Most electron beam physics is considered in the context of a vacuum, but there are applications to long-range electron beam transmission in air. As particle acceleration sources become more compact, we may have the chance to take particle beams out to the real world. The example provided in the paper describes that of x-ray backscatter detectors, where significantly stronger signals could be achieved by scanning objects with electron beams. This paper forms the basis for a potential new mode of particle-beam research, and it is important to ensure the reproducibility of this work for groups who wish to explore the applications of this new technology.
The results of this paper have been used in multiple subsequent studies as a benchmark against which other methods of performing the same calculation have been tested. Other groups have challenged the results as suffering from finite size effects, in particular the calculations on mixtures of cubic and hexagonal ice. Should there be time during in the event, participants could check this by performing calculations on larger unit cells. Each individual calculation should converge adequately within 96 hours making it amenable to a HPC ReproHack. Given modern HPC hardware many such calculations could be run concurrently on a single HPC node.
There are many applications to multi-MeV X-rays. Their penetrative properties make them good for scanning dense objects for industry, and their ionising properties can destroy tumours in radiotherapy. They are also around the energy of nuclear transitions, so they can trigger nuclear reactions to break down nuclear waste into medical isotopes, or to reveal smuggled nuclear-materials for port security. Laser-driven X-ray generation offers a compact and efficient way to create a bright source of X-rays, without having to construct a large synchrotron. To fully utilise this capability, work on optimising the target design and understanding the underlying X-ray mechanisms are essential. The hybrid-PIC code is in a unique position to model the full interaction, so its ease-of-use and reproducibility are crucial for this field to develop.
Because: - Two fellow PhDs working on different topics have been able to reproduce some figures by following the README instructions and I hope this extends to other people - I've tried to incorporate as many of the best practices as possible to make my code and data open and accessible - I've tried to make sure that my data is exactly reproducible with the specified random seed strategy - the paper suggests a method that should be useful to other researchers in my field, which is not useful unless my results are reproducible
The original data took quite a while to produce for a previous paper, but for this paper, all tables and figures should be exactly reproducible by simply running the jupyter notebook.