1 Efficiencies and backgrounds re-evaluation ANKARA CM 2/4/2009 D.Autiero, S.Dusini

2 The re-evaluation of OPERA background and efficiencies is asked by the scientific committees who would like to know what we have learnt with one year of real data. For years we have been showing efficiencies and backgrounds estimated at the time of the proposal or during the year after the proposal submission. This work can be based on the following handles which were not available in the past: Availability of real data and possibility of measuring directly on them backgrounds and efficiencies New MC production with final geometry of the experiment, detailed simulation of the events at emulsion level with the same reconstruction as for data Possibility of validating the MC simulation with real data in order to have a credible knowledge of the variables and the effects of the cuts Improvements in the analysis: more sophisticated analysis including the merging of scanning data + electronic detector data (many things at the proposal level where estimated almost at the generator level) and taking into account the correlations among different steps. New analysis approaches with optimized cuts aiming at maximizing the sensitivity of the experiment. Multivariable likelihood approaches.

3 Going from the conservative cuts of the proposal to these last two points is possible only if we show that we have under control MC vs Data the variables used for the analysis and we can squeeze their discriminating power without creating artefacts and believing in corners of the phase-space which are not really existing in real data. In OPERA we have a factor 10 between tau interactions in the bricks and candidates selected at the end of the analysis. We should see how this could be optimized given the experience from real data. The re-evaluation implies:  New MC production with state of the art knowledge  Data ED and MC reconstruction with final version  Reconstruction of MC emulsion data with OpEmurec  Availability of emulsion data and merging with ED data by using OpEmurec In particular there are requirements on the quality and the kind of samples of emulsion data which should be made available for the analysis Goal: Timescale to complete the re-evaluation work: at latest the end of the year

4 Data availability: OpEmurec is almost in final shape. Succesful first reconstruction test down to vertex, dedicated meeting last week on first steps Alignment  Luca During after Mitzunami we got a sample event of Japanese data. An interface was built in order to put it in the standard DB format and this event has been re- reconstructed offline by Cristiano using sysal. A second event was provided last week to complete testing. Tools have been provided to Nagoya in order to handle the bricks publication. So we are also going towards the full integration of data from Japan.  Elisabetta It is a first priority job to get it interfaced also to the MC emulsion data (+ background from real data) in order to perform full MC studies as for real data  Luca The new MC production was started at CCINP23 at the time of the last PC Data reprocessing will be following  Elisabetta + Stefano

5 Bulk efficiencies: Trigger Target event selection Brick finding CS tagging Geometrical efficiency Vertex location B2B Long and Short decays

6 Trigger efficiencies: During 2008 a cut at 10 hits was left in the DAQ manager. It penalizes the tau  >e QE events. The situation has to be improved for 2009 with a smarter cut based on pulse height and relaxing the 10 hits. A special run has been taken with 4 hits threshold  factor 2 larger data flow, random coincidences with veto (affordable), timeouts of DAQ manager (being investigated)  re-evaluation with MC of trigger efficiency, optimization of cuts. (T. Brugiere) Caveat: in data there are spurious hits and x-talk not reproduced by MC, this can increase the real efficiency. Try to estimate this bias. Checks on data (also useful for other aspects of this re-evaluation): check with a sample of rock muons that the number of p.e. is well reproduced DATA/MC, check on these tracks the inefficiency: how many times there are missing hits (  Cecile final results) Implementation by Stefano in OpFilter of a package simulating for MC data the trigger conditions in DAQ and removing hits not satisfying the trigger conditions.

7 Fiducial volume selection efficiencies: This efficiency was never taken into account so far The algorithm of Alessandro/Tiem is mature now and it can be used for automatic selection on real data. It has a few per mille inefficiency on low energy NC events with respect to visual scanning. These events are at the borderline and partially doubtful  Re-evaluation with MC samples of these efficiencies with final version of the algorithm (OpCarac) Show with Data vs MC that we have under control the background from external interactions

8 Brick finding and CS tagging Getting data from second bricks to complete efficiency estimation from real data. At the moment still poor statistics of 2nd bricks (data from EU only) Last data: First bricks raw eff: 467/715 = 65.3% Second bricks raw eff: 29/65 = 44.6% Removal of interactions in dead materials % = 688  1st brick corrected eff: 467/688 / (1 -6.8%) = 72.8% (72% MC) Correlation with 2 nd brick: Unfound raw after first brick (100% %) Unfound related to BF inefficiency (100% %) foundable in 2 nd brick  Second brick corrected eff: = 29/65 * (100 – 65.3) / ( ) = 56.9% 1st brick BF eff = 72.8% % 2 nd brick BF eff = 56.9% % Total efficiency 1st + 2nd: 72.8% + (100% %)*56.9% = 88.3 % +- 5% (80% MC) Still too large uncertainty on 2 nd bricks

9 Comments and warnings: 1)Predictions were made time ago for these events. Taking the latest version of the reconstruction for about 1/3 (9 events) now the brick is predicted directly as first brick, reconstruction problems fixed 2)For 8 events the second brick suffers from the underestimation of tracking errors. This has to be fixed in order to predict correctly the lateral probability 3) For 8 events the second brick was in another wall with large probability (30-40%), this looks higher (~ a factor 2) than on average prediction for second bricks. It is a fluctuation in this first sample 4)Too few NC  We need a larger sample to draw some more solid conclusions We should get a large sample from the last couple of weeks of extractions

10  We should have a clearer view with the increase in statistics of the last weeks (gather all possible second brick results, also from Japan)  Re-evaluation of last version of the reconstruction on all events  A deeper comparison per events categories is needed (QE,NC,CC, electromagnetic-like)  So far the algorithms have been kept untouched, the main work has been concerning the debugging of the reconstruction. On the basis of these results it will be possible to have a second version  BF efficiency was optimized for tau events (the efficiency is about 5% larger than for standard numu NC or CC events), in order to check it we should look for events which are tau like CC QE and with low energy muons, events with dominant electromagnetic activity, like tau  e and tau  rho.  First priority: increase the efficiency as much as possible, There are ideas about that on the side of BF and also on the possibility of concentrating the efforts on a tau signal enriched sample. We should first advance with the analysis of the event sample and understand why it goes wrong (reconstruction, 2nd bricks, …)

11 Integrate in the simulation the CS tagging absent in the past: acceptance effect with respect to the total surface behind the bricks (7.4% uncovered area) + CS base track efficiencies measured from real data, implement also the 3/4)  Complete efficiency evaluation from real data (convolution of BF + CS)  Evaluate CS tagging efficiency from full MC (including the CS intrinsic efficiency as a function of the angle measured in real data, provided by Giovanni for base tracks) Re-evaluation campaign (brick finding CS tagging part):

12  Better errors evaluation in tracking, important for probability maps  Re-evaluate MC BF efficiency per categories of event including the interplay of CS tagging efficiency, compare to data per categories of events: DIS, QE, NC, NC with e.m. component.  Possible tau enriched sample to maximize the efficiency  Estimate possible bias of CS tagging inefficiency (~ 25%) on muon matching: are all muons found at the vertex even if not followed by scan-back ? even a residual inefficiency of 2% could change a lot the charm background.

13 Geometrical efficiency At the proposal level it was simply assumed that 1mm along the border was inefficient at the level of emulsion scanning a 3.6% loss. Giovanni thinks that the dimension of the inefficient region is actually reasonably close to 0.5 mm. We have also to take into account the fact that the lead plates seem to have a different geometry with respect to the nominal one: g/plate vs g/plates (nominal) a loss of 3.3%. Where is the missing mass ? The reduction in surface of the plates ( x vs 125.5x100: -1.16%) does not justify the effect. In The MC prod we applied also a thickness reduction of 20 microns (Stefano)  we have concluded at the last PC meeting that the thickness reduction of 20 microns was real (BAM and lead production presentations)  update also the target mass and number of interactions (in progress)  evaluate with the full MC the real loss of efficiency for events at the borders (need to include in MC final lead geometry) Emulsion dimensions x 99.0

14 B2B connection Now we should have experience from real data. The statistics is still poor, in Europe we have 32 events with frontal connection, very few events with lateral connection  re-evaluate with full MC  increase statistics with data measurement

15 Vertex localization (Giovanni) This is another point where people expect some experience return from real data. At the moment the statistics is poor and can provide just a range for the efficiency: CC: 84-94% NC: 71-92% The lower limit of the range is computed assuming that the actually pending events are not localized.  Improve the statistics with data  Launch the evaluation of efficiency (quite relevant for NC like) with full MC by performing detailed reconstruction  Study of multiplicity distributions at the primary  How to prove that we understand the efficiency for events with electromagnetic showers  How to proove that we understand the efficiency for secondary vertices ? Try a K0s sample with one track detected in CS, rates well known

16  How to prove that we understand the efficiency for NC events Fake NC removing the muon  How to prove that we understand the efficiency for events with electromagnetic showers  How to proove that we understand the efficiency for secondary vertices ? Try a K0s sample with one track detected in CS, rates well known CS Tagging in the CS of known showers from photon conversions

17 Beam angle Slope zx Slope zy Tracks at large angle File provided by Giovanni with 196 vertices, 166 CC Tracks slopes at primary vertex for CC events

18 Track multiplicity at primary vertex for numu cc Single track events 24% Expected contribution from QE+RES 10%  To be quantified losses of tracks for DIS (efficiency for large angles, range for soft particles)

19 Muon slope in xz plane Data MC

20

21 Muliplicity at primary vertex Data MC QE+RES (10%) not included but taken into account in normalization Protons <300 MeV/c (mainly from nuclear rescattering removed)

22

23 All tracks slope in zx plane Data MC Angular efficiency

24 Distributions already spoiled by deficit of tracks seen at the multiplicity level