Impact Parameter Resolution Measurements from 900 GeV LHC DATA

1. Impact Parameter Resolution Measurements from 900 GeV LHC DATA Boris Mangano & Ryan Kelley (UCSD)

2. Outline • Samples and Event selection. • Description of the method. • Validation of the method on MC samples. • Measurement of Transverse and Longitudinal Impact Parameter resolutions on 900 GeV DATA.

3. Samples and Event Selection DATA: /MinimumBias/BeamCommissioning09-BSCNOBEAMHALO-Dec19thSkim_336p3_v1/RAW-RECO MC: /MinBias/Summer09-STARTUP3X_V8K_900GeV-v1/GEN-SIM-RECO • Event Selection (see backup slides): • BSC trigger and BH Veto (already applied at the level of the central skim) • Tech.Trigger bit 0 • PhysicsDeclared bit • NoScrapingEvent filter • Only B=3.8 T runs • Only E=900 GeV runs

4. Tk1 Tk2 d01 PV Tk1 is from decay-in-flight. Its d01, wrt the Primary Vertex, is genuinely ≠0. Tk2 is a prompt track. Its d02 is exactly = 0. Tk1 Tk2 reco PV true PV Preliminary Remarks Different Components affecting the IP measurement Case 1) Exactly known trajectories and perfectly known collision point (SimTracks and SimVertex) Case 2) Exactly known trajectories, but measured collision point (SimTracks and reco PV) Both Tk1 and Tk2 have d0 different from their true values because of the “smearing” due to the vertex position resolution d0 = d0true “vertex smearing”

5. Preliminary Remarks Different Components affecting the IP measurement Case 3) Both trajectories and collision point are not exactly know because they are both measured = Real World reco Tk1 Tk1 reco Tk2 Tk2 reco PV Both Tk1 and Tk2 have d0 different from their true values because of the “smearing” due to the vertex position resolution and the smearing due to the finite resolution on the track parameters d0meas = d0true “vertex smearing”  “track impact parameter resolution”

6. Preliminary Remarks Different Components affecting the IP measurement d0meas = d0true “vertex smearing”  “track impact parameter resolution” The agreement between the resolutions of the primary vertex position measurements in DATA and MC has already been proved by Y.Gao, F.Fiori et al. https://twiki.cern.ch/twiki/bin/view/CMS/PrimaryVertexResolution In the rest of the talk, focusing on the effect of vertex resolution on the IP measurement: “vertex smearing” Final observable measured by this analysis

7. Description of the method 1) Select only events with the primary vertex fitted from 10-16 tracks (see next). 2) For a given track with measurements on 8 Tracker layer (2 pixels), refit the primary vertex using all the other tracks in the event. 3) For the same track, evaluate d0 and dz w.r.t. the refitted vertex position. 4) Repeat 2-3 for all the other tracks in the event that pass the selection. 5) Save the previously evaluated d0 and dz values in bins of track’s pT and eta. 7) Repeat 2-5 for all the selected events.

8. Description of the method (II) 8) Fit each pT and eta bin using the function F = VertexSmearingFunction  IP ResolutionFunction Measured d0 wrt recoPV [m] Vertex “smearing” pdf [m] Impact parameter resolution [m] Measured from data Estimated from MC Extracted from the Fit of the convolution function F

9. --- narrower gaussian --- wider gaussian --- 2 gaussian sum = VertexSmearing pdf Tk1 Tk2 Vertex “smearing” pdf [m] reco PV true PV Evaluation of the VertexSmearing function The d0 and dz of simulated SimTracks were evaluated with respect to the reconstructed PV position on the MC sample. The d0 and dz calculated in this way were put in separate histograms for distinct SimTrack’s pT and eta values. Each bin is fitted by a 2-gaussian sum function.

10. Evaluation of the VertexSmearing function Vertex smearing for d0 as a function of the track’s eta Vertex smearing for d0 as a function of the track’s pT Vertex smearing pdf  [m] Track’s pT [GeV/c] Track’s eta Vertex smearing for dz as a function of the track’s pT Vertex smearing for dz as a function of the track’s eta Vertex smearing pdf  [m] Track’s pT [GeV/c] Track’s eta

11. Measured d0 wrt recoPV [m] Evaluation of the Impact Parameter Resolution F = VertexSmearingFunction  IP ResolutionFunction Data are fit using the convolution function F, where only the parameters of the “IP ResolutionFunction” (a single gaussian) are unconstraint. Vertex “smearing” pdf [m] • The use of a single gaussian for modeling the resolution function is appropriate if: • The pT and eta of the tracks contributing to the same histogram are sufficiently “close”. • Only the core of the distribution is considered (2sigma fit)

12. Validation of the method on MC Transverse Impact Parameter Resolution Additional Track cut: |eta| < 0.4 Good agreement between the “measured” resolutions (red) and the mc-truth-determined resolutions (black).

13. Validation of the method on MC Transverse Impact Parameter Resolution Track selection: 0.75 < |pT| < 0.85 (GeV) Track selection: 1.0 < |pT| < 1.4 (GeV)

14. Validation of the method on MC Longitudinal Impact Parameter Resolution Track selection: 0.75 < |pT| < 0.85 (GeV) Track selection: 1.0 < |pT| < 1.4 (GeV)

15. Results from 900 GeV DATA Track cut: |eta| < 0.4

16. Results from 900 GeV DATA Track selection: 0.75 < |pT| < 0.85 (GeV) Track selection: 1.0 < |pT| < 1.4 (GeV)

17. Results from 900 GeV DATA Track cut: |eta| < 0.4

18. Results from 900 GeV DATA Track selection: 0.75 < |pT| < 0.85 (GeV) Track selection: 1.0 < |pT| < 1.4 (GeV)

19. Conclusions Method to estimate the Track Impact Parameter Resolution from DATA has been implemented and described in this talk. The Method has been successfully validated on MC and used on 900 GeV DATA from December 2009 runs. Results based on 900 GeV DATA are very close to values expected from STARTUPMC. Impact Parameter resolutions are just slightly worse. Overall, the analysis will benefit from higher LHC energy events for which there are more high pT tracks from the collision and the uncertainty on the primary vertex position is smaller. TWIKI page and Analysis Note in preparation: https://twiki.cern.ch/twiki/bin/viewauth/CMS/ImpactParameterResolutionDec2009

20. BACKUP SLIDES

21. Event Selection for DATA (and that you don’t usually apply on a MC sample) Require Tech.Trigger bit 0 (i.e. BPTX coincidence): it selects events in beam-beam bunch crossings. Discards single-beam BXs and empty BXs. Require Tech.Trigger bit 40 or 41 (i.e. BSC triggers): selects events with activity compatible with a collision Veto on Tech.Trigger bit 36-39 (BeamHalo triggers)

22. Event Selection for DATA (II) (and that you don’t usually apply on a MC sample) Discard events for which B!=3.8, e.g. events collected during the magnet ramping to its nominal value. 4’) For this study only, discard events from 2.36 TeV runs Discarded runs: 123967-123997, 124119,124120,124275 5) Require PhysicsDeclared bit: this bit is set to TRUE when all the CMS components are declared OK for data taking: e.g. all the HighVoltages of the Tracker sensors are ON.

23. Event Selection for DATA (III) (and that you don’t usually apply on a MC sample) 6) Reject beam-background events (AKA pixel monster events, AKA scraping event). The NoScraping event filter has been used: it requires >25% of tracks in the event to be “highPurity” tracks.

24. Validation of the method on MC Longitudinal Impact Parameter Resolution Track selection: |eta| < 0.4 Some bins looks problematic

25. Validation of the method on MC Longitudinal Impact Parameter Resolution After smoothing of the response function, the final fit is more stable There are less “problematic” bins

26. Effect of the resolution on the Primary Vertex position 1) Are the reconstructed primary vertices of the MC (used to estimate the response function) consistent with DATA? From Y.Gao: https://twiki.cern.ch/twiki/bin/view/CMS/PrimaryVertexResolution 2) Anyway, how much the Impact Parameter Resolution measurement is sensitive to the vertex smearing? See next slides..