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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. Non-destructive diagnostics.
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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
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Non-destructive diagnostics 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 Schematic of BIF at GSI* *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
Optical beam profile r Beam direction r
Ha Hb Hg Hd Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Optical Profiler in IPN/CEA Beam profiles of proton beam • Intensified CCD camera was used to capture beam image Profiles obtained with different gases but with constant gas pressure. *P. Ausset, et. al., Transverse Beam Profile Measurements for High Power Proton Beams, Proceedings of EPAC 2001, Paris, France *Pottin, B, (2001) Etude d’un profileur optique de faisceaux intenses de protons par absorption laser, Doctor of Science thesis. Institut de Physique Nucléaire
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Tomography y 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 x Measurable Solvable
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain How? Algebraic Reconstruction Technique for 2 Projections g1= f1 + f4 + f7 g2= f2 + f5 + f8 g3= f3 + f6 + f9 f1 f2 f3 f4 f5 f6 g6= f1 + f2 + f3 f7 f8 f9 g5= f4 + f5 + f6 g4= f7 + f8 + f9 g A f Projections Sparse Matrix Image
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain How? Interested in finding a vector solution f to the vector equation: unknown slice vector Sparse matrix or forward projection matrix Projection data vector IterativeProcedure
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Initial Tests of the Algorithm
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Initial Test Reconstructed spatial distribution 0˚ 30˚ 60˚ Rotatable mask L2 L1 laser Gas- filled chamber 90˚ 120˚ 150˚ CCD camera 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).
0˚ 30˚ 60˚ 90˚ 120˚ 150˚ I HAVE Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Numerical Test TEST IMAGE
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Dependence on number of Iterations Original Projections Reconstructed Projections It.6 It .2 It.3 It.8 It.15 Projections measuredat 90°
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Numerical Test The reconstructed image after 15 iterations 0° 90° y -profile x -profile
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Comparison with the source image Original image Reconstructed image
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain ? Experimental Measurements With Ion Beams
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Vacuum Chamber specially designed for Measurements Doppler shift effect spectroscopy 90° 30° Ion Beam Spatial density reconstruction
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Imaging and Detection • Stingray F146B • Fujinon HF25HA-1B objective Labview
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Measurements in BETSI test bench Banc d’Etude et de Tests des Sources d’Ions Tomographicchamber after the Magnet ECR SOURCE Focusingsolenoid ECR source H2 dominated residual gas Low Intensity beams : 2mA H+ current at the beam stop Analyzing Magnet For validation
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Measurements in BETSI 0˚ 30˚ 60˚ 90˚ 120˚ 150˚ Bizarre ̎BANANA ̎shape beam ! NEED MORE VALIDATION Reconstructed Measured
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Measurements in SILHI 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 Measurements in SILHI Steerer 1 Solenoid 2 Solenoid 1 Ion Source Steerer 2 Tomography chamber
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Measurements VS Sol 2 current 138A 142A 143A 147A 153A 159A Ibeam dump (mA) IReconstructed projection Same Linear dependence ISolenoid-2 (A)
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Measurements VS Sol 2 current BUT Beam Shape Beam position have changed! Non linearity of the solenoid for such beam size 141 138 153 143 147 159
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain 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 Intensityremains constant BUT Beam shape has changed!
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Copper « Profiler » Camera 1 for the copper « profiler » mounted on the 30° viewport BEAM SPOT Camera 2 on the five 90°-viewport for tomographic reconstruction Water cooled copper block Beam Manual translator Measurementregionwith camera 2 Camera 1
Camera 2 TOMOGRAPHY on VP1 VP1 VP2 VP3 BEAM Copper block inside the chamber Camera 1 BEAM SPOT VP4 VP5
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Copper « Profiler » Comparing the shape of the reconstructed image with 5 viewports with the copper ̎profiler ̎ BEAM Comparisonbetween the beam spot and the reconstructed image shapeisverymuch comparable evenwith 5 projections CAMERA1 Reconstructed Measured
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain 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.
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Acknowledgements • This work is supported by the DITANET Marie Curie European network. • CEA Saclay • Romuald Duperrier • Wilfrid Farabolini • Guillaume Ferrand • Alain France • Francis Harrault
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Thank you for your attention
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Numerical Illustration with MATLAB
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Step 1 Image to Projections of the TEST IMAGE 0˚ 30˚ 60˚ TEST IMAGE 90˚ 120˚ 150˚ I HAVE
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Step 2 Construction of the Projection vector ̎ g̎
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Step 3 Sparse matrix is constructed • 6 projections • 101 x 101 image • 606 x 10201 sparse matrix size
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Step 4 Must solve for f =
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Step 5, iteration 2 f is reshaped to 101× 101 image matrix Reconstructed Image pixel values
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain An Illustration f is solved iteratively pixel values Number of iterations
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain An Illustration The reconstructed image after 15 iterations 0° 90° y -profile x -profile
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain An Illustration Original Projections Reconstructed Projections Reconstructed images with respect number of iterations It.6 It .2 It.3 It.8 It.15 Projections measuredat 90°
Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain An Illustration Original image Reconstructed image
Cherry May Mateo/ High Intensity Beam Diagnostics Workshop/ 27.09.2011/Massy France How? Algebraic Reconstruction Technique for more than 2 projections Sparse matrix for more projection angles not equal to 0˚ and 90 ˚ C3 C2 More angles more complicatedsparse matrix C1 C4 Number of rows Number of columns
Optical Profiler in IPN/CEA 42 Faisceau d'hydrogène H+ H2+ H3+ Balmer H 656.2 nm DlH+ DlH2+ DlH3+ Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Doppler Shift Spectroscopy allows discrimination of different beam components r H2+ Hα H+ λ *Pottin, B, (2001) Etude d’un profileur optique de faisceaux intenses de protons par absorption laser, Doctor of Science thesis. Institut de Physique Nucléaire *P. Ausset, et. al., Transverse Beam Profile Measurements for High Power Proton Beams, Proceedings of EPAC 2001, Paris, France
Tomography 43 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain y By Fourier Slice Theorem, EXACT value of f(x,y) can be calculated given an infinite number of projections g s t g θ θ x Fourier Slice theorem: g(s,θ)
How? 44 Cherry May Mateo/ DITANET International Conference/ 11.11.2011/Seville, Spain Iteration process g Vector of projection data fVector of unknown slice data A Matrix such thatg = Af aij Value of elementlocatedat the ithand jthcolumn of matrix A i Projection subscript j Pixel subscript giNumber of counts in the ith bin of the projection dataset m Number of pixels n Number of bins g