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Inferring morphology and strength of magnetic fields from proton radiographs
Carlo Graziani1, Petros Tzeferacos1, Donald Q Lamb1
1Flash Center for Computational Science, Department of Astronomy and Astrophysics, University of Chicago, 5640 S. Ellis Avenue, Chicago, Illinois 60637, USA.
The Review of Scientific Instruments
|January 1, 2018
Summary
Proton radiography analysis for magnetized plasmas is improved with new theory. This method reconstructs magnetic fields from radiographs, advancing laser plasma diagnostics.
Area of Science:
- Plasma Physics
- Astrophysics
- Laser-Induced Fusion
Background:
- Proton radiography is crucial for diagnosing laser plasma experiments, especially those involving magnetized plasmas.
- Existing theoretical frameworks for analyzing proton radiographs have limitations in characterizing complex plasma structures.
Purpose of the Study:
- To develop an advanced theoretical framework for analyzing proton radiographs in magnetized plasmas.
- To enable a more comprehensive reconstruction of magnetic field structures from radiographic data.
Main Methods:
- Deriving a theory where proton radiographs are projection images of MHD current.
- Utilizing a 2D diffusion equation to reconstruct perpendicular magnetic fields in the linear regime.
- Investigating the impact of image contrast, noise, and experimental artifacts on reconstruction accuracy.
Main Results:
- Proton radiographs directly map to MHD currents along proton paths under linear conditions.
- A novel inversion method allows full reconstruction of projected perpendicular magnetic fields using radiograph data.
- The study quantifies limitations imposed by noise, discretization, edge effects, and target obstructions.
Conclusions:
- The developed theory significantly enhances the analytical capabilities for proton radiography in magnetized plasmas.
- The reconstruction method provides a powerful tool for inferring magnetic field structures and turbulence spectra.
- Future work will extend the analysis to the nonlinear regime for higher contrast scenarios.
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