Thesis Open Access

PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware

Huebl, Axel


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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>The presented thesis establishes simulations on modern massively parallel computing hardware to investigate relativistic laser-driven plasmas. The latter are of special interest as they may provide a compact source for energetic ion beams. Computer simulations provide valuable insight into ultrafast plasma processes, evolving in the ultrahigh intensity (I<sub>0</sub> \u226b 10<sup>18</sup> W/cm<sup>2</sup>) focus of the ultrashort (\ud835\udf0f<sub>0</sub>=30-500 fs) laser pulses driving the interaction. Such simulations require high numerical resolution and full geometric treatment for reliable predictions, which can only be addressed with high-performance computing. The open source particle-in-cell code PIConGPU, which is developed in the framework of this thesis, answers these demands, providing speed and scalability to run on the world&#39;s largest supercomputers. PIConGPU is designed with a modular and extensible implementation, allowing to compute on current and upcoming hardware from a single code base. Furthermore, challenges arising for generated data rates, reaching 1 PByte per simulation, are resolved with scalable data reduction techniques and novel workflows, such as interactive simulations.</p>\n\n<p>Numerical studies are performed on two novel targets for laser-proton acceleration with near-critical and mass-limited properties. A micrometer-scale spherical target is explored with realistic temporal laser contrast, providing an interpretation for experimental results collected at the PW-class laser system PHELIX (\ud835\udf0f<sub>0</sub>=500 fs pulse length). In this study, 3D modeling with the GPU supercomputer Titan enabled the identification of pre-expansion to near-critical target conditions, which uncovers a regime of volumetric laser-electron interaction generating a highly directed proton beam. Furthermore, a novel cryogenic hydrogen jet target is researched in close collaboration to experiments at the laser system DRACO (\ud835\udf0f<sub>0</sub>=30 fs). This target system provides a unique setup for the isolated investigation of multi-species effects and their influence on the generated ion energy distribution. A novel analytical model provides a link between characteristic modulations in the ion energy spectra and ensemble properties of the microscopic electron distribution. In view of a potential experimental realization, parametric scans are performed confirming the feasibility of the proposed setup.</p>", 
  "license": "http://creativecommons.org/licenses/by-sa/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Helmholtz-Zentrum Dresden-Rossendorf and TU Dresden", 
      "@id": "https://orcid.org/0000-0003-1943-7141", 
      "@type": "Person", 
      "name": "Huebl, Axel"
    }
  ], 
  "url": "https://zenodo.org/record/3266820", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "contributor": [
    {
      "affiliation": "Helmholtz-Zentrum Dresden-Rossendorf", 
      "@id": "https://orcid.org/0000-0002-8258-3881", 
      "@type": "Person", 
      "name": "Dr. Bussmann, Michael"
    }, 
    {
      "affiliation": "Helmholtz-Zentrum Dresden-Rossendorf", 
      "@id": "https://orcid.org/0000-0003-4861-5584", 
      "@type": "Person", 
      "name": "Dr. Kluge, Thomas"
    }
  ], 
  "datePublished": "2019-07-03", 
  "headline": "PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware", 
  "keywords": [
    "laser-plasma acceleration", 
    "modeling", 
    "HPC", 
    "GPU", 
    "laser-ion acceleration", 
    "exascale computing", 
    "open source", 
    "open data"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3266820", 
  "@id": "https://doi.org/10.5281/zenodo.3266820", 
  "@type": "ScholarlyArticle", 
  "name": "PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware"
}
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