Methods for extremely sparse-angle proton tomography

Abstract

Proton radiography is a widely fielded diagnostic used to measure magnetic structures in plasma. The deflection of protons with multi-MeV kinetic energy by the magnetic fields is used to infer their path-integrated field strength. Here the use of tomographic methods is proposed for the first time to lift the degeneracy inherent in these path-integrated measurements, allowing full reconstruction of spatially resolved magnetic field structures in three dimensions. Two techniques are proposed which improve the performance of tomographic reconstruction algorithms in cases with severely limited numbers of available probe beams, as is the case in laser-plasma interaction experiments where the probes are created by short, high-power laser pulse irradiation of secondary foil targets. A new configuration allowing production of more proton beams from a single short laser pulse is also presented and proposed for use in tandem with these analytical advancements.

Proton imaging of high-energy-density laboratory plasmas

“…The number of high-energy laser facilities equipped with multiple high-intensity laser beams suitable for proton acceleration is currently small (Danson et al, 2015), while fielding more than two D 3 He capsules at once is not feasible even at thelargest facilities, due to the number of beams required per capsule. Novel targets have been proposed for overcoming this issue (Spiers et al, 2021), which in principle would allow a single short-pulse beam to produce multiple proton beams. Future experiments will be needed to confirm whether such a scheme would work in practice.…”

“…This suggests that specific work on sparse-angle tomography algorithms would be warranted. Two possible approaches that have been demonstrated to address this problem have improved the performance of more conventional filtered backprojection schemes (Spiers et al, 2021). Further improvements could be derived by considering studies in related areas, such as the holographic reconstruction via scattering that is done with electrons (Mankos, Scheinfein, and Cowley, 1996).…”

Accelerator beam phase space tomography using machine learning to account for variations in beamline components

“…Data collection and processing can be time-consuming, especially for higher-dimensional phase space reconstruction. Traditional tomography algorithms can be prone to artefacts in the reconstruction, especially when the range or number of projection angles is limited (as is often the case in beam phase space tomography) [23,24]: although there are techniques that can be used to reduce the appearance of reconstruction artefacts (see, for example, [25]), ultimately the fidelity of the reconstruction depends on collecting screen images with a sufficient number of different strengths of the upstream quadrupoles, setting a lower limit on the time needed for data collection and analysis.…”