Supervisor: Christopher Ridgers (University of York)
High power lasers produce extremely strong electromagnetic fields in their focus. The fields rapidly strip electrons from atoms to produce a plasma. These electrons can strongly radiate x-rays by bremsstrahlung. These x-rays are very useful for radiographing dense material and have been proposed as a diagnostic tool for inertial confinement fusion (ICF) experiments. In ICF a driver is used to compress DT fusion fuel capsule to high density and temperature. This compression is unstable and deformations of the spherical fuel capsule inhibit fusion performance. Solving this is a major research question in ICF but is difficult due to a lack of diagnostic information about the shape of the compressed fuel. The recent addition of the ARC laser to the largest ICF experiment (the National Ignition Facility) aims to solve this using bremsstrahlung x-rays to radiograph the fuel. Producing x-ray sources which can radiograph high Z materials is a major goal of experiments on the PW-power Orion laser at AWE. Such sources have potential applications to border security.
Bremsstrahlung emission from laser-plasma interactions is complex as these interactions are highly nonlinear, depending on many parameters. Previously we added bremsstrahlung to the particle-in-cell code EPOCH. In this project you will follow on from this, using this version of EPOCH to understand how to control laser-driven bremsstrahlung sources. You will apply machine learning techniques to explore the complicated parameter space. Of particular interest is our ability to modify the laser and target parameters to tailor the x-ray spectrum. It is envisaged that this will form the basis of an Orion experiment.
This project will provide training in modern computational techniques and provide opportunity to work as part of an experimental team.
The project will be partly funded by AWE so visits there will be beneficial. Presentation of work at national and international conferences is encouraged.
This project is offered by University of York. For further information please contact Christopher Ridgers (christopher.ridgers@york.ac.uk).
This project may be compatible with part time study, please contact the project supervisors if you are interested in exploring this.