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  • Laser-assisted propagation of a relativistic electron bunch in air

    Authors: R M G M Trines, A P L Robinson, J R Wilkinson, J N Kirk, D S Hills, R M Deas, S Morris, T Goffrey, K Bennett, T D Arber
    DOI: 10.1088/1361-6587/ac0b9d
    Submitted by Stuart_Morris      

    Why should we attempt to reproduce this paper?

    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.

  • Thermodynamics of stacking disorder in ice nuclei

    Authors: David Quigley
    DOI: 10.1063/1.4896376
    Submitted by dquigley      
      Mean reproducibility score:   3.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    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.

  • Highly efficient conversion of laser energy to hard X-rays in high intensity laser-solid simulations

    Authors: S. Morris, A. Robinson, C. Ridgers
    DOI: 10.1063/5.0055398
    Submitted by Stuart_Morris      

    Why should we attempt to reproduce this paper?

    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.

  • REMoDNaV: robust eye-movement classification for dynamic stimulation

    Authors: Asim H. Dar, Adina S. Wagner, Michael Hanke
    DOI: https://doi.org/10.3758/s13428-020-01428-x
    Submitted by adswa    
      Mean reproducibility score:   7.6/10   |   Number of reviews:   5
    Why should we attempt to reproduce this paper?

    In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at https://github.com/psychoinformatics-de/paper-remodnav). We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.

  • Plasmonic nanostructure design and characterization via Deep Learning

    Authors: Malkiel, I., Mrejen, M., Nagler, A. et al.
    DOI: 10.1038/s41377-018-0060-7
    Submitted by hub-admin    

    Why should we attempt to reproduce this paper?

    The current code is written in Torch, which is no longer actively maintained. Since deep learning in nanophotonics is an area of active interest (e.g. for the design of new metamaterials), it is important to update the code to use a more modern deep learning library such as tensorflow/keras

  • model4you: An R Package for Personalised Treatment Effect Estimation

    Authors: Seibold, H., Zeileis, A. and Hothorn, T., 2019
    DOI: 10.5334/jors.219
    Submitted by hub-admin    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    I guess it could be a cool learning experience. The paper is written with knitr, uses a seed, is part of the R package it describes, was openly written using version control (SVN, R-Forge) and is available in an open access journal (@up_jors).

    Tags: R LaTeX SVN knitr

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