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Search: WFRF:(Farmer Andrew J.) > Research review

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1.
  • Arndt, D. S., et al. (author)
  • STATE OF THE CLIMATE IN 2017
  • 2018
  • In: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 99:8, s. S1-S310
  • Research review (peer-reviewed)
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2.
  • Arun, K. G., et al. (author)
  • New horizons for fundamental physics with LISA
  • 2022
  • In: Living Reviews in Relativity. - : Springer Science and Business Media LLC. - 1433-8351 .- 2367-3613. ; 25:1
  • Research review (peer-reviewed)abstract
    • The Laser Interferometer Space Antenna (LISA) has the potential to reveal wonders about the fundamental theory of nature at play in the extreme gravity regime, where the gravitational interaction is both strong and dynamical. In this white paper, the Fundamental Physics Working Group of the LISA Consortium summarizes the current topics in fundamental physics where LISA observations of gravitational waves can be expected to provide key input. We provide the briefest of reviews to then delineate avenues for future research directions and to discuss connections between this working group, other working groups and the consortium work package teams. These connections must be developed for LISA to live up to its science potential in these areas.
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3.
  • Allanach, Benjamin C., et al. (author)
  • Simple and statistically sound strategies for analysing physical theories
  • 2022
  • In: Reports on progress in physics (Print). - : Institute of Physics Publishing (IOPP). - 0034-4885 .- 1361-6633. ; 85:5
  • Research review (peer-reviewed)abstract
    • Physical theories that depend on many parameters or are tested against data from many different experiments pose unique challenges to statistical inference. Many models in particle physics, astrophysics and cosmology fall into one or both of these categories. These issues are often sidestepped with statistically unsound ad hoc methods, involving intersection of parameter intervals estimated by multiple experiments, and random or grid sampling of model parameters. Whilst these methods are easy to apply, they exhibit pathologies even in low-dimensional parameter spaces, and quickly become problematic to use and interpret in higher dimensions. In this article we give clear guidance for going beyond these procedures, suggesting where possible simple methods for performing statistically sound inference, and recommendations of readily-available software tools and standards that can assist in doing so. Our aim is to provide any physicists lacking comprehensive statistical training with recommendations for reaching correct scientific conclusions, with only a modest increase in analysis burden. Our examples can be reproduced with the code publicly available at Zenodo.
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  • Result 1-4 of 4

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