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Summary of the Emulsion Reconstruction WG P. Migliozzi S. Aoki, L. Arrabito, A. Badertscher, M. Besnier, C. Bozza, E. Carrara, M. Cozzi, G. De Lellis,

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Presentation on theme: "Summary of the Emulsion Reconstruction WG P. Migliozzi S. Aoki, L. Arrabito, A. Badertscher, M. Besnier, C. Bozza, E. Carrara, M. Cozzi, G. De Lellis,"— Presentation transcript:

1 Summary of the Emulsion Reconstruction WG P. Migliozzi S. Aoki, L. Arrabito, A. Badertscher, M. Besnier, C. Bozza, E. Carrara, M. Cozzi, G. De Lellis, M. De Serio, F. Di Capua, L. S. Esposito, T. Fukuda, M. Guler, F. Juget, K. Kodama, M. Komatsu, J. Knuesel, I. Kreslo, I. Laktineh, A. Longhin, G. Lutter, K. Mannai, A. Marotta, F. Meisel, P. Migliozzi, A. Pastore, L. Patrizii, C. Pistillo, L. Scotto Lavina, G. Sirri, T. Strauss, V. Tioukov, A. Zghiche

2 Tracking in an ECC (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche) Vertex location as a function of the event classification (L. Arrabito, C. Bozza, M. De Serio, I. Kreslo, A. Marotta, Y. Nonoyama, C. Pistillo, C. Sirignano) Volume scan, vertex reconstruction and decay selection based on topological criteria (M. Besnier, C. Bozza, F. Di Capua, T. Fukuda, K. Kodama, M. Komatsu, I. Kreslo, A. Marotta, Y. Nonoyama, A. Pastore, C. Pistillo, L. Scotto Lavina, C. Sirignano, V. Tioukov, A. Zghiche) Brick to brick connection (E. Carrara, M. Komatsu, A. Longhin); Momentum measurement by MCS criteria (M. Besnier, C. Bozza, M. Komatsu, C. Sirignano, A. Zghiche) e/pi separation and energy measurement (S. Aoki, F. Juget, F. Meisel); p/pi and pi/mu separation (S. Aoki, T. Fukuda, I. Kreslo, I. Laktineh, K. Mannai, C. Pistillo); Post-scanning 1mu/0mu classification (Y. Nonoyama); Kinematical decay selection criteria (C. Bozza, A. Marotta, Y. Nonoyama, C. Sirignano) List of activities

3 Now available on the wiki page)

4 Brick finding Trigger Vertex location Decay search long or short decays decay mode Kinematics events Classify as / e yes no Electronic detectors Emulsions Electronic detectors e at 1ry vtx ?

5 Vertex location

6 Preliminary results for the the -> DIS and -> QE channels -> DIS LONG trigger in emulsione = 95% conferma del trigger = 99% scanback = 96% identificazione topologia = 94% idLONG = 92% idSHORT-LIKE = 8% SHORT trigger in emulsione = 93% conferma del trigger = 98% scanback = 91% identificazione topologia = 98% -> QE LONG trigger in emulsione = 84% conferma del trigger = 99.9% scanback = 97.7% identificazione topologia = 95.6% idLONG = 83% idSHORT-LIKE = 17% SHORT trigger in emulsione = 82% conferma del trigger = 99% scanback = 62% identificazione topologia = 98.9%

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8 A proposal for 0 primary vertex location Cristiano Bozza Salerno Emulsion Group Phys. Coord. May 2007

9 Types of NC-like events X h e-e- X h h h e-e- production, decay to h production, decay to e (shower likely) NC showerless NC with shower 1) 2) 3) 4)

10 Main problems of 0- h e-e- h stop in brick 1) TT prediction cannot define a precise slope/position pair reduced filtering function of CS 2) Many tracks can be found in CS (mostly type 2 and 4) scanback takes time with many paths 3) Scanback paths are likely to lead to 2ry vertices; sizable probability of not finding 1ry vertex by direct scanback However, what we can do with a brick is Scanback + Volume Scan Solution should be found there

11 Further considerations Scanning load cannot be increased too much Lead ECC is a relatively dense material – EM 2ry interactions should be near to the 1ry (X 0 =0.56 cm 4 cells, 9/7X 0 =0.72 cm 6 cells) Track multiplicity is very high in showers, but low momentum e + /e - are strongly scattered and travel a short length Scanback is efficient in finding interaction points quickly

12 Strategy – Step 1 CS Scanning Search for base-track pairs on CS (no 3-out-of-4) S CS = slope difference between base tracks S CS < 0.015 Rank tracks with S CS and select the first N pCS = 300 Goal of step 1: discard low momentum tracks as soon as possible

13 Strategy – Step 2 CS – Target connection Project CS pairs to first two plates of target using most upstream pos/slope A CST = area to be searched 500 500 m 2 S CST = 0.040 (CS-brick misalignments possible) Pick up all candidates for each track Goal of step 2: minimize track losses (scattering should be small)

14 Strategy – Step 3 Scanback Follow scanback paths with the same parameters as for in CC Many scanback paths with low momentum are lost very soon (hard SB parameters) S SB = 0.020 P SB = 80 m Max missing plates N mpSB = 5 plates Goal of step 3: follow tracks with high momentum as upstream as possible, and discard low momentum tracks quickly

15 Strategy – Step 4 TotalScan/NetScan Choose the N V = 10 paths stopped most upstream (except passing-through paths) TotalScan around most upstream stopping points Use latest direction to search for 1ry vertex – skewed volumes Volume width grows upstream (A S = slope acceptance 0.4) Correlation between 1ry vertex position and products of 2ry interactions Goal of step 4: limit complexity of scanning procedure despite of a small increase in scanning load NuNu NdNd Catch conversions and charm decays: N u = 10

16 Scanning load and data size Step 1: 240 cm 2 ×2 sides = 480 cm 2 Scanning time for both CS = 24 h (at 20 cm 2 /h/side) (lower if prediction scan is used) Data size = 60 MB for 10 5 tracks in each CS Step 2: 0.75 cm 2 ×2 sides = 1.5 cm 2 Scanning time = 4min30s (at 20 cm 2 /h/side) Data size = negligible Step 3: 300 predictions×57 plates Scanning time = 5h42min (at 1.2s/track) Data size < 5 GB Step 4: 115 cm 2 ×2 sides Scanning time = 11h30min (at 20 cm 2 /h/side) Data size < 5 GB Total: 41h/brick, < 10 GB/brick

17 Conclusions The procedure should be able to fulfill several conflicting goals Efficiency should be estimated If 1ry vertex is not found, event interpretation is affected estimate resulting background Scanning load and data size acceptable Many parameters can be optimized work for MC experts!

18 Comments The vertex location for events with a muon in the final state works very well (despite of the low base track efficiency, the usage of micro-tracks helps) The situation for 0mu-like events is more difficult. More efforts are needed if we want to be ready by September We should review this item by mid of July

19 Vertex Reconstruction L. Arrabito, M. Besnier, C. Bozza, A. Pastore, L. Scotto Lavina, V. Tioukov

20 Summary Goal : - Analysis of vertex reconstruction of CC neutrino interactions Data set: - Monte Carlo simulation of 3000 CC events generated by OpRoot-ORFEOv7 Properties: - Monte Carlo data (TreeMSE) with smearing and efficiency correction ( eff = 0.944 – 0.216 * – 0.767 * 2 +1.856 * 3 Analysis: - Tracking and Vertexing performed by Fedra (Similar results have been obtained by using the AlfaOmega framework)

21 Interactions inside the OPERA brick Z (cm) Y ( cm ) X (cm) energy spectrum of interacting - 3000 CC events - CNGS energy spectrum Analysed data sample

22 CC interaction

23 Neutrino interaction vertex is at the center of the fiducial volume P0P0 +1+2+3+4+5-2-3-4-5 muon Volume size : 25 mm 2 * 11 plates P 0 = first emulsion sheet containing the neutrino-associated ( X 0, Y 0 ) = position at Z P 0 (X 0,Y 0 ) Pb plate Emuls. film Fiducial volume

24 MC truth vs MC reconstructed vertices MC truth primary vertex primary tracks secondary tracks MC rec reconstructed primary vertex reconstructed primary tracks secondary track wrongly attached to the vertex

25 x = 0.34 m y = 0.37 m z = 2.77 m MC truth vs MC reconstructed vertices: vertex position

26 1) Study of CC N f <1% z =8.9µm xy = 1.1µm

27 MC truth MC rec p p + + - - e+e-e+e- e+e-e+e- MC truth vs MC reconstructed vertices: interaction products

28 hadrons e +,e - secondary tracks wrongly attached to the neutrino vertex tracks really belonging to the neutrino vertex dz < 1300 m 97 % signal selecteddz < 1300 m 23 % of wrong tracks survive MC truth vs MC reconstructed vertices: interaction products

29 Generated interactions3000 Track Reconstruction (n primary tracks) n = 0 64 (2.2 ± 0.3)% n = 1 583 (19.5 ± 0.7)% n 2 2353 (78.4 ± 0.8)% Multi-prong vertex successfully reconstructed 2541 (86.5 ± 0.6)% Vertex detection efficiency Purity (all tracks attached to the vertex are primary)> 99 %

30 (tracking) ~ 100% for P>1GeV, drastically decreases below 1 GeV (vertexing) ~ 95% for P>2GeV, drastically decreases below 1 GeV 50% of generated tracks with P<1GeV large angles Low reconstructed multiplicity Vertex detection efficiency: dependence on momentum

31 Overall summary (1/4) The data/MC comparison on 8 GeV pions shows that data behavior is compatible with MC expectations, apart IP distribution, where a strong discrepancy is present at small values. The IP distribution discrepancy must be understood. The plate misalignment, together with the inefficiency and the track smearing already simulated, could (at least partially) explain it. Investigations are in progress. So far, the data/MC comparison on pions is used to make a systematic comparison between data and our MC. To predict the exact IP distribution found in data we need to simulate all the effects: - tracking inefficiency; - track parameters smearing; - plate misalignment; - cosmics and uncorrelated background. Summary of present activities on vertex reconstruction and decay search

32 Studies on CC interactions show that: the tracking efficiency is ~100% for P > 1GeV, drastically decreases below 1 GeV; the vertexing efficiency is ~95% for P > 2GeV, drastically decreases below 1 GeV Studies on CC ( ) and CC ( 3h) events show that: Several selection categories are populated by events with low momentum particles, in particular the momentum of particles from decay All these simulations dont take into account the effects of electronic reconstruction and neutrino location on the neutrino energy spectrum. Concerning events, they are roughly using the CNGS spectrum without taking into account the energy dependence of oscillations. Overall summary (2/4) The neutrino oscillation effect is very easy to reproduce. The electronic reconstruction and neutrino location effects have been parametrized in function of neutrino energy Summary of present activities on vertex reconstruction and decay search

33 Neutrino energy spectrum CNGS interacting CNGS with m 2 =2.5x10 -3 Interacting CNGS after electronic reconstruction Summary of present activities on vertex reconstruction and decay search

34 Overall summary (3/4) Studies on multiple vertices events like CC ( 3h) and charmed events show that low efficiencies and purities occur in the reconstruction and correct recognition of vertices while reconstructing 2 vertex in the same fiducial volume. The reason is the confusion between track associations when the primary and the secondary vertex are too near each other. Such effect is amplified where tracks have low momentum and high angles and by the presence of fake vertices (wrong associations, interactions, e-pairs,...). A study for the e-pair rejection is shown. Pair Based Vertexing algorithms implemented in FEDRA cannot be used for the topologies recognition as they are. The pairs association should be studied according to the analysis peculiarities. Global Vertexing method could be more effective and its effectiveness is under study. The study of the microtracks near the vertices could play an important role. Summary of present activities on vertex reconstruction and decay search

35 Comments The vertex reconstruction is well under control for ν μ events –There are different algorithms with similar performance. We are in the process to select the best algorithm The decay search algorithms have to be tuned. In particular, it was shown that –The hunting for short decays (decays in lead) has to be optimized –The search for multi-prong decays is more difficult than single-prong. An approach on the so called Global vertexing is being tried The usage of micro-tracks is mandatory

36 Momentum measurement by MCS M. Besnier

37 Perfect MC linearity, shift for 4 GeV data (250MeV offset) The MC indicates that it is possible to measure momentum until 8GeV with a resolution of 26%. MC/data study Data fome from TBàCERN in 2002-04 Resolution update after fit range studies independently determined!

38 Large angle results 3 effects appear at large angles ( >0.1rad ) 1) Crossed Lead thickness more important 0.1 0.2 0.3 0.4 0.5 0.6 MC 4GeV pions at different 3D angle :

39 How to determine correctly with OPERA track configuration ? -PMS at 0rad is now implemented in FEDRA with a s set to 1.8mrad. The Z correction with slope is also taken into account. But no dependance with slope => wrong momentum estimation at large angles. -First idea of using passing-through cosmic tracks to evaluate the has to be reconsidered because of wide angular and momentum dispersions. -A way to get the is to parameterise its value with data and update it often. Pgen (GeV) for cosmic muons with x/y < 0.4rad x (rad) for cosmic muons Albertos cosmics simulation

40 Conclusion : Some updates on momentum resolutions at 0rad : fitting range does not exceed 14 plates. free in the calculation is a wrong way to evaluate the momentum angular dependance (under studies) : -should be parametrised in X and Y directions separately -or should be avoided by changing coordinates frame A draft discussing the results related to the first 2 points is in preparation

41 41 OPERA Analysis status in Neuchatel Frank Meisel, Frederic Juget, Guillaume Lutter 01.06.2007 Université de Neuchâtel

42 42 Status in Neuchatel Three major projects on emulsion reconstruction (besides scanning): Developing and integration of an advanced shower reconstruction algorithm/library into FEDRA Testing different methods of shower reconstruction Continue/Improve the energy measurement of an electromagnetic shower

43 43 libShower First version has been adopted by Frederic, can be used still options for improving / modifing gives reconstructed shower output file user has to decide which showercandidates to put in... In the near future me (FWM) will provide idea/implementation of a shower reco using maybe tracks or more sophisticated (up to know we have to know the initiating basetrack)

44 44 Testing different methods shower reconstruction Using different parametersets to find best set for efficency / purity of a shower with a induced (microscope) bg. slightly modified algorithm (going downstream instead of upstream) ConeTube, Neuchatel scanned empty (peanut) Brick for BG have to scan over 250Mio. parametersets->taking long time.... still running......(Submit on any cluster machine prefered) taken then best paramters in ShowerReco and for energymeasurement. For example: Electron energy and BG contamination

45 45 Continue/Improve the energy measurement of an electromagnetic shower e/pi_Algorithm and variables for e/pi separation taken over: Number of Basetracks, dR, dTHeta distributions (mean, rms) Longitutinal profile (number of BT per each plate (11...56 sheets) ANN Structure InputNeurons: 5+#LongProfile => 16...61 variables HiddenLayer1,2:n+1, n(n=InputNeuron) OutputNeuron, 50 TrainingsEpochs on the cont. sample (0.5..6GeV, 0.5..10GeV) 35kEvents Energy correction has to be done on the output Linear fit function: E_(measured) -> E_(true) Run again with:E_(measured) -> E_(corrected) Plots/Results for the first ParameterSet:

46 46 ANN Outputs Before Linear Energy Correction (Trained on 0.5..10GeV, 20Sheets) After Linear Energy Correction

47 47 Before Linear Energy CorrectionAfter Linear Energy Correction Shower Resolution can be improved (now...~50%/Sqrt(E)) 20 sheets

48 48 Summary Neuchatel is continuing on scanning and simulation: energy measurement slight improvements in energy resolution: but to early to have complete datasets insert into shower package also... Shower Reconstruction ( focused on e for now ) slight improvements in efficency, purity: but to early to have complete datasets developing convenient and useful shower algos and their insertion in fedra still ongoing....

49 / separation / separation

50 Results of Perrine Royole (IPNL) dE/dx (data) Using only the dE/dX

51 Multiple scattering

52 Multiple scattering (simulation) Multiple scattering dE/dx Muon Pion

53 Simulation

54 Multiple scattering (data) Volume_grains (data) N_ grains (data) et separation (data) et separation (data)

55 Preliminary / separation (data) / separation (data)

56 % misidentified pions % muons identification efficiency Preliminary

57 Comments The particle identification in a brick (electron, pion, muon, proton) as well as the momentum/energy measurement is well under control The particle identification in a brick (electron, pion, muon, proton) as well as the momentum/energy measurement is well under control New test-beams are very important to fine tune the algorithms (see Next talk on TB activities) New test-beams are very important to fine tune the algorithms (see Next talk on TB activities)

58 Tracking in an ECC (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche) Tracking in an ECC (M. Besnier, C. Bozza, T. Fukuda, K. Kodama, I. Kreslo, Y. Nonoyama, C. Pistillo, C. Sirignano, V. Tioukov, Zghiche) Vertex location as a function of the event classification (L. Arrabito, C. Bozza, M. De Serio, I. Kreslo, A. Marotta, Y. Nonoyama, C. Pistillo, C. Sirignano) Volume scan, vertex reconstruction and decay selection based on topological criteria (M. Besnier, C. Bozza, F. Di Capua, T. Fukuda, K. Kodama, M. Komatsu, I. Kreslo, A. Marotta, Y. Nonoyama, A. Pastore, C. Pistillo, L. Scotto Lavina, C. Sirignano, V. Tioukov, A. Zghiche) Brick to brick connection (E. Carrara, M. Komatsu, A. Longhin) Brick to brick connection (E. Carrara, M. Komatsu, A. Longhin) Momentum measurement by MCS criteria (M. Besnier, C. Bozza, M. Komatsu, C. Sirignano, A. Zghiche) e/pi separation and energy measurement (S. Aoki, F. Juget, F. Meisel) p/pi and pi/mu separation (S. Aoki, T. Fukuda, I. Kreslo, I. Laktineh, K. Mannai, C. Pistillo) Post-scanning 1mu/0mu classification (Y. Nonoyama) Post-scanning 1mu/0mu classification (Y. Nonoyama) Kinematical decay selection criteria (C. Bozza, A. Marotta, Y. Nonoyama, C. Sirignano) Kinematical decay selection criteria (C. Bozza, A. Marotta, Y. Nonoyama, C. Sirignano)


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