1. Jean Favier LAPP GenIma: program to simulate emulsions Introduction GEANT : GENerate tracks and grains IMA: makes pictures Examples Conclusions

2. Jean Favier LAPP Introduction The lack of data for various conditions ( particle type, angles, energies, fog densities, integration times, etc) and a poor statistics make difficult the reconstruction programs optimization. The large feed-back time between beam tests and scanning is responsible for these difficulties. It was attracting to reproduce emulsions data by Monte- Carlo, as for the other detectors, with the hope to increase the comprehension of the parameters influence, and to permit an optimization of the designing of future beam tests.

3. Jean Favier LAPP PART 1: Particles generation in GEANT (3.2) ( IN PROGRESS…) Problems with Geant to reproduce in the same time  electrons and the good relativistic rise for dE/dX ( We keep the coodinates of each energy deposite Volume =200*200*44  3 (one layer ) ) To get a density of 30 grains/100  en mean for mip, I eliminate randomly points. ( same result than to discriminate on energy deposite)

4. Jean Favier LAPP Grain x,y,z Pixels filling zone density =f(r) in plan i r Optical axis   = focusing angle = arcsin(N.A/n)

5. Jean Favier LAPP PART 2 In a separate program: For each “grain” x,y,z we calculate intercepted surfaces by conical expansions backward and upward, isolating zones of pixels to fill. The cone aperture is determined by the lense parameters :  = arcsin(N.A/n refr ) Pixels are filled with grey in each of the 16 picture planes; grey densities vary with the grain-plane distance( 1/d 2 et e -d/ ou =longueur d’absorption optique de l’emulsion). Size of grains is obtained by an appropiate smearing Field is 200×200  for 1024 ×1024 pixels, 16 planes; cone angle is 36 0 (pure Liban cedar oil), or 64 0 (air) Then add the wanted amount of random fog (6 grains/ (10  ) 3 ) and expand them also. Pictures are written in Fortran (PPM format), then converted in JPEG with XView.

6. Jean Favier LAPP Format PPM http//cedric.cnam.fr/~gouet/Var/ppm.html #Example: toto.ppm P3 4 255 # red green blue 0 0 0 16 16 16 32 32 32 48 48 48 64 64 64 80 80 80 96 96 96 112 112 112 128 128 128 143 143 143 159 159 159 175 175 175 191 191 191 207 207 207 223 23 223 239 239 239

7. Jean Favier LAPP Oil and air (without fog) N.A=nsin(  ) n=1. ou 1.52  = 64 0 ou 36 0

8. Jean Favier LAPP Electrons tracks 0 to 1 Mev  20 0 horizontal, fog= 6/1000  3 Jean Imad

9. Jean Favier LAPP Emulsion simulation 16 images

10. Jean Favier LAPP Emulsion simulation 16 images

11. Jean Favier LAPP

12. Emulsion simulation

13. Jean Favier LAPP Emulsion simulation 16 images

14. Jean Favier LAPP Emulsion simulation 16 images

15. Jean Favier LAPP Emulsion simulation 16 images

16. Jean Favier LAPP Emulsion simulation 16 images

17. Jean Favier LAPP Emulsion simulation 16 images

18. Jean Favier LAPP Emulsion simulation 16 images

19. Jean Favier LAPP Emulsion simulation 16 images

20. Jean Favier LAPP Emulsion simulation 16 images

21. Jean Favier LAPP Emulsion simulation 16 images

22. Jean Favier LAPP Emulsion simulation 16 images

23. Jean Favier LAPP Emulsion simulation 16 images

24. Jean Favier LAPP Emulsion simulation 16 images

25. Jean Favier LAPP Find the vertex ! : 5 muons emerging from a point at 17 microns depth

26. Jean Favier LAPP

42. Next steps Improve grain density = f(dE/dX), saturations,  rays add the second layer Interface with microscope software Compare with available data ( ex: eff=f(angle) ) Version root, C++ ? Documentation “Album” of various backgrounds (compton + fog, refreshing actions) Distorsion simulation Lyon inclined geometry?