1 Bunch length measurement with BaBar SVT B. VIAUD B. VIAUD Université de Montréal Université de Montréal

2Aim Extracting LER and HER bunch lengths Extracting LER and HER bunch lengths from luminous region data from luminous region data Compare with recent measurements done at PEP Compare with recent measurements done at PEP

3 Principle Fit the theoretical distribution of the Z of the e + e - collision Fit the theoretical distribution of the Z of the e + e - collision to data taken before and after a RF voltage change from 3.2 MV to 3.8 MV Number of particles per bunch, Z c : Z where the bunchs meet

4 Principle (II) Simultaneous fit of the 2 distributions measured before and after RF voltage change : Simultaneous fit of the 2 distributions measured before and after RF voltage change : One   per distribution : fit and to minimise One   per distribution : fit and to minimise Use the following constraint : Use the following constraint :  ~ 7.6 mm  ~ 7.2 mm 3.2 MV 3.8 MV Z [mm]

5 Z collision variations Z c variations in the sample taken at 3.8 MV Z c variations in the sample taken at 3.8 MV June 11 time mm => Use only this region in the fit

6 TOY MC A TOY Monte Carlo has been written to validate the method. A TOY Monte Carlo has been written to validate the method. Generated distributions with Generated distributions with Perform the fit, obtain : Perform the fit, obtain : avec    => Seems to work => 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

7 Fit to the data with    => Does not match the data. => Does not match the data. Z [mm] 3.8 MV

8 Theoretical shape vs Data shape Fit the 2 individual distributions by fixing Fit the 2 individual distributions by fixing  Check that the theoretical distribution can describe the shape of the data the data The data have not the same shape as the theoretical formula! The data have not the same shape as the theoretical formula! 3.2 MV  ~ 7.6 mm 3.8 MV  ~ 7.2 mm   ~11   ~3.5 Z [mm]

9 Theory data discrepancy What can be the source of this discrepancy ? What can be the source of this discrepancy ? Z position of the magnetic waist different between LER and HER ? Z position of the magnetic waist different between LER and HER ? Acceptance / resolution effects ? Acceptance / resolution effects ? … …

10 Fit the 2 individual distributions by fixing Fit the 2 individual distributions by fixing Let and free in the fit Let and free in the fit Z [mm] Z position of the magnetic waist ? 3.2 MV  ~ 7.6 mm   ~ MV  ~ 7.2 mm   ~1.1 Z [mm]

11 Z position of the magnetic waist ? What can be the source of this discrepancy ? What can be the source of this discrepancy ? Z position of the magnetic waist different between LER and HER ? Z position of the magnetic waist different between LER and HER ? Acceptance / resolution effects ? Acceptance / resolution effects ? … …

12 Z Position of the magnetic waists (II) Indications in the data ? Z and Z RMS variation as a function of the bunch number Bunch number Z [mm] RMS Z [mm] Data 3.8 MV (Region used in the fit) Z [mm] RMS Z [mm] Data 3.2 MV Bunch number

13 Z Position of the magnetic waists (III) Z c [mm] RMS Z [mm] Data 3.2 MV RMS Z [mm] Z c [mm] theory Zw (mm)=-3 (ler); 3(her) -2 ; 2 -1 ; 1 0 ; 0

14 Z Position of the magnetic waists (IV) Z c [mm] RMS Z [mm] Data 3.2 MV

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

16 Acceptance effects (II) ? Bunch number Data 3.8 MV (Region used in the fit) Z [mm] RMS Z [mm] Data 3.2 MV Bunch number Z [mm] RMS Z [mm]

17 Conclusion What’s wrong ?What’s wrong ? Did not take into account the Z variation as a function of the bunch number. Did not take into account the Z variation as a function of the bunch number. => One of the next steps. But when fitting in a restricted region => One of the next steps. But when fitting in a restricted region ( small variation of Z and Z RMS ), still doesn’t work. ( small variation of Z and Z RMS ), still doesn’t work. Both HER and LER waists are choosen at the same position. Both HER and LER waists are choosen at the same position. => Tried to let them as free parameters in the fit :   improved, but => Tried to let them as free parameters in the fit :   improved, but unreasonable waist positions are found, and reduced to ~10.5 mm unreasonable waist positions are found, and reduced to ~10.5 mm Measurement bias ? Bug ? Measurement bias ? Bug ? ?? ??

18 Observation 4 : Z vs bucket number Studied Z centroid dependance wrt the bunch numberStudied Z centroid dependance wrt the bunch number | | | Bucket Number Abort Gap

19 Number of 2-prong events as a function of bucket number | | | Bucket Number Number of 2-prong events

20 X,Y,Z shapes 18 Use 113k events (smooth distributions with small statistical uncertainty on the shape) Use 113k events (smooth distributions with small statistical uncertainty on the shape) Equivalent to 10 days : must remove the actual movement of the beam Equivalent to 10 days : must remove the actual movement of the beam  Divide into 125 events sample, calculate mean for each sample, subtract this mean to each event of the sample. each event of the sample.       X [mm] Y [mm]

21 Beamspot from Bhabhas and  Aim : providing each 10 minutes a measurement of the centroids, sizes and X-Z tilt of the interaction region centroids, sizes and X-Z tilt of the interaction region => Need to get online a sample of well reconstructed primary vertices => 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 and perform tracking using 28 executables on 8 dual processor nodes tracks reconstructed using DCH and SVT 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) centroids calculated in the SVT frame (attached to the beam pipe) All our results are obtained in that frame (not in MCC frame) All our results are obtained in that frame (not in MCC frame) Accumulate samples of ~1250 vertices between 2 updates Accumulate samples of ~1250 vertices between 2 updates ( 10 minutes of data taking ). Interaction region seen as the (X,Y,Z) ( 10 minutes of data taking ). Interaction region seen as the (X,Y,Z) distribution of primary vertices distribution of primary vertices Results made available both in EPICS and in the AmbientDataBase Results made available both in EPICS and in the AmbientDataBase

22 Augmentation de la statistique Un exemple important d’amélioration : Un exemple important d’amélioration : longueur de la zone d’interaction en fonction longueur de la zone d’interaction en fonction du voltage RF : du voltage RF : 0.2 mm 0.05 mm 27 mars temps 6 avril7 juin temps 12 juin  Z mm

23 Application aux données Z [mm]