1. Evaluation of SySal efficiencies for 1  sample Chorus Collaboration Meeting Ishigaki,7-8 April 2003 Emiliano Barbuto, Chiara Sirignano, Salvatore Sorrentino Salerno Emulsion Group

2. Introduction Collecting MC files Storing them into an Access DB Collecting background files directly from emulsion Simulating scan-back procedures and selections Merging MC data and emulsion data into Image files Processing Image files with our alghorithms Computing acceptancies and efficiencies We evaluated SySal efficiencies using Choral predictions (see Inuyama CM April 2000), now we perform the same work using Chant predictions. We go troughout the same procedure, but slight different criteria are needed. Step towards our efficiencies results are: A cc, A ,  0 MC Events Kinematical Selection Simulated Image Files VRK & Other Reconstruction Programs A VRK cc, A VRK   kink Simulation strategy

3. MC Data We collect a large amount of dst files related to MC neutrino interactions processed by Eficass and Chant. We extract from them only events reconstructed by Chant and their topology in emulsion: Vertex coordinates, tracks’ slopes, muons’ momenta, neutrinos’ energies. In the end our sample of MC truth neutrino interactions is: 52225  CCDIS 12711  CCDIS (  signal) These events are predicted along the whole Chorus target and we descarded events situated outside or in air between two emulsion stacks.

4. MC Vertices This is longitudinal distribution of MC vertices along each emlsion sheet. If you compare it with the same distribution coming from data we used in previous simulation we observe that event ratio in base is bigger. This corresponds to experimental measurements. Now 2000

5. Kink topologies These are two distributions related to kink topologies, We divide kinks into short (mother and doughter track in the same plate) and long ones. Short = 0.34 Long = 0.66 We require the kink to be : Less than 5 plate downstream respect to the primary vertex Kink angle > 25 mrad Decay length > 20  m Mu Pt > 250 MeV/c =    ( 0.720 + 0.006 )

6. Scanning files Background tracks will come from SySal scanning data and we selected 1006 different random files. In each file there are stored different type of information: Information stored also in FZ banks. Header Id Predictions Tracks Acquisition Id Emulsion Side Scan-Back Track Id Grains number Grains Scanning specifications Measured slopes Coordinates Distortion corrections Each file could consist of 1 scanning field (200  200  m 2 )  40 tracks or of 4 scanning fields (400  400  m 2 )  120 tracks.

7. Simulated scanning procedure on thin sheets We select the following sample for CS: Track angle < 400 mrad Track probability > 0.1 (only for hadrons) CS angular tolerance 30 – 50 mrad, position cut 600  m SS angular tolerance 30 – 50 mrad, position cut 350  m We set as scanbacks all reconstructed tracks having an angular matching with MC for the same event. = 70.413 + 0.004 % In this way SySal acceptancies are: <A   + 0.008 %   + 0.01 %

8. Chant vs Choral Selection criteria are quite different from ones we used prevoiusly, we see that there is the same mean number of scanback tracks per event. CC 

9. Image files MC vertex Taking a background file from scanning from a sample of 1006 Taking MC tracks from vertex Simulating grains with a certain  (density along the trajectory) and  (dispersion along the fitted trajectory) Merging them into an Image file Typical errors on slopes in emulsion (from Scanning Data):  S y, z = m y, z · S y, z + n y, z +  y, z Shrinkage ErrorSySal Accuracy  0  0.006  y,z 0.008  0.004 n y,z -0.131  0.026 m y,z Value We create image file both in interaction and previous bulk

10. Vertex detection efficiencies Arec CC VRK = 93.24 + 0.07 Arec  VRK = 92.15 + 0.07 Automatic reconstruction (vertex alarms) Semi-automatic selection for low multiplicity (1-2 matching tracks) Manual check of vertex alarms to be confirmed and stopping tracks.

11. Kink topologies Short kink: mother & daughter tracked in the same emulsion side Short kink in base: mother & daughter not in the same side Long kink: mother & daughter tracked in the same emulsion side Long kink: mother & daughter not in the same emulsion side Reconstructed topologically Identified by high IP and monitoring tracks’ slopes

12. SySal scanning and reconstruction efficiencies A CC ( E ) = A CC Scan (E) A CC VRK (E) A CC Scan (E) is the acceptance and comes from scanning procedure simulation A CC VRK (E) is VRK efficiency in vertex reconstructions = 0.65 + 0.07 A  ( E ) = A  Scan (E) A  VRK (E) A  Scan (E) is the acceptance and comes from scanning procedure simulation A  VRK (E) is VRK efficiency in vertex reconstructions = 0.63 + 0.07

13.  kink computation  kink =  0  Rec = ( 0.720 + 0.006 )  Rec  Rec = % Short  RecShort + % Long  RecLong = 0.34  RecShort + 0.66  RecLong  RecShort = r tracked  tracking  VRKtrk + r top  VRKtop = 0.51 + 0.04  RecLong = r tracked  tracking  VRKtrk + r top  VRKtop = 0.72 + 0.04  Rec = 0.65 + 0.05  kink =  0  Rec = ( 0.720 + 0.006 ) 

14. Outlook Next step is to evaluate SySal efficiencies for 0mu samples (oscillation search) and then for charm samples. These analisys would be based on Total Scan phase and we will evaluate efficiencies. We will use a similar strategy: we will put MC true events into Total Scan empty volumes and than we will run on image files our event reconstruction algorithms; finally we will apply our selection criteria to find interesting topologyes.