Real Time Tracking with ATLAS Silicon Detectors and its Applications to Beauty Hadron Physics

Transcription

1 Real Time Tracking with ATLAS Silicon Detectors and its Applications to Beauty Hadron Physics Carlo Schiavi Dottorato in Fisica - XVII Ciclo

2 Outline The ATLAS Experiment The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Application to B-physics Selection Impact on m s Measurement

8 Outline The ATLAS Experiment Experiment Overview The ATLAS Trigger System The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Application to B-physics Selection Impact on m s Measurement

9 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS detector:

12 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS detector: Tracking and particle identification: Pixel, SCT and TRT forming the Inner Detector (ID)

13 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS Tracking System: Magnetic field: solenoidal magnet; 2 T field

14 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS Tracking System: Pixel detector: sensor elements: 5 4 µm; three layers, built from identical modules; maximum radius: 15 cm.

15 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS Tracking System: SemiConductor Tracker (SCT): sensor elements: strips 8 µm wide; four layers, built from identical modules; maximum radius: 5 cm.

16 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS Tracking System: Transition Radiation Tracker: tubes with two thresholds; provides 36 spatial points per track; maximum radius: 1 m.

17 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS detector: Calorimeters: EM Liquid Argon and Hadronic Tile detectors

18 Experiment Overview The ATLAS experiment, starting operation at the LHC pp collider in 27, will cover many different aspects of high energy physics: discover new physics, to validate or reject the available theoretical models; e.g. Higgs and supersymmetric scenarios; perform precision SM measurements; be capable of detecting unpredicted physical signals. The ATLAS detector: Muons: MDT and CSC chambers plus RPC and TGC trigger

19 Challenges at LHC LHC parameters: Design Start-up CoM energy (TeV) 14 TeV 14 TeV Luminosity cm 2 s Bunch spacing 25 ns 25 ns Interactions/bunch 23 5 b b rate (Hz) H rate (Hz) The LHC environment poses constraints and problems to the ATLAS experiment: event size 1.6 MB, so max data storage rate 2 Hz: reject most interactions; interesting collisions always mixed with background ones: pile-up interactions must be filtered out; 6 cm uncertainty on interaction position along beam line: primary vertex reconstruction required.

20 The ATLAS Trigger System LHC interaction rate ( 1 GHz) is reduced through three trigger selection steps: Level1 Trigger: hardware based (FPGAs ASICs); coarse granularity calo/muon data; latency: 2 µs; output rate: 75 khz. HIGH LEVEL TRIGGER (HLT): Level2 Trigger: detector sub-regions processed; full granularity for all subdetectors; fast rejection steering ; mean execution time: 1 ms; output rate: 2 khz. Event Filter: guided by Level2 result; potential full event access; Offline-like algorithms; mean execution time: 2 s; output rate: 2 Hz; data storage: 3 MB/s.

24 Software Trigger Data Access One of the distinguishing features of the ATLAS Software Selection strategy is the reconstruction in Regions of Interest (RoI): only a subset of detector data is processed; RoI size and position are derived from previous steps; mainly exploited at LEVEL2; parallel processing; goal: minimize processing time and network traffic.

25 Outline The ATLAS Experiment The SiTrack Algorithm On-Line Tracking The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Application to B-physics Selection Impact on m s Measurement

26 On-Line Tracking In the ATLAS experiment, as in all the experiments at hadronic colliders, track reconstruction is a fundamental ingredient for the selection of many event signatures. Its main characteristics: it uses the precise spatial measurements (space points) provided by the tracking detectors; in general it uses data coming from different detectors (e.g. Pixel and SCT); given the previous two points, it can only act in the software trigger framework; the most delicate step is track reconstruction at LVL2, given the limitation on the average event processing time; requires a good timing optimization without spoiling the precision of the reconstructed tracks; fully exploits the RoI-based approach.

27 The SiTrack Algorithm The SiTrack algorithm: combinatorial pattern recognition algorithm; operates at LEVEL2; uses space points from the pixel and strip detectors. It can be described in terms of its component blocks: space point sorting; track seed formation; primary vertex reconstruction; track extension.

28 The SiTrack Algorithm The SiTrack algorithm: combinatorial pattern recognition algorithm; operates at LEVEL2; uses space points from the pixel and strip detectors. It can be described in terms of its component blocks: space point sorting; track seed formation; primary vertex reconstruction; track extension. Space Point Sorting: retrieves points in the RoI; sorts points according to their detector module; subsequent access refers to module addresses; speeds-up algorithm data access.

29 The SiTrack Algorithm The SiTrack algorithm: combinatorial pattern recognition algorithm; operates at LEVEL2; uses space points from the pixel and strip detectors. It can be described in terms of its component blocks: space point sorting; track seed formation; primary vertex reconstruction; track extension. Track Seed Formation: combinatorial formation of SP couples; first point on the innermost Pixel layer; second point on a subset of modules, to reduce combinations; modules subset identified using a probabilistic Montecarlo map; straight line extrapolation to the beam line; cut on transverse impact parameter. Y 1 1 X

30 The SiTrack Algorithm The SiTrack algorithm: combinatorial pattern recognition algorithm; operates at LEVEL2; uses space points from the pixel and strip detectors. It can be described in terms of its component blocks: space point sorting; track seed formation; primary vertex reconstruction; track extension. Primary Vertex Reconstruction: extrapolated longitudinal impact parameter (z ) used to fill a histogram; histogram maxima search; more than one vertex candidate can be retained; seeds not pointing to a reconstructed vertex are discarded.

31 The SiTrack Algorithm The SiTrack algorithm: combinatorial pattern recognition algorithm; operates at LEVEL2; uses space points from the pixel and strip detectors. It can be described in terms of its component blocks: space point sorting; track seed formation; primary vertex reconstruction; track extension. Track Extension: seeds extrapolated to outer layers; third point on a subset of modules, to reduce combinations; modules subset identified using a probabilistic Montecarlo map; cut on third space point distance; track fit: straight line in the longitudinal plane, circle in the transverse plane. Y X

32 The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution.

33 The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon 1 datasets at different p T, to evaluate its efficiency 8 and resolution. Efficiency (%) Efficiency 6 definitions: Fake fraction (%) 4reconstructible MC particle: must pass a set of geometrical 2 cuts plus a cut on p T ; good5 reconstructed track: 25 linked 3 35 to a reconstructible particlep T by (GeV) at least two SP; η 1fake track: reconstructed track 1 where θ is the angle w.r.t. the beam line which is not a good track; 8 8 efficiency: good tracks to 6 reconstructible particles ratio; Transverse 6 Momentum Efficiency 4 1 GeV ± 1.1 % fake fraction: ratio between fake 6 GeV 96. ± 1.1 % 2tracks and all the reconstructed 2 GeV ± 1.1 % tracks passing the applied cuts p T (GeV) η Efficiency (%) Fake fraction (%) η = ln(tan θ/2)

34 The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution. Parameters definitions: η: direction in the RZ plane; φ : direction in the RΦ plane evaluated at the closest distance from the beam line; z : Z impact parameter; d : RΦ impact parameter; p T : transverse particle momentum η rec -η mc Parameter resolutions:.1 1 GeV 6 GeV 2 GeV η (1 3 ) 4, φ (mrad) z (µm) d (µm) /p T (TeV-2 1 ) z rec -z mc.15.1

35 The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution..1 Parameters definitions:.5 η: direction in the RZ plane; φ : direction in the RΦ plane evaluated at the closest distance η rec -η mc from the beam line; z : Z impact parameter; d : RΦ impact parameter; p T : transverse particle momentum z rec -z mc φ rec -φ mc.3 Parameter resolutions: 1 GeV 6 GeV 2 GeV.2 η (1 3 ) 4, φ (mrad) z.1 (µm) d (µm) /p T (TeV -.2 ) /p T rec -1/p T mc.15.1

36 ATLAS SiTrack Electron/Photon b-tagging.1 B-physics Impact on m s The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution. Parameters definitions: η: direction in the RZ plane; φ : direction in the RΦ plane evaluated at the closest distance from the beam line; z : Z impact parameter; d : RΦ impact parameter; p T : transverse particle momentum η rec -η mc z rec -z mc Parameter resolutions:.1 1 GeV 6 GeV 2 GeV η (1 3 ) 4, φ (mrad) z (µm) d (µm) /p T (TeV -.5 ) d rec -d mc

37 ATLAS SiTrack Electron/Photon b-tagging.1 B-physics Impact on m s The SiTrack Algorithm: Basic Performance SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution. Parameters definitions: η: direction in the RZ plane; φ : direction in the RΦ plane evaluated at the closest distance from the beam line; z : Z impact parameter; d : RΦ impact parameter; p T : transverse particle momentum z rec -z mc d rec -d mc Parameter resolutions: 1 GeV 6 GeV 2 GeV η (1 3 ) 4, φ (mrad) z (µm) d (µm) /p T (TeV 1 )

38 ATLAS.1 SiTrack Electron/Photon b-tagging B-physics Impact on m s.1.5 The SiTrack Algorithm: Basic Performance η rec -η mc SiTrack was exercised on single muon datasets at different p T, to evaluate its efficiency and resolution..1 Parameters definitions: η: direction in the RZ plane; φ : direction in the RΦ plane -2 2 evaluated at the closest distance z rec -z mc from the beam line; z : Z impact parameter; d : RΦ impact parameter; p T : transverse particle momentum d rec -d mc φ rec -φ mc /p T rec -1/p T mc Parameter resolutions: 1 GeV 6 GeV 2 GeV η (1 3 ) 4, φ (mrad) z (µm) d (µm) /p T (TeV 1 )

39 Impact on m s Measurement ATLAS SiTrack Electron/Photon b-tagging B-physics Impact on m s Outline The ATLAS Experiment The SiTrack Algorithm Application to Electron and Photon Selection Physical Relevance SiTrack Performance Results for Single Electron Selection Application to b-tagging Selection Application to B-physics Selection

40 Physical Relevance Many channels lead to final states with isolated e/γ. Very clean signatures and high statistical significance. SM Higgs sector: Low mass range channels: H γγ H ZZ ( ) 4l Higgs golden channels: H ZZ llνν H WW lljj H WW lνjj Supersymmetrical scenarios: SUSY Higgs channels with higher significance have lepton/photon final states. Tagging and reconstruction of SUSY particles.

43 SiTrack Performance: Tracking Single isolated electron datasets: Design luminosity: 3 GeV tracks; Start-up luminosity: 25 GeV tracks. Algorithm configuration: η φ =.1.1 RoI; no primary vertex reconstruction is performed, since it would prove very inefficient, given the too low signal track multiplicity; track selection cuts are tuned for high p T values; timing performance is greatly improved by the high p T cut, balancing the effect of the missing vertex reconstruction. Efficiency (%) Fake fraction (%) p T (GeV) p T (GeV) Efficiency (%) Fake fraction (%) η η Start-up Design Efficiency 94. ± 1.6 % 93.3 ± 2.1 % Fake 1.1 ±.2 % 11.1 ±.6 %

44 SiTrack Performance: Timing Single isolated electron datasets: Design luminosity: white; Start-up luminosity: shaded. Algorithm configuration: η φ =.1.1 RoI; no primary vertex reconstruction is performed, since it would prove very inefficient, given the too low signal track multiplicity; track selection cuts are tuned for high p T values; timing performance is greatly improved by the high p T cut, balancing the effect of the missing vertex reconstruction Sorting (ms) Vertexing (ms) Seeding (ms) Extension (ms) Results obtained on 2.4 GHz processor: Start-up Design Sorting (ms).7.26 Seeding (ms).3.77 Extension (ms).18.5 Total (ms)

45 Results for Single Electron Selection The HLT e/γ selection efficiency and rejection w.r.t. to LVL1 were studied on simulated samples, with final ATLAS software. For the initial luminosity 25 GeV isolated electron trigger menu (e25i), studies performed on: signal sample: 25 GeV single electron files; background sample: 17 GeV dijets; initial luminosity pileup occupancy conditions.

46 Results for Single Electron Selection The HLT e/γ selection efficiency and rejection w.r.t. to LVL1 were studied on simulated samples, with final ATLAS software. For the initial luminosity 25 GeV isolated electron trigger menu (e25i), studies performed on: signal sample: 25 GeV single electron files; background sample: 17 GeV dijets; initial luminosity pileup occupancy conditions. Results obtained using SiTrack at LVL2: Step Efficiency Rate L2 Calo 95.6 ±.3% ± 46 Hz L2 ID 87.7 ±.6% 143 ± 12 Hz EF Calo 86.1 ±.6% 11 ± 15 Hz EF ID 79.7 ±.7% 34 ± 6 Hz

47 Results for Single Electron Selection The HLT e/γ selection efficiency and rejection w.r.t. to LVL1 were studied on simulated samples, with final ATLAS software. For the initial luminosity 25 GeV isolated electron trigger menu (e25i), studies performed on: signal sample: 25 GeV single electron files; background sample: 17 GeV dijets; initial luminosity pileup occupancy conditions. Results obtained using SiTrack at LVL2: Step Efficiency Rate L2 Calo 95.6 ±.3% ± 46 Hz L2 ID 87.7 ±.6% 143 ± 12 Hz EF Calo 86.1 ±.6% 11 ± 15 Hz EF ID 79.7 ±.7% 34 ± 6 Hz Track reconstruction at LEVEL2 and its matching with calorimeter clusters are grants an affordable rate at the boundary between the two software selection layers.

48 Impact on m s Measurement ATLAS SiTrack Electron/Photon b-tagging B-physics Impact on m s Outline The ATLAS Experiment The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Physical Relevance SiTrack Performance Results for b-tagging Selection Application to B-physics Selection

49 Physical Relevance Final states containing more than one b-jet are signatures with a substantial discovery potential in different sectors and, e.g. in the searches for Higgs bosons in the intermediate mass range, 8 GeV < m H < 18 GeV. In particular, two main cases can be quoted: H/A b b and H hh b bb b decays where the Higgs boson is produced in association with a b b couple. LVL1 Trigger: calorimeter jet trigger; efficiency reduced by QCD background. b-tagging benefits: provide flexibility, allowing a relaxation of the LVL1 thresholds and increasing the signal selection efficiency. H b b decays where the Higgs boson comes from the associated WH, ZH and t th production. LVL1 Trigger: leptonic trigger from the decay of associated particles. b-tagging benefits: fundamental to reduce the background and the rate for the events selected by the leptonic trigger.

50 SiTrack Performance: Tracking b-jets from the decay of an Higgs boson (m H = 12 GeV). Design luminosity. Start-up luminosity. Algorithm configuration: η φ =.2.2 RoI; primary vertex: high p T are selected and three vertex candidates are retained, obtaining efficiencies exceeding 95%; track selection cuts are tuned to achieve full efficiency down to p T values around 2 GeV; tight track quality selections are applied, to reduce the fake fraction and to provide an high purity track sample. Efficiency (%) Fake fraction (%) p T (GeV) p T (GeV) Efficiency (%) Fake fraction (%) η η Start-up Design Efficiency 84.5 ±.5 % 81.2 ±.5 % Fake 6. ±.1 % 15.3 ±.1 %

51 SiTrack Performance: Timing b-jets from the decay of an Higgs boson (m H = 12 GeV). Design luminosity: white. Start-up luminosity: shaded Algorithm configuration: η φ =.2.2 RoI; primary vertex: high p T are selected and three vertex candidates are retained, obtaining efficiencies exceeding 95%; track selection cuts are tuned to achieve full efficiency down to p T values around 2 GeV; tight track quality selections are applied, to reduce the fake fraction and to provide an high purity track sample Sorting (ms) Vertexing (ms) Seeding (ms) Extension (ms) Results obtained on 2.4 GHz processor: Start-up Design Sorting (ms).25.6 Seeding (ms) Vertexing (ms).18.5 Extension (ms) Total (ms) 3 6

52 Online b-tagging: the Likelihood-Ratio Method The likelihood-ratio method is a statistical tool used to separate two or more event classes, based on a set of characteristic variables. For each reconstructed track sample the likelihood-ratio variable W = S(sig)/S(bkg), is evaluated, where S(sig) and S(bkg) are the probability densities for signal (b-jets) and background (u-jets). To obtain a variable defined on a finite interval, W is replaced by X = W 1 + W, which ranges between (background u-jets) and 1 (signal b-jets).

53 Online b-tagging: Discriminant Variables Many choices can be adopted for the b-tagging discriminant variable. Samples: u-jets and b-jets from the same Higgs decay. Selection performance: u-jet rejection vs. b-jet efficiency curve. Luminosity: start-up.

54 Online b-tagging: Discriminant Variables Many choices can be adopted for the b-tagging discriminant variable. Samples: u-jets and b-jets from the same Higgs decay. Selection performance: u-jet rejection vs. b-jet efficiency curve. Luminosity: start-up. Transverse impact parameter d : Hadrons containing b-quarks have a finite lifetime, so their decay tracks have large d values, while u-jet tracks come from the primary vertex. The significance S = d /σ(d ) is used, where σ(d ) has been parametrized as a function of p T. Entries R.25.2 b-jets u-jets X( d /σ(d )) b

55 Online b-tagging: Discriminant Variables Many choices can be adopted for the b-tagging discriminant variable. Samples: u-jets and b-jets from the same Higgs decay. Selection performance: u-jet rejection vs. b-jet efficiency curve. Luminosity: start-up. Longitudinal impact parameter z : The z impact parameter is distributed around the primary vertex position (z vtx ) for u-jet tracks, while larger z z vtx values are obtained for b-jets. The value of z vtx is reconstructed a posteriori using a sliding window approach, obtaining efficiencies exceeding 95 % and a resolution of about 17µm. Entries R b-jets.14 u-jets X( z -z pv ) b

56 Online b-tagging: Discriminant Variables Many choices can be adopted for the b-tagging discriminant variable. Samples: u-jets and b-jets from the same Higgs decay. Selection performance: u-jet rejection vs. b-jet efficiency curve. Luminosity: start-up. Collective variables: We can also adopt discriminant variables collectively characterizing the jets. In particular, three variables have been combined: average track multiplicity; jet energy; jet invariant mass;

57 Online b-tagging: Discriminant Variables Many choices can be adopted for the b-tagging discriminant variable. Samples: u-jets and b-jets from the same Higgs decay. Selection performance: u-jet rejection vs. b-jet efficiency curve. Luminosity: start-up. Overall combination: All the previous methods can be combined together, in order to obtain the final b-tagging performance. Impact parameters are combined adopting two-dimensional probability density functions. All the other variables are combined multiplying their p.d.f. s.

58 Online b-tagging: Operation at Design Luminosity All the results shown so far refer to the start-up luminosity scenario. The same studies have been repeated on data samples where the design luminosity conditions are simulated. The efficiency vs. rejection curve obtained combining all the discriminant variables show that the selection performance is almost unchanged by the increase in the luminosity. This was expected, since the results on tracking efficiency showed little difference between the two scenarios.

59 Impact on m s Measurement ATLAS SiTrack Electron/Photon b-tagging B-physics Impact on m s Outline The ATLAS Experiment The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Application to B-physics Selection Physical Relevance SiTrack Performance B-physics Trigger Selections

60 Physical Relevance The ATLAS B-physics programme is rather wide; a couple of example measurements can be provided to give an overview of the corresponding trigger strategies. Rare B µ + µ decays. These decays, involving flavour changing neutral current, only occur at loop level in the SM andare sensitive to new physics. LVL1 signature: double muon trigger with two different E T thresholds. LVL2 signature: muon signature confirmation; invariant mass selection. Operating conditions: this kind of menus will be the only B-physics selection operating at all luminosities. B s Ds π and B s Ds a 1 decays. These channels are used to measure Bs B s oscillations and their ms parameter. LVL1 signature: single muon trigger passing a 6 GeV threshold. LVL2 signature: muon confirmation; semi-inclusive or exclusive decay selection in a hadronic calorimeter jet RoI. Operating conditions: this kind of menus will be operational as soon as luminosity will fall below its start-up value.

61 SiTrack Performance: Tracking B s D s π, D s φ π, φ K + K LVL1 trigger: single muon from the other B hadron. Luminosity: start-up. Algorithm configuration: η φ = RoI; primary vertex: three vertex candidates are retained, obtaining 89% efficiency; track selection cuts are tuned to achieve full efficiency down to p T values around 1.5 GeV; loose track quality selections are applied, to increase the tracking efficiency as much as possible. Efficiency (%) Fake fraction (%) p T (GeV) p T (GeV) Efficiency (%) Fake fraction (%) η η Start-up luminosity Efficiency 77. ±.5% Fake 2.6 ±.1%

62 SiTrack Performance: Timing B s D s π, D s φ π, φ K + K LVL1 trigger: single muon from the other B hadron. Luminosity: start-up. Algorithm configuration: η φ = RoI; primary vertex: three vertex candidates are retained, obtaining 89% efficiency; track selection cuts are tuned to achieve full efficiency down to p T values around 1.5 GeV; loose track quality selections are applied, to increase the tracking efficiency as much as possible Sorting (ms) Vertexing (ms) Seeding (ms) Extension (ms) Results obtained on 2.4 GHz processor: Start-up luminosity Sorting (ms).5 Seeding (ms) 5. Vertexing (ms) 1.8 Extension (ms) 1.8 Total (ms) 9.2

63 B-physics Trigger Selections: Ingredients In order to reduce the background contributions and to minimize the overall execution time, preliminary track selection cuts are applied: cuts on reconstructed p T are applied, coherently with offline pre-selections; reduce fake tracks; two tracks are combined only if their z parameters are less than 3mm away; prevents the combination of tracks from different vertices; cuts on particle candidates p T are applied, coherently with offline pre-selections; reduce fake candidates.

64 B-physics Trigger Selections: Ingredients The most powerful tools used for B-physics studies are invariant mass cuts, providing a selection specific to each signal decay channel. For each track pair the invariant mass is evaluated. For most of these cuts tracks are combined in opposite charge-sign pairs.

65 B-physics Trigger Selections: Ingredients The most powerful tools used for B-physics studies are invariant mass cuts, providing a selection specific to each signal decay channel. For each track pair the invariant mass is evaluated. For most of these cuts tracks are combined in opposite charge-sign pairs. Candidate φ mass distribution: φ K + K central value: 119 MeV width: 5.7 MeV Candidates M(φ)

66 B-physics Trigger Selections: Ingredients The most powerful tools used for B-physics studies are invariant mass cuts, providing a selection specific to each signal decay channel. For each track pair the invariant mass is evaluated. For most of these cuts tracks are combined in opposite charge-sign pairs. Candidates Candidate D s mass distribution: D s φ π central value: 1944 MeV width: 32 MeV M(D s )

67 B-physics Trigger Selections: Ingredients The most powerful tools used for B-physics studies are invariant mass cuts, providing a selection specific to each signal decay channel. For each track pair the invariant mass is evaluated. For most of these cuts tracks are combined in opposite charge-sign pairs. Candidate B s mass distribution: B s D s π central value: 5247 MeV width: 11 MeV Candidates M(B s )

68 B-physics Trigger Selections: Semi-Inclusive Semi-inclusive D ± s φ π ± decays selection: track p T > 1.4 GeV; z < 3 mm; invariant mass selection for φ and D s candidates, using asymmetrical windows around their central mass values. Three different mass window widths were tested: loose: [ 2.5 σ, +3. σ]; standard: [ 2. σ, +3. σ]; tight: [ 2. σ, +2.5 σ]. The background efficency was obtained on a B µ X sample, where p T (µ) > 6 GeV. The final rates were evaluated with the following assumptions on the muon signature: rate after LVL1: 23 khz; rate after LVL2 confirmation: 4 khz. Sig eff. Bkg eff. Rate Loose 58 ± 1% 7.2 ±.3% 288 ± 9 Hz Standard 56 ± 1% 6.4 ±.2% 256 ± 8 Hz Tight 55 ± 1% 5.7 ±.2% 228 ± 8 Hz

69 B-physics Trigger Selections: Exclusive Exclusive B s D sπ decays selection; additional cuts introduced: invariant mass selection for B s candidates; cut at p T (B s) > 9 GeV. The background efficency was obtained on a B µ X sample, where p T (µ) > 6 GeV. The final rates were evaluated with the following assumptions on the muon signature: rate after LVL1: 23 khz; rate after LVL2 confirmation: 4 khz. Two different mass window schemes were tested: loose: [ 3. σ, +3.5 σ] for φ, D s; [ 3. σ, +5. σ] for B s; tight: [ 2.5 σ, +3. σ] for φ, D s; [ 3. σ, +4. σ] for B s. Sig eff. Bkg eff. Rate Loose 45 ± 1% 1.9 ±.1% 76 ± 1 Hz Tight 42 ± 1% 1.2 ±.1% 52 ± 1 Hz

70 Outline The ATLAS Experiment The SiTrack Algorithm Application to Electron and Photon Selection Application to b-tagging Selection Application to B-physics Selection Impact on m s Measurement Current Experimental Situation Impact of On-line Selection on ATLAS Reach

71 Current Experimental Situation One of the main ATLAS contributions to the B-physics sector will be the accurate determination of m s, measured in the two decays: B s D s π; B s D s a 1. The current experimental knowledge of the m s parameter is dominated by the results from Bs B s mixing studies at LEP and SLD. Sensitivity: 18.3 ps 1. Hint: 17.5 ps 1, at about 2 σ.

72 Current Experimental Situation One of the main ATLAS contributions to the B-physics sector will be the accurate determination of m s, measured in the two decays: The m s parameter can be indirectly predicted, through a Standard Model fit of the Unitarity Triangle associated to the CKM matrix. B s D s π; B s D s a 1. The current experimental knowledge of the m s parameter is dominated by the results from Bs B s mixing studies at LEP and SLD. Sensitivity: 18.3 ps 1. Hint: 17.5 ps 1, at about 2 σ.

73 Current Experimental Situation One of the main ATLAS contributions to the B-physics sector will be the accurate determination of m s, measured in the two decays: The m s parameter can be indirectly predicted, through a Standard Model fit of the Unitarity Triangle associated to the CKM matrix. B s D s π; B s D s a 1. The current experimental knowledge of the m s parameter is dominated by the results from Bs B s mixing studies at LEP and SLD. Sensitivity: 18.3 ps 1. Hint: 17.5 ps 1, at about 2 σ. 68% 95% 99% m s (ps 1 ) 21.2 ± 3.2 [15.4, 27.8] [13.8, 3.] These results are well compatible with the m s measurements from LEP and SLD.

74 Impact of On-line Selection on ATLAS Reach The 5σ measurement limit achievable by the ATLAS experiment was evaluated as a function of the trigger selection efficiency for the corresponding signal decays. Results are given for an integrated luminosity of 1 fb 1, achievable in a few months running at start-up luminosity. Two systematic uncertainties scenarios are reported.

75 Conclusions A complete characterization of the SiTrack algorithm was provided at three different levels: tracking performance, operating in different conditions; reconstruction of trigger signatures; definition of new trigger selection strategies; trigger selection impact on physics measurements; an example was provided.

76 Conclusions A complete characterization of the SiTrack algorithm was provided at three different levels: tracking performance, operating in different conditions; reconstruction of trigger signatures; definition of new trigger selection strategies; trigger selection impact on physics measurements; an example was provided. Studies performed on two different topologies: single isolated particles and jets. Good efficiency has been obtained while the fraction of fake tracks was kept under control. Tracking performance proved robust w.r.t. changes in the luminosity conditions. The timing performance resulted compatible with the LVL2 framework constraints. All measurements have been obtained on processors slower than the ones adopted in ATLAS.

77 Conclusions A complete characterization of the SiTrack algorithm was provided at three different levels: tracking performance, operating in different conditions; reconstruction of trigger signatures; definition of new trigger selection strategies; trigger selection impact on physics measurements; an example was provided. Studies performed on the trigger selection performance for three different physical signatures. Identification of high momentum isolated electrons. Identification of jets from beauty hadrons. New b-tagging strategies were developed and tested. Semi-inclusive and exclusive selection of decay channels relevant to B-physics studies.

78 Conclusions A complete characterization of the SiTrack algorithm was provided at three different levels: tracking performance, operating in different conditions; reconstruction of trigger signatures; definition of new trigger selection strategies; trigger selection impact on physics measurements; an example was provided. Studies on the impact of a trigger selection based on SiTrack on the ATLAS physics reach for the measurement of the m s parameter. This study showed that after a few months of operation at start-up luminosity, the 5 σ measurement limit will range between 18 and 22 ps 1, covering a significant part of the m s interval compatible with the Standard Model picture of flavour physics.