Thesis Open Access

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

Huebl, Axel

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<dc:contributor>Dr. Bussmann, Michael</dc:contributor>
<dc:contributor>Dr. Kluge, Thomas</dc:contributor>
<dc:creator>Huebl, Axel</dc:creator>
<dc:date>2019-07-03</dc:date>
<dc:description>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 (I0 ≫ 1018 W/cm2) focus of the ultrashort (𝜏0=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'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.

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 (𝜏0=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 (𝜏0=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.</dc:description>
<dc:description>This is the dissertation of Axel Huebl (German spelling: Hübl) to achieve the academic degree Doctor rerum naturalium (Dr. rer. nat.). The thesis was defended on July 25th, 2019 at Technische Universität Dresden and was assessed with the grade "summa cum laude" (with highest distinction).

This research used resources of the Oak Ridge Leadership Computing Facility at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This project received funding within the MEPHISTO project (BMBF-Förderkennzeichen 01IH16006C). The GPU Center of Excellence Dresden provided a framework for many fruitful projects and travel funding, sponsored by the Nvidia Corporation.</dc:description>
<dc:identifier>https://zenodo.org/record/3266820</dc:identifier>
<dc:identifier>10.5281/zenodo.3266820</dc:identifier>
<dc:identifier>oai:zenodo.org:3266820</dc:identifier>
<dc:language>eng</dc:language>
<dc:relation>info:eu-repo/grantAgreement/EC/H2020/654220/</dc:relation>
<dc:relation>doi:10.5281/zenodo.3266819</dc:relation>
<dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
<dc:subject>laser-plasma acceleration</dc:subject>
<dc:subject>modeling</dc:subject>
<dc:subject>HPC</dc:subject>
<dc:subject>GPU</dc:subject>
<dc:subject>laser-ion acceleration</dc:subject>
<dc:subject>exascale computing</dc:subject>
<dc:subject>open source</dc:subject>
<dc:subject>open data</dc:subject>
<dc:title>PIConGPU: Predictive Simulations of Laser-Particle Accelerators with Manycore Hardware</dc:title>
<dc:type>info:eu-repo/semantics/doctoralThesis</dc:type>
<dc:type>publication-thesis</dc:type>
</oai_dc:dc>

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