Bunch length measurement with the luminous region Z distribution : evolution since 03/04

1. Bunch length measurement with the luminous region Z distribution : evolution since 03/04 • Origin of the discrepancies between on- and off-line : • Reminder • Comparison using 2 samples from the same runs • Comparison using 2 samples containing the same events • Differences in the selection between on- and offline B. VIAUD, C. O’Grady

2. Reminder : different results between on- and off-line Measurement with 2 samples at RF voltage = 3.2 and 3.8 MV Data type sLERsHERSz2c2 #events (3.2) #events (3.8) online 12.42±0.20 12.05±0.20 299 8.6 0.56M 1.50M offline 14.12±0.15 10.60±0.15 311 11.3 0.53M 3.30M B. VIAUD, C. O’Grady • Important variation between on- and offline. Why ?

3. Cuts on the vertex χ2 and on tan(λ1) are applied + same frame Comparison of 2 samples made of the same runs online offline <Z> = 1.10 ±0.1 mm RMS = 7.7 ±0.1 mm <Z> = 1.27 ±0.2 mm RMS = 7.8 ±0.2 mm B. VIAUD, C. O’Grady Z [mm] Z [mm] Data type Sz2c2Sz2 β*(y) c2 online 314 ±1 ~5 270 ± 2 18.4 ±0.8 ~1.5 offline 322 ±1 ~5 284 ± 3 16.3 ±0.8 ~1.5 Hardly consistent

4. Comparing 2 samples containing exactly the same events The timestamp is available both in online and offline samples: • used it to select a sample containing exactly the same events online and • offline • compared the vertex coordinates: z differs by ~50±10 μm, Δz/z <6% • => only a part of the discrepancy B. VIAUD, C. O’Grady

5. Differences in the selection… Cuts on the vertex χ2 and on tan(λ1) applied online offline Z [mm] Z [mm] B. VIAUD, C. O’Grady sqrt(x2+y2) [mm] sqrt(x2+y2) [mm]

6. Differences in the selection… Cuts on the vertex χ2 and on tan(λ1) applied offline online Z [mm] Z [mm] B. VIAUD, C. O’Grady cos(trk1-trk2) in rest frame cos(trk1-trk2) in rest frame

7. Differences in the selection: add cuts on tan(λ2), cos(trk1-trk2), sqrt(x2+y2) online offline <Z> = 1.10 ±0.1 mm RMS = 7.71 ±0.1 mm <Z> = 1.22 ±0.2 mm RMS = 7.73 ±0.2 mm B. VIAUD, C. O’Grady Z [mm] Z [mm] Data type Sz2c2Sz2 β*(y) c2 online 314±0.8 ~5 270 ± 2 18.4 ±0.8 ~1.5 offline 314±1.5 ~4 273± 4 17.9±1.2 ~1.3

8. Discrepancies between on- and off-line • Not yet completely understood • A small part is due to differences in the reconstruction • Samples built with the same runs lead to consistent results • after a few extra cuts, but: • need more statistics to conclude • -> get some other samples built with the same runs • need to reproduce, as much as possible, the same cuts in both samples B. VIAUD, C. O’Grady

9. On the way • Codes to subtract the slow and bunch number dependant z variations • Codes to fit using unbinned likelihoods • Fit in slices of z B. VIAUD, C. O’Grady

10. Measurement with 2 samples taken at RF voltage = 3.2 and 3.8 MV Data type sLERsHERSz2c2 #events (3.2) #events (3.8) online 12.42±0.20 12.05±0.20 299 8.6 0.56M 1.50M offline 14.12±0.15 10.60±0.15 311 11.3 0.53M 3.30M if we subtract the bunch number dependent Z variation offline 13.43±0.15 11.22±0.15 306 11.8 • => Important variation between on- and offline. Why ? • Large correlation between sLER and sHER ( > 99%) • too large to find precisely the individual values ? • MC-TOYs have the same correlation and work correctly. • effect of fitting a PDF which doesn’t describe the data properly ? • need more MC-TOY tests to check that. • several discrepancies observed between on- and offline : • RMS of both RF distributions 0.1 mm larger in offline data • An offset of ~1mm in Z • => Origin ? Different frames ? Something in the slow Z movement subtraction ? • Cuts ? => We’ll try the offline analysis with exactly the cut than online. B. VIAUD, C. O’Grady

11. Measurement with long coast data Data type sLERsHERSz2c2 #events online 5.6±1.4 14.7±0.6 247 1.5 140k offline 6.4±3.3 14.6±1.6 254 1.2 35k • Not enough stat. + correlations ? B. VIAUD, C. O’Grady

12. Z variation as a function of the bunch number Slow Z movement not subtracted Slow Z movement subtracted <Z> [mm] B. VIAUD, C. O’Grady Mini-trains ? Bunch number

13. Z variation as a function of the bunch numberhigh vs. low I High I Low I <Z> [mm] B. VIAUD, C. O’Grady Bunch number

14. Z-RMS variation as a function of the bunch number Z-RMS [mm] B. VIAUD, C. O’Grady 0 Bunch number 3492

15. Systematic uncertainties • Varying the parameters fixed in the fit within their • known errors and re-compute the results. • How to evaluate the uncertainty due to the fact the PDF • used in the fit doesn’t describe properly the data ? • try several PDFs (asymmetric bunches) ? • let Beta*_y float ? • use TOYs to produce distorded distributions compared to • the nominal PDF ? • ? B. VIAUD, C. O’Grady

16. New Since Last Collab Mtg

17. New Offline-Style Analysis Necessary for analyzing MC/data with same code. New (simple) cuts: • ntracks==2 • Chi2(vertex)<3 • Mass(2track)>9.5GeV • E(charged showers)<3GeV • 0.7<tan(lambda1)<2.5 Note that all our units are mm (like PEP). Also, subtract Z motion of beamspot more trivially now (new value every 10 minutes).

18. Check we see the same effect in data (from late July 2005) • => Similar effect. Similar values of the fitted parameters New Offline Analysis Code c2 ~10 c2 ~3 Z [mm] Z [mm]

19. Monte Carlo with a gaussian Z distribution • Z-distribution is generated in the mu-pair MC as a gaussian with • <Z>=0 mm and s= 8.5 mm • => No obvious effect due to the • reconstruction / selection c2 ~1.1 Z [mm]

20. Z vertex resolution from MC • 30um resolution is very small on the scale we are looking, so feels difficult for it to be a resolution effect. Z Reconstructed – Z True (mm)

21. Z-distribution/bunch length measurement as a function of bunch current • Data/theory discrepancy could be due to Beam-Beam effect proportional to the bunch current • => Compare Z-distribution at high and low current • Used data taken on July the 31st and July the 9th • LER: 2.4 A -> ~ 0.7 A • HER: 1.5 A -> ~1050 A • Selected each time the first and last runs of the period • during which the currents drop.

22. Standard fit (waists Z-position or b*(y) not allowed to float ) • No obvious difference at this statistics. When waists Z-position or b*(y) are allowed to float : Chi2 ~ 1, fitted values of Zwaist andb*(y) similar to those obtained with the usual sample. 31st of July Low current High current c2 ~1.3 c2 ~1.4 RMS=7.0 mm RMS=7.14 mm Z [mm] Z [mm]

23. Standard fit (waists Z-position or b*(y) not allowed to float ) • No obvious difference at this statistics. When waists Z-position or b*(y) are allowed to float : Chi2 reduced, fitted values of Zwaist andb*(y) ~ consistent with those we usually see. 9th of July High current Low current Low current High current c2 ~0.8 c2 ~1.6 c2 ~1.3 c2 ~1.4 RMS=7.01 mm RMS=7.2 mm RMS=7.0 mm RMS=7.14 mm Z [mm] Z [mm]

24. Conclusions • No obvious z-distribution distortion observed when analysis run on monte-carlo • With available statistics, no obvious beam-beam effects in high/low beam-current runs.

25. How do we proceed? • Analyze monte-carlo with correct hourglass shape (tried once, but hourglass in monte-carlo was not correct we believe). Unlikely cause, IMHO. • Backgrounds (tau, 2-photon)? Unlikely cause, IMHO. • Effect of parasitic crossings (now have bunch number in ntuples … so should be easy). Unlikely cause, IWHO. • Think about asymmetric bunches more • Perhaps help Ilya/Witold study at simulation? • Some machine studies?

26. Fit the following PDFon the luminous region Z distribution: Reminder I Number of particles per bunch, Zc : Z where the bunchs meet Allowed to float

27. Reminder II • The theoretical distribution cannot describe the shape of the data. • Trying to understand this before proceeding with bunch length measurement!! s ~ 7.25 mm c2 ~13 Z [mm]

28. Reminder III • 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]