 Dms 15 20 25 30 s(Dms) 0.009 0.011 0.013 0.016 The sensitivity for Dms Amplitude fit method analogous to LEP Curves contain 5 different assumptions for the decay time resol. 5s Sensitivity: Dms = 68 ps-1 ~1000 jobs

CP angle g sensitivity for many parameter settings Dms 15 20 25 30 s(g+d) 12.1 14.2 16.2 18.3 (Ab-)using the GRID DGs/Gs 0.1 0.2 s(g+d) 12.1 14.2 16.2 g+d 55 65 75 85 95 105 s(g+d) 14.5 14.2 15.0 15.1 Precision on angle g after one year with 1 year data: s(g) ~ 14o d -20 -10 +10 +20 s(g+d) 13.9 14.1 14.2 14.5 14.6 Dependence on background Dependence on resolution

Bs mixing phase and b→s penguin Bs → J/yf Admixture of CP even and CP odd final states Sensitive to Bs mixing phase J.Amoraal, S.Klous reconstructed matched to generated decay b→s m+m- b→s decay (Afb) is sensitive to SUSY parameters Inclusive event selection M. Zupan

Summary NIKHEF LHCb group has a relatively large involvement in software Past: Detector Optimization (4 Theses: N.Z.:2001, R.v.d.E.:2002, R.H.:2003, N.v.B.:2004) Now: Preparation for Data Reconstruction Responsibilities (convenor: “Track fitting”) (M.M.) OT simulation and detector response (J.v.Tilburg, J.Nardulli) OT region pattern recognition (Online and Offline) (B.Hommels, G.Ybeles Smit) Kalman track fitting (E.Rodrigues, J.v.Tilburg) Alignment studies (E.Bos, J.Nardulli) Physics Responsibilities (convenor: “Proper time and mixing”) (G.Raven) Measurement of Dms with Bs → Ds p (J.v.Tilburg) Measurement of g-2c with Bs → DsK (J.v.Tilburg, B.M’charek) Measurement of 2c with Bs → J/yf (S.Klous, J.Amoraal) Study of rare decays with b → s l+l- (M. Zupan)

Outlook A possible scenario before the LHCb measurement of g:

Outlook A possible scenario after the LHCb measurement of g:

The End (Some X-tra slides)

B Physics: A (quick) comparison LHCb TevaTron Babar/Belle √s 14 TeV 2 TeV 10.4 GeV L (cm-2 s-1) 2 x 1032 cm-2 s-1 4x1033 cm-2s-1 sbb 500 mb 100 mb 1.05 nb sbb / sinel 1/160 1/1000 1/4 N bb / year 1012 2 x1011 4 x 107 Distance 10 mm 5 mm 260 mm Comparison with e+e- factories: All b hadrons produced: Bu (40%), Bd(40%), Bs(10%), Bc and b-baryons (10%) => Bs physics! Statistics vs Systematics B hadrons not coherent: mixing dilutes tagging Many particles not associated to b hadrons: primary vertex Decay time resolution Rare decays Comparison with hadronic facilities: CDF & D0: S/B Dedicated trigger PID BTeV: ~ equivalent ECAL Vtx+Trigger

BaBar & Belle D0/CDF HERA-B LHCb PEP-II/KEKB Tevatron HERA LHC e+e- pp mode e+e- pp pA Start datataking 1999 2002 200? 2007 s (GeV) 10.4 = M(4S) 2000 42 14000 sbb/sqq 1/4 1/1000 1/1000000 1/160 Nqq/s (Hz) 40 20k 10M 13M Nbb/s (Hz) 10 20 100K <B flight distance> (um) 260 450 9000 10000

Efficiencies, event yields and Bbb/S ratios Nominal year = 1012 bb pairs produced (107 s at L=21032 cm2s1 with bb=500 b) Yields include factor 2 from CP-conjugated decays Branching ratios from PDG or SM predictions

CP Asymmetries and Dilutions Both mis-tags (w) & finite proper time resolution (σt ) dilute CP asymmetries. A simplified model (tested on toy MC): A plausible scenario: In this (Bs) case σt dominates dilution error, and total systematic significant! (eg. our expected annual statistical precision on Af for DsK is 0.05 [CHECK]) Hence, we are now investigating ways to maximise understanding of tagging, proper time resolution and acceptance, and trigger biases. (Needless to say, any improvement in performance is also useful !)

LHCb

B Production @ LHC qb O(10%) Pythia & hep-ph/0005110 (Sjöstrand et al) Forward (and backward) production Build a forward spectrometer

 LHCb detector ~ 200 mrad ~ 300 mrad (horizontal) 10 mrad p p Inner acceptance ~ 15 mrad (10 mrad conical beryllium beampipe)

LHCb tracking: vertex region  VELO: resolve Dms oscillations in e.g. Dsp events

LHCb tracking: vertex region Pile-Up Stations Interaction Region s=5.3 cm y x y x 

LHCb tracking: momentum measurement Tracking: Mass resolution for background suppression in eg. DsK By[T]  Total Bdl = 4 Tm Bdl Velo-TT=0.15 Tm

LHCb tracking: momentum measurement All tracking stations have four layers: 0,-5,+5,0 degree stereo angles. ~1.41.2 m2 ~65 m2 

LHCb Hadron Identification: RICH 5 cm aerogel n=1.03 4 m3 C4F10 n=1.0014 RICH2 100 m3 CF4 n=1.0005 3 radiators to cover full momentum range: Aerogel C4F10 CF4  RICH: K/p separation e.g. to distinguish Dsp and DsK events.

LHCb calorimeters e h  Calorimeter system to identify electrons, hadrons and neutrals and used in the L0 trigger: hadron Pt trigger for Dsh events

LHCb muon detection m  Muon system to identify muons and used in L0 trigger e.g. unbiased trigger on “other B” for Dsp events

Event Generation: Pythia Pythia 6.2: proton-proton interactions at √s = 14 TeV . Minimum bias includes hard QCD processes, single and double diffractive events sinel = 79.2 mb bb events obtained from minimum bias events with b or b-hadron sbb = 633 mb Use parton-parton interaction “Model 3”, with continuous turn-off of the cross section at PTmin. The value of PTmin depends on the choice of Parton Density Function. Energy dependence, with “CTEQ4L” at 14 TeV: PTmin=3.47 ± 0.17 GeV/c. Gives: Describes well direct fit of multiplicity data: Robustness tests…

Charged multiplicity distributions at generator level In LHCb acceptance ( 1.8 < h < 4.9 ) Average charged multiplicity Minimum bias bb CDF tuning at 14 TeV 16.53 ± 0.02 27.12 ± 0.03 LHCb tuning, default pTmin 21.33 ± 0.02 33.91 ± 0.03 LHCb tuning, 3s low pTmin 25.46 ± 0.03 42.86 ± 0.03

Particle ID RICH 2 RICH 1 e (K->K) = 88% e (p->K) = 3% Example: Bs->Dsh K  Bs K ,K Ds Prim vtx

Flavour tag eff = tag (1-2wtag )2 K+ Knowledge of the B flavour at production is needed for the asymmetries B0 Ds- tagging strategy: opposite side lepton tag ( b → l ) opposite side kaon tag ( b → c → s ) (RICH, hadron trigger) same side kaon tag (for Bs) opposite B vertex charge tagging B0 D K- l b Bs0 b s sources for wrong tags: Bd-Bd mixing (opposite side) b → c → l (lepton tag) conversions… s K+ u u 4 35 42 εeff [%] Wtag [%] εtag [%] 6 33 54 Bd  p p Bs  Ds h Combining tags effective efficiency: eff = tag (1-2wtag )2

Trigger Acceptance function Impact parameter cuts lead to a decay time dependent efficiency function: “Acceptance” Acc Bs→DsK

Bs→Dsh Reconstruction J.v.Tilburg, B.M’charek S.Klous, J.Amoraal M.Zupan Final state reconstruction Combine K+K-p- into a Ds- Good vertex + mass Combine Ds- and “bachelor” into Bs Pointing Bs to primary vtx Ds Bs K K ,K  d p 47 mm 144 mm 440 mm Mass distribution: K/p separation

Toy Simulation Smear theoretical events (t=ttrue) into experimental events (trec) and assign an experimental error (dtrec). Method: From the full simulation make a lookup table with selected events: ttruei, treci, dtreci Generate ttrue in toy and assign trec and dtrec from look-up table, such that non-Gausian effects of the full simulation are included For etag fraction of the events assign an event tag: Statistically assign 1-wtag correct tags, and wtag wrong tags. Current studies etag = 54% wtag = 33% . Apply an acceptance function A(trec) by statistically accepting events according to the acceptance value for a given event time.

Likelihood Fitter (general idea) The likelihood that nature produces an event at a given time t = The probability that this event is reconstructed (i.e. observed) at a reconstructed time trec with measurement error dtrec= Thus the likelihood of observing an event (trec, dtrec) = Fit the physics parameters (Dm, g,…) in R such that the likelihood is maximal:.i.e. maximize:

Likelihood Fitter (for the die-hard) Maximize an unbinned likelihood describing the best theory curves simultaneously matching simultaneously the 4 decay rates for Bs->Ds p and 4 decay rates for Bs-> Ds K Event probab: 1 year data: Bs -> Ds- p+ Bs -> Ds- K+ (Slow computation!) Normalization of the probability: Create the Likelihood: Fit parameters: -Physics: -Experimental: Normalization of the Likelihood is interesting! See also LHCb note…LHCb 2003-124 (Include information of the relative overall rates)

Strategy for Dsp / DsK fits It turns out to be difficult to fit simultaneously the wrong tag fraction, resolution and acceptance function. A small bias in the acceptance function biases the resolution fit A possible solution could be a 4 step procedure: Calibrate the experimental time resolution Fit the acceptance function on the untagged sample of Bs->Dsp events Fit simultaneously the values of Dms, wtag with Dsp events. Fit the values of the r, g, d with the DsK sample

1.Fitting the measurement errors Resolution can be determined from the negative tail of the lifetime distribution. Fit with 10% of 1 year data: S· dtrec . => S = 0.99 ± 0.04 Can L1 trigger be tuned to provide unbiased Bs-> Dsp events? What would be the required bandwidth for this? In any case unbiased samples of J/y events are foreseen. L1 trigger 10% of 1 year untagged Bs→Dsp S=0.99+- 0.04 trec

2. Fitting the acceptance function The acceptance function is modelled as: The function can easily be determined using the unbiased sample 1 year untagged Bs→Dsp Acc trec trec

3. + 4. Fit the Physics parameters Use the 4 tagged (B) and (B) Dsp decay rates to fit Dms and Wtag fraction Use the 4 tagged DsK events to fit r, g, d 5 years data: Bs→ Ds-p+ Bs→ Ds-K+ (Dms = 20) Actually perform the Dsp and DsK fits simultaneous For each setting of the parameters repeat ~100 toy experiments A task for the GRID

(My) Conclusions The decay Bs→Dsp can provide an observation of Dms oscillations in the first year of data taking. Important are: A working hadronic trigger A good tagging procedure Fairly good resolution The decay Bs→DsK can provide an observation of angle g in subsequent years. Important are: Very good mass resolution for background suppression Full understanding of time resolution and tagging for systematics An efficient K/p separation

b  s m+m- reconstructed matched to generated decay lepton spectrum allows theoretically clean calculations of certain coefficients in OPE of electroweak interactions charge AFB sensitive to SUSY parameters pole of AFB sensitive to SUSY parameters Signal events (generated within LHCb acceptance of 400 mrad) 92500 Selected events 455 Trigger (L0&L1) efficiency on selected events 87.3% Total selection efficiency 0.149% Annual yield estimate 9500