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Approaching predictive capabilities for LWFA experiments with PIConGPU

Pausch, R.; Couperus Cabadağ, J. P.; Garten, M.; Hübl, A.; Köhler, A.; Kurz, T.; Schöbel, S.; Schramm, U.; Steiniger, K.; Widera, R.; Zarini, O.; Irman, A.; Bussmann, M.; Debus, A.

State-of-the-art particle-in-cell simulations are becoming faster in terms of time to solution by utilizing modern hardware accelerators like GPUs and more accurate by improving the underlying algorithms. However, in order to model experiments, methods to include realistic laser pulses and gas distributions as well as efficient techniques to predict experimental observables, so-called synthetic diagnostics, need to be included in these simulations.

In this talk, we present extensions to the particle-in-cell code PIConGPU that were essential to accurately model LWFA experiments based on self-truncated ionization injection performed at HZDR. We discuss the significant impact of the implementation of higher order laser modes on the plasma dynamics and the resulting acceleration process. Furthermore, we discuss in detail the advantage of efficient in situ data analysis on the example of studying electron phase space evolution and of predicting spectrally and directionally radiation emission by all particles.

These improvements set the stage for quantitatively predicting the results of experiments in the near future.

Keywords: PIConGPU; LWFA; radiation; synthetic diagnostics

  • Lecture (Conference)
    DPG-Frühjahrstagung der Sektion Materie und Kosmos (SMuK), 18.-22.03.2019, München, Deutschland

Permalink: https://www.hzdr.de/publications/Publ-29256
Publ.-Id: 29256