Tomographic Reconstruction of Particle Beam Distributions
Student: Tyler Blanton
School: University Of North Carolina At Chapel Hill
Mentored By: Balša Terzić
In the areas of plasma and charged particle beam diagnostics, computed tomography (CT) is used to reconstruct a beam's two-dimensional (2D) particle distribution using only line-of-sight intensity projections. This reconstruction may be accomplished using either 1D or 2D mathematical transforms, depending on whether or not the distribution is cylindrically symmetric. In practice, only a relatively small number of intensity projections (e.g., <100) can be measured, and these measurements are susceptible to Poissonian (signal-dependent) noise. In this study, we improved the performance of particle beam CT in noisy environments by exploring the effectiveness of wavelet-based denoising for both the 1D and 2D reconstruction methods. We created a program in MATLAB which reconstructs a beam's particle distribution from simulated noisy intensity projections that can be denoised for both the 1D and 2D methods. In both cases, we found the denoising procedure to greatly improve the signal-to-noise ratio in noisy environments.