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  • A multi-level analysis of data quality for formal software citation

    Authors: David Schindler, Tazin Hossain, Sascha Spors, Frank Kr├╝ger
    DOI: https://doi.org/10.48550/arXiv.2306.17535
    Submitted by frank.krueger    
      Mean reproducibility score:   9.0/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    We spend a lot of time to make our analyses reproducible. A review would allow us to collect some information on whether we are successful with it.

  • 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.

  • PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals

    Authors: Henry Charlesworth and Giovanni Montana
    Submitted by gmontana74      
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper proposes a probabilistic planner that can solve goal-conditional tasks such as complex continuous control problems. The approach reaches state-of-the-art performance when compared to current deep reinforcement learning algorithms. However, the method relies on an ensemble of deep generative models and is computationally intensive. It would be interesting to reproduce the results presented in this paper on their robotic manipulation and navigation problems as these are very challenging problems that current reinforcement learning methods cannot easily solve (and when they do, they require a significantly larger number of experiences). Can the results be reproduced out-of-the-box with the provided code?

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