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Summary of efficiencies on ppg measurement

Summary of efficiencies on ppg measurement. TRG, TV, TCA+LIK : single track efficiency found with data efficiencies combined using MC at KINE level TRK : single track efficiency found by MC and corrected with data efficiency combined using MC at KINE level VTX , MTRK :

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Summary of efficiencies on ppg measurement

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  1. Summary of efficiencies onppg measurement • TRG, TV, TCA+LIK : • single track efficiency found with data • efficiencies combined using MC at KINE level • TRK : • single track efficiency found by MC and corrected with data • efficiency combined using MC at KINE level • VTX , MTRK : • efficiency from MC, checked with data • FILFO : • efficiency from data • geometrical acceptances (angular and Pt,Pz cuts): • efficiency from MC Marco Incagli – 23/5/03

  2. 1.1 – Trigger + Trigger Veto • The single particle TRG (and TV) efficiency is first obtained, then the information are combined using MC P0±(P1±)= probability that the p± fires 0(1) trigger sectors P0R(P1R) = prob. that the Rest of the event fires 0(1) trigger sectors PTRG = 1 - P0+ P0- P0R- P1+ P0-  P0R- (-) - (R) • To evaluate the single particle TRG efficiency events with TV on(with the hardware prescale factor 5) + 1/5th of the events with TV offto be independent from the TV • TV efficiency is evaluated on triggered events, so what we find is e(TRG)•e(TV|TRG)

  3. TRG + TV single track efficiency • To get the single particle efficiency • the track is associated to one or more clusters • the clusters are associated to trigger (TV) sectors • The first step is performed by extrapolating the TRK to the ECAL using the newextratom procedure (developed by T.S. and C.G.) and associating to TRK all clusters within a radius R=60cm • The second step is performed using the CTRG bank • A check of the dependence of the procedure from the R value has been performed

  4. 1 – TR+TV efficiency • The average efficiency starts to saturate at R60cm • The systematic error is at the 0.2 % level • A systematic error which is function of Q2 can be used

  5. TRK efficiency • Two data samples are selected: p+p-p0: 2 prompt photons with p0 mass + a track which extrapolates back to IP connected to a cluster which satisfies the pion likelihood p+p-: 1 or 2 ‘prompt’ clusters ; one is associated with a track of p=490±5 MeV which satisfies the pion likelihood • Some cuts are applied to clean up the second sample. The following categories are selected: • monotracks • two tracks of the same sign • proton stars

  6. Monotracks

  7. Monotracks • They are characterized by a deposit of energy in one or two cells • Monotracks associated to clusters with 1 or 2 cells are removed from the sample Good events monotracks

  8. Two tracks of Same Sign

  9. Two tracks of Same Sign • They are removed if the minimum distance of LH-FH is larger than 100cm • (this is done to keep inefficiencies in which the tagging track is broken into two pieces)

  10. Proton Stars

  11. Proton Stars • They are removed by cutting on the variable QTOT/Ntrk

  12. Closing kinematically the event • The momentum of the candidate track is evaluated using the f-boost from Bhabhas, the photons after imposing the p0 mass and the tagging track extrapolated at IP • When a vertex exists in the event, then it is possible to check the goodness of the above procedure • The plots show that the error is symmetric and has m0 , s6 MeV • I take bins ofDp=25MeV which seems to be safe

  13. Candidate track (TRK2) assignement • Once the event is selected the momentum components of TRK2 are evaluated(pxe,pye,pze) • All tracks of the events satisfying the cuts reported in the next transparency are compared with the tagging track • The track which minimizes the 2 defined below is the candidate track • A cut at 2<15 (it was 2<10) is applied 2distribution

  14. Definition of candidate track • A candidate track must satisfy the following cuts: • Charge must be opposite wrt tagging track • First hit must have r<50cm • The point of closest approach(PCA) of backward track extrapolation must have rPCA<8cm and |zPCA|<7cm • c2 condition must be fulfilled

  15. TRK efficiency data(p+p-p0+p+p-) vs MC(ppg) – 5slices in q btwn 40o and 90o DATA/MC MC DATA

  16. TRK efficiency • Since the ratio data/MC is rather flat I use the MC track efficiency spectrum correcting it for the following percentage: (98.59+99.27)/2 = 98.93% • The systematic error of this procedure is estimated as half the maximum difference btwn the data/MC ratio: (99.27-98.59)/2=0.34%

  17. TCA+Likelihood eff • The ratio data/MC is not flat , therefore MC cannot be used to measure TCA. This effect is expected, since TCA efficiency requires a detailed description of hadronic showers at low energy. • The TCA+LIK efficiency has been obtained by B.Valeriani by tagging the event with the p+ and looking at the p- and viceversa.

  18. TCA+LIK efficiency 50o<q<90o The single track efficiency is at the level of 98%, except for the lowest q bin which is in the intersection between BAR and ECA The OR of the likelihood has an efficiency of ~100%, while for the AND the correct combination of efficiencies must be done 40o<q<50o 50o<q<90o 40o<q<50o

  19. VTXEFF a module to select p+p-gevents • VTXEFF • A prompt photon having: • 29 < L/t < 32 cm/ns • E>20MeV ; r>100cm • Two tracks with: • opposite charge • rFH<50cm • rPCA<8cm • zPCA<7cm • Track 1 associated with a cluster which satisfies the pion likelihood

  20. The selected sample has a large bck from p+p-p0, therefore the following cuts are applied: Mass(gg)<110MeV , >160MeV (if a second prompt photon exists) cos(Dqg)>0.9 (angle btwn photon and 2p system) |DEg|<20MeV Number of events Mpp2 (GeV2)

  21. MC Data vtx efficiency vs Q2 (GeV2) vtx efficiency : (data-MC)/MC Vertex efficiency - LA • From the comparison data-MC at Large Angle, the systematics error on VTX is of the order of 1-2% • Note that LA spectrum essentially dies off at Q2=0.4GeV2 (MC), while data have a sizable fraction of p+p-p0 • More data could improve the significance of the comparison +2% -2%

  22. Vertex efficiency - SA vs LA • Small angle events are back to back in f and they are on the same side in q • This causes the different VTX efficiency for the two categories • MC is used for SA eff.; LA used as benchmark • Systematics ~2%

  23. Track Mass • The data track mass distribution has been compared with MC summing the signal + the two backgrounds ppp and mmg ; • The regions above and below Q2=0.5GeV2 have been fitted separately • .AND. of the likelihood, to suppress Bhabhas • Eg (prompt)<10MeV because of the cut in RPI stream p+p-p0 m+m-g

  24. Before the sum the following corrections have been applied:

  25. In the low Q2 region the following corrections have been applied: This procedure provides also the fraction of background events wrt signal; this value is used to scale the MC shape and to estimate the number of background events

  26. The effect of the smearing+shifting on the track mass efficiency in the region of interest (>0.35) is at the per mille level

  27. TRKMASS final efficiency efficiency Mpp2(GeV2)

  28. FILFO efficiency Q2 (GeV2)

  29. bclde (MeV) • If the QQ shape does not depend upon bclde, then:

  30. Summary of efficiencies

  31. Systematics - preliminary • TRG + TV : 0.2 % • TRK : 0.34 % • VTX : < 2 % • FILFO : < 1% • MTRK : 0.2 % (?) Systematic error dominated by VTX

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