1. Non-interceptive profile measurements via light-emission based tomography technique DITANET International Conference: Accelerator Diagnostic Techniques Cherry May Mateo- DITANET, CEA Saclay Co-authors: G. Adroit, R. Gobin, Y. Sauce, F. Senée, O. Tuske

2. 2 Motivation Increased demand  It must not perturb the beam  It must not be destroyed by high current beam (kilowatt beam power) Optical Profilers  Beam Induced Fluorescence (BIF) Monitor at GSI *  Beam Ionization Optical profile monitors Non-destructive diagnostics * F. Becker et al., Beam Induced Fluorescence Monitor for Transverse Profile Determination of 5 to 750 MeV/u Heavy Ion Beams, Proceedings of DIPAC 2007, Venice, Italy Schematic of BIF at GSI * Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

3. Beam direction r r Optical beam profile

4. 4 Optical Profiler in IPN/CEA * P. Ausset, et. al., Transverse Beam Profile Measurements for High Power Proton Beams, Proceedings of EPAC 2001, Paris, France Beam profiles of proton beam Profiles obtained with different gases but with constant gas pressure. HH HH HH HH * Pottin, B, (2001) Etude d’un profileur optique de faisceaux intenses de protons par absorption laser, Doctor of Science thesis. Institut de Physique Nucléaire Intensified CCD camera was used to capture beam image Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

5. 5 Tomography Tomography is the method used to reconstruct a 2D cross sectional image of an object given multiple flat scans taken from multiple angles around an object Measurable Solvable x y Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

6. 6 How? Algebraic Reconstruction Technique for 2 Projections f 1 f 2 f 3 f 4 f 5 f 6 f 7 f 8 f 9 g 1 = f 1 + f 4 + f 7 g 2 = f 2 + f 5 + f 8 g 3 = f 3 + f 6 + f 9 g 4 = f 7 + f 8 + f 9 g 5 = f 4 + f 5 + f 6 g 6 = f 1 + f 2 + f 3 g A f ProjectionsSparse MatrixImage Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

7. 7 How? Interested in finding a vector solution f to the vector equation: unknown slice vector Sparse matrix or forward projection matrix Projection data vector Iterative Procedure Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

8. 8 Initial Tests of the Algorithm Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

9. 9 Initial Test 0˚30˚60˚ 90˚120˚150˚ Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain laser L1 L2 Rotatable mask Gas- filled chamber CCD camera Reconstructed spatial distribution G.E. Belyaev, I.V. Roudskoy, D. Gardes, P. Ausseth and A. Olivier, Nucl. Instr. and Meth. in Phys. Res. A 578, p. 47-54 (2007).

10. 10 Numerical Test TEST IMAGE 0˚30˚60˚ 90˚120˚150˚ I HAVE Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

11. Dependence on number of Iterations 11 It.2It.3 It.6 It.8It.15 Original Projections Reconstructed Projections Projections measured at 90° Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

12. 12 Numerical Test The reconstructed image after 15 iterations y -profilex -profile 0°90° Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

13. 13 Original image Comparison with the source image Reconstructed image Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

14. 14 Experimental Measurements With Ion Beams ? Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

15. Vacuum Chamber specially designed for Measurements 15 Doppler shift effect spectroscopy Spatial density reconstruction 90° 30° Ion Beam Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

16. Imaging and Detection 16 Stingray F146B Fujinon HF25HA-1B objective Labview Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

17. Measurements in BETSI test bench 17 Banc d’Etude et de Tests des Sources d’Ions ECR source H 2 dominated residual gas Low Intensity beams : 2mA H+ current at the beam stop For validation ECR SOURCEFocusing solenoid Analyzing Magnet Tomographic chamber after the Magnet Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

18. Measurements in BETSI 18 Reconstructed Measured 0˚30˚60˚ 90˚120˚150˚ Bizarre ̎ BANANA ̎ shape beam ! NEED MORE VALIDATION Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

19. Measurements in SILHI 19 High Intensity Light Ion Source  ECRIS: 2.45 GHz - 875 Gauss.  CW or pulsed mode.  up to 130 mA at 95 kV  kilowatt of beam power Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

20. Measurements in SILHI 20 Solenoid 1 Solenoid 2 Steerer 1 Steerer 2 Tomography chamber Ion Source Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

21. Measurements VS Sol 2 current 21 138A142A143A147A153A159A I Solenoid-2 (A) I beam dump (mA) I Reconstructed projection Same Linear dependence Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

22. Measurements VS Sol 2 current 22 138 141 143147153159 BUT Beam Shape Beam position have changed !  Non linearity of the solenoid for such beam size Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

23. 23 Measurements VS Steerer current Varying the steerer values DH1 +0,2 DV1 -0,7 DH2 +0,5 DV2 -0,5 DH1 0 DV1 -0,2 DH2 -0,9 DV2 -0,3 Position has changed Intensity remains constant BUT Beam shape has changed ! Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

24. Copper « Profiler » 24 Water cooled copper block Manual translator Camera 1 Beam Camera 1 for the copper « profiler » mounted on the 30° viewport  BEAM SPOT Camera 2 on the five 90°-viewport for tomographic reconstruction Measurement region with camera 2 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

25. Camera 1 BEAM SPOT Copper block inside the chamber BEAM Camera 2 TOMOGRAPHY on VP1 VP1 VP2 VP3 VP4 VP5

26. Copper « Profiler » 26 Comparing the shape of the reconstructed image with 5 viewports with the copper ̎ profiler ̎ Reconstructed Measured BEAMBEAM Comparison between the beam spot and the reconstructed image shape is very much comparable even with 5 projections CAMERA1 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

27. Summary It was demonstrated that tomography technique can reconstruct the spatial density of the beam both for low and high intensity beams. ▫6 viewports seemed to be enough to reconstruct smooth beams. The algorithm written in MATLAB is very fast. ▫Future use of 6 simultaneous cameras is foreseen. 27 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

28. Acknowledgements This work is supported by the DITANET Marie Curie European network. CEA Saclay ▫ Romuald Duperrier ▫ Wilfrid Farabolini ▫ Guillaume Ferrand ▫ Alain France ▫ Francis Harrault 28 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

29. 29 Thank you for your attention

30. 30 Backup Slides

31. 31 Numerical Illustration with MATLAB Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

32. 32 Step 1 Image to Projections of the TEST IMAGE 0˚30˚60˚ 90˚120˚150˚ TEST IMAGE I HAVE Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

33. 33 Step 2 Construction of the Projection vector ̎ g ̎ Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

34. 34 Sparse matrix is constructed Step 3 6 projections 101 x 101 image  606 x 10201 sparse matrix size Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

35. 35 Step 4 = Must solve for f Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

36. 36 pixel values Step 5, iteration 2 f is reshaped to 101× 101 image matrix Reconstructed Image Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

37. An Illustration 37 Number of iterations pixel values f is solved iteratively Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

38. 38 An Illustration The reconstructed image after 15 iterations y -profilex -profile 0°90° Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

39. An Illustration 39 It.2It.3 It.6 It.8It.15 Reconstructed images with respect number of iterations Original Projections Reconstructed Projections Projections measured at 90° Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

40. 40 Original image An Illustration Reconstructed image Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

41. Cherry May Mateo/ High Intensity Beam Diagnostics Workshop/ 27.09.2011/Massy France 41 Algebraic Reconstruction Technique for more than 2 projections Sparse matrix for more projection angles not equal to 0˚ and 90 ˚ How? C4C4 C1C1 C2C2 C3C3 More angles  more complicated sparse matrix Number of rows Number of columns

42. Optical Profiler in IPN/CEA 42 * P. Ausset, et. al., Transverse Beam Profile Measurements for High Power Proton Beams, Proceedings of EPAC 2001, Paris, France H3+H3+ H2+H2+ H+H+ Faisceau d'hydrogène H + H 2 + H 3 + Balmer H 656.2 nm Doppler Shift Spectroscopy allows discrimination of different beam components * Pottin, B, (2001) Etude d’un profileur optique de faisceaux intenses de protons par absorption laser, Doctor of Science thesis. Institut de Physique Nucléaire H+H+ r λ H2+H2+ HαHα Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

43. Tomography 43 By Fourier Slice Theorem, EXACT value of f(x,y) can be calculated given an infinite number of projections g g Fourier Slice theorem: θ s t g(s,θ) x y θ Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain

44. 44 How? Iteration process gVector of projection data f Vector of unknown slice data A Matrix such that g = Af a ij Value of element located at the i th and j th column of matrix A i Projection subscript j Pixel subscript g i Number of counts in the i th bin of the projection dataset m Number of pixels n Number of bins g Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain