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Sökning: WFRF:(Arthurs M.)

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1.
  • Aalbers, J., et al. (författare)
  • A next-generation liquid xenon observatory for dark matter and neutrino physics
  • 2023
  • Ingår i: Journal of Physics G: Nuclear and Particle Physics. - : IOP Publishing. - 0954-3899 .- 1361-6471. ; 50:1
  • Forskningsöversikt (refereegranskat)abstract
    • The nature of dark matter and properties of neutrinos are among the most pressing issues in contemporary particle physics. The dual-phase xenon time-projection chamber is the leading technology to cover the available parameter space for weakly interacting massive particles, while featuring extensive sensitivity to many alternative dark matter candidates. These detectors can also study neutrinos through neutrinoless double-beta decay and through a variety of astrophysical sources. A next-generation xenon-based detector will therefore be a true multi-purpose observatory to significantly advance particle physics, nuclear physics, astrophysics, solar physics, and cosmology. This review article presents the science cases for such a detector.
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2.
  • Koubarakis, M., et al. (författare)
  • From copernicus big data to extreme earth analytics
  • 2019
  • Ingår i: Advances in Database Technology - EDBT. - : OpenProceedings. - 9783893180813 ; , s. 690-693
  • Konferensbidrag (refereegranskat)abstract
    • Copernicus is the European programme for monitoring the Earth. It consists of a set of systems that collect data from satellites and in-situ sensors, process this data and provide users with reliable and up-to-date information on a range of environmental and security issues. The data and information processed and disseminated puts Copernicus at the forefront of the big data paradigm, giving rise to all relevant challenges, the so-called 5 Vs: volume, velocity, variety, veracity and value. In this short paper, we discuss the challenges of extracting information and knowledge from huge archives of Copernicus data. We propose to achieve this by scale-out distributed deep learning techniques that run on very big clusters offering virtual machines and GPUs. We also discuss the challenges of achieving scalability in the management of the extreme volumes of information and knowledge extracted from Copernicus data. The envisioned scientific and technical work will be carried out in the context of the H2020 project ExtremeEarth which starts in January 2019.
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