Extracting LER and HER bunch lengths from luminous region, using BaBar data

1. Extracting LER and HER bunch lengths from luminous region, using BaBar data B. VIAUD, C. O’Grady U. Montréal, SLAC With the great help of Witold Kozanecki !

2. Overview • Fit the Z-distribution • Z-distribution width behavior versus bunch number • Acceptance and resolution effects study • Conclusion

3. Fit the theoretical distribution of the Z of the e+ e- collisions Z Distribution Formula Number of particles per bunch, Zc : Z where the bunchs meet Allowed to float

4. 2.5 Million events: Bhabha and mumu • Tried to select periods where Zc is ~ constant: 0.7mm peak to peak • (have studied this with Toy Monte-Carlo by moving Zc 4mm) Data Sample <Z> mm June 10th time june 27th

5. Fit of the measured Z distribution • Check the theoretical distribution can describe the shape of the data. • The data have not the same shape as the theoretical formula! Changing does not improve the agreement. (The c2 minimum depends only on ) s ~ 7.25 mm c2 ~13 Z [mm]

6. Fit of the measured Z distribution • Better data/theory agreement if the waists Z-position or b*(y) are allowed to float in the fit • Waists Z positions / b*(y) values seem unlikely ! • Are they real ? Which other effect could simulate this lack of focalisation ?? c2 ~2.2 c2 ~2.4 Z [mm] Z [mm]

7. Fit with a bunch longitudinal asymmetry • Better data/theory agreement with the following PDF : • when Zc , the waists Z-position ( common to HER and LER ) and the asymmetry factor A are allowed to float in the fit. Still strange waists. • Real ? c2 ~3.1

8. Z and Z RMS variation as a function of the bunch number Z [mm] RMS Z [mm] 0 3492 Bunch number

9. Z and Z RMS variation as a function of the bunch number • Origin of Z-RMS variation? Possible reasons: • Zc moving (around the waist) with bucket number: Studied this, by itself it can’t explain the observed RMS behaviour. • Bucket dependent bunch lengths (not studied yet) • These (Zc motion and RMS variation) could mess up the fit! • Fit with only buckets in 0.5us of the turn. Same answers: • Toy Monte-Carlo also excludes Zc/RMS motion as cause of discrepencey

10. Resolution / acceptance effects • Resolution and acceptance depend on the angle between the e (μ) and the Z axis: • => Select a zone where the resolution is constant and • where the acceptance as a function of Z is constant • (Don’t understand Data/MC disagreement: mumu(MC) vs. Bhabha(Data)?) Data MC < Z> [mm] <Z> [mm] tan(λ1) tan(λ1)

11. Resolution / acceptance effects • Fit of the Z distribution afer tan(λ1) cut • fixed waists Z position and Beta functions : • data/theory discrepancy still important : χ2 = 15 • floating waists Z position • floating Beta functions c2 ~1.6 Z [mm]

12. Discrepancy between data and theory in Z distribution. Big, on scale of SVT resolution (~100mm). • One effect mimics a lack of focalisation (important!) in the data: • correct description of the data by the fit if the waists are very distant, • or if the b*(y) are 50% higher than expected • Or if we use a PDF accounting for a longitudinal bunch asymmetry • Variation of Z-distribution RMS as a function of the bunch number : not understood • not due to the variation of Zc around Z-waist • TOY MC studies show this effect cannot mess up the fit • At first order, does not seem to be due to a resolution/acceptance effect • One of our next main steps will be to use a complete MC simulation to evaluate precisely the bias introduced by the reconstruction and selection. • Ideas ? Suggestions ? Conclusion

13. TOY MC studies • Can the Zc and Z-RMS variations mimic a lack of focalisation and/or mess up the fit enough to obtain • ?? • Performed a TOY MC study to check the effects of Zc and Z-RMS variations on the results of the fit • Generate two samples, with both waists at Z=0, Beta functions at 10.5 mm, and: • ADD the two samples and fit Zc and Z RMS variations can’t explain the waists’ Z position and Beta functions results

14. Performed a TOY MC study to check the effects of Zc and Z-RMS variations on the results of the fit • Generate two samples, with both waists at Z=0, Beta functions at 10.5 mm, and: • Gather the two samples and fit • Floating Z-waists: • Floating Beta*: TOY MC studies (II)

15. Performed a TOY MC study to check the effects of Zc and Z-RMS variations on the results of the fit • Generate two samples, with both waists at Z=0, Beta functions at 10.5 mm, and: • Gather the two samples and fit • Floating Z-waists: • Floating Beta*: TOY MC studies (III) Zc and Z RMS variations can’t explain the waists’ Z and Beta functions results

16. Z RMS wrt the bunch number: theory prediction • Study directly Zc, given by the fit, with Z-waists fixed at 0 mm and (-2,2) mm • With the values of Zc and of the bunch length ( XX mm ) found by the fit on the global sample, use the theoretical formula to find the theoretical RMS (green dots) Zc [mm] Zc [mm] Z waists at (0,0) mm Z waists at (-2,2) mm RMS Z [mm] RMS Z [mm] 0 3492 Bunch number 0 3492 Bunch number

17. Z RMS wrt the bunch number: theory prediction • Best case: Z-waists fixed at (+2.5,+2.5) mm Zc [mm] Z-RMS [mm] | | 0 3492 Bunch number

18. Z RMS wrt the bunch number: only theory prediction RMS Z [mm] RMS Z [mm] Theory Data (Z0,HER;Z0,LER) = (0;0),(-2;2),(-5;5) ,(-10;10) mm Zc [mm] Zc [mm] Z-RMS variation wrt bunch number can’t be explained by the variation of Zc around the waists.  We can’t use this variation to find the waists Z-position.

19. Z RMS wrt the bunch number: theory prediction • Z-waists fixed at (-5,5) mm and (-10,10) mm Zc [mm] Zc [mm] RMS Z [mm] RMS Z [mm] 0 3492 Bunch number 0 3492 Bunch number

20. Z RMS wrt the bunch number: theory prediction • Z-waists fixed at (0,0) mm, after the tan(λ1) cut Zc [mm] Z RMS variation is not an acceptance effect. Z-RMS [mm] | | 0 3492 Bunch number

21. Simultaneous fit of the 2 distributions measured before and after RF voltage change : • One c2 per distribution : fit and to minimise • Use the following constraint : Reminder: principles (II) 3.8 MV 3.2 MV s ~ 7.2 mm s ~ 7.6 mm -30 0 30 -30 0 30 Z [mm] Z [mm]

22. Reminder: TOY MC • A TOY Monte Carlo has been written to validate the method. • Generated distributions with • Perform the fit, obtain : • avec c2 = 1.15 • => Seems to work HER (x/y) 32.2 / 10.6 mm 30 / 1.05 nm LER (x/y) 32.2 / 10.6 mm 31.3 / 10.3 nm

23. Reminder: Fit to the data • with c2 = 14 !! • => Does not match the data. 3.8 MV Z [mm]

24. first step : looked at Z vs cos(theta) Resolution effects Z [mm] Cos(theta)

25. Beamspot from Bhabhas and mm • Aim : providing each 10 minutes a measurement of the • centroids, sizes and X-Z tilt of the interaction region • => Need to get online a sample of well reconstructed primary vertices • Take events from 28 ( out of 30 ) L3 executables (via the trickle stream ), and perform tracking using 28 executables on 8 dual processor nodes • tracks reconstructed using DCH and SVT • Select two-prong events • Reconstruct the two tracks common vertex • centroids calculated in the SVT frame (attached to the beam pipe) • All our results are obtained in that frame (not in MCC frame) • Accumulate samples of ~5000 vertices between 2 updates • ( 10 minutes of data taking ). Interaction region seen as the (X,Y,Z) • distribution of primary vertices • Results made available both in EPICS and in the AmbientDataBase

26. Sensitivity to RF voltage modifications s Z mm 0.05 mm June 7th temps june 12th

27. Cuts used to select two-prong events • See TrkOprMon/TrkTwoProngSelector.cc • Take the list of reconstructed tracks TrkSelTracks • Select the 2 tracks with the highest |p| • For these 2 tracks, calculate docaXY, docaZ, tanDip, and x,y,z position at POCA • Reconstruct the difference between the 2 Z at poca, and deltado (seem to be impact param of one track wrt the other, check) • Reconstruct the boost of the current event, from the sum of the above momenta: magnitude of the boost and x,y slopes • Go to the frame which Z axis is parallel to the boost, and reconstruct the diff between the PT (the same than in CMS), the difference between the phi in this new frame, the Delta D (see later the def) • Boost to CMS, reco angle between tracks, diff in |p|, inv Mass.