1. Nuclear Emulsion Readout Techniques Developed for the CHORUS Experiment or “...how we managed in CHORUS to convert nuclear emulsion into an electronic detector” Ioannis M. Papadopoulos CERN EP-CHE division

2. Emulsion highlights 3-d spatial resolution better than 1  m no dead time permanent storage device cheapest detector large discovery potential

3. W.H.Barkas, Nuclear research emulsions,1963 & 1973 Emulsion readout…until recently

4. CHORUS physics Search for    oscillation SBL appearance Clean signal  X    kink  c  mm  kink  mrad Phys. Lett. B 424 (1998) 202-212 Phys. Lett. B 434 (1998) 205-213 hep-ex/9907015 CDHS CCFR E531 NOMAD CHORUS (Phase II)   

5. 770 kg emulsion target and scintillating fibre tracker Calorimeter Air core spectrometer and emulsion tracker Air core spectrometer and emulsion tracker Veto plane Muon spectrometer Muon spectrometer  - -  - - h-h- h-h- T=5° Nucl. Instr. Meth. A 401 (1997) 7-44 CHORUS detector

6. Focal depth : ~3  m Red frame: ~30x40  m 2 beam 0  m ‘Inside a vertex plate’ -21  m -36  m

7. Automatic microscopes in Nagoya Sony analog CCD camera Track Selector Host CPU Network data storage NIKON optics and stage http://flab.phys.nagoya-u.ac.jp/flab. html

8. Automatic scanning 90  m plastic backing 350  m (175  m) emulsion sheet CCD camera CCD camera microscope stroke tomographic image X50 magnification ~3  m focal depth 140x160  m view, 120 Hz frame rate 350  m (175  m) emulsion sheet emulsion plate track

9. Track Selector algorithm track found track shifting grain finding, binarizing expanding summing track

10. Track Selector implementation Current performance: 3 Hz (for all tracks with  z < 400 mrad) T.Nakano, Ph.D. Thesis, Nagoya Univ., 1997 During 1 camera cycle (8 ms): digitizes image (FADC) finds pixels of grains (hardware FIR filter) expands grains (3  3 expander) stores pixels in FIFO buffers After 16 images are taken: tries out a number of shifts IN PARALLEL (to cover angular acceptance) for every shift tried: performs summing (FPGA technology) clustering on the sum image (Pentium) finds tracks stage has moved already to next position

11. CERN/NIKHEF microscopes http://choruswww.cern.ch/CERN-Microscope Larger stage (MICOS) to handle the whole emulsion sheet Larger digital camera (Thomson Mpixel CCD) to analyze larger emulsion volume per view using DSP cards (Blue Wave) based on the TI-C80 and TI-C620 processors for flexible data treatment Advanced optics from Jenoptik  FOV=0.5 mm DOF=1.2  m shutter up to 120 Hz 350 x 350  m 2 /view

12. Microscope layout Motor control CCD Mpixel camera Objective, shutter, light source DAC/ADC IO I/O driver Clean roomOperator room 10 m Interface card Data (LVDS) DSP C80, C620 (Image filtering) Network Matrox Pulsar (Emulsion display, graphical tools) Matrox Mil. (primary display) COM1 COM2 RS232 Slow Control Temp.,Hum.,Oil Clustering, tracking, controlling stage and light (2  Pent ium) controls (RS422) PCI FastEthernet

13. Data flow 2  Pentium II (C++) Clustering (grain finding) JPEG compression prediction tracking FastEthernet card 1 Mb raw data input @30 Hz 128 kb pixels LINUX farm (C++) general tracking 16-25  30kb grain data 20-250  30kb grain data 250  50kb image data tracks + grains 2  C620 (Assembly) IIR filter C80 (C, Assembly) acquisition control Objectivity DB tracksvertices grains (emulsion hits) kinks... PCI Ethernet

14. We want to find many of such events fully automatically Phys. Lett. B 435 (1998) 458-464...and analyze the data pretending they were taken using an electronic tracker with a 3-D spatial resolution of 1 µm.