arXiv · 2605.16206
Kinetic Simulations of Laser-Driven Compression and Heating of Magnetised Cryogenic Hydrogen Targets using PIConGPU
Abstract
We present fully kinetic two-dimensional, three-velocity-component (2D3V) PIConGPU simulations of a three-beam direct-drive interaction with a 15 $\mu$m solid-density cryogenic hydrogen cylinder, establishing a predictive numerical baseline for the operational DRACO ($\tau=30$ fs) and upcoming PENELOPE ($\tau=150$ fs) laser facilities at HZDR. The simulations resolve charge-separation fields on the order of 3 TV/m and reveal a robust kinematic bifurcation of the accelerated population into a fast (1-5 MeV) ion beam and a slower bulk (1-100 keV) flow. We demonstrate analytically and numerically that the charge-separation front ($v_{hb}$) is an intrinsically non-quasi-neutral electrostatic double layer that lies outside the closure assumptions of radiation-hydrodynamic models. A simple $2v_{hb}$ reflection scaling derived directly from the front trajectory tracks the centroid of the constant-energy fast-ion band under the impulsive 30 fs driver and the time-varying upper edge of the swept fast-ion band under the sustained 150 fs driver, across both intensities ($a_{0}=12.7$ and 22.0), establishing this non-thermal mechanism as the dominant acceleration pathway. We then scan an external axial magnetic field from 0 T to 10 kT. Laboratory-achievable 20 T fields leave all macroscopic observables unchanged; fields at the kT scale progressively magnetise the MeV hot-electron population, quench the laser-driven charge-separation mechanism, suppress the fast-ion band, and more than double the net-inward compression time of the short-pulse driver-while extending the outer target envelope. A geometric equivalence argument maps these kT-scale results onto larger-diameter cryogenic hydrogen jets.
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Filip Optołowicz, Klaus Steiniger, David Blaschke, Michael Bussmann, Brian Marre. 2026-05-15. Kinetic Simulations of Laser-Driven Compression and Heating of Magnetised Cryogenic Hydrogen Targets using PIConGPU. https://arxiv.org/abs/2605.16206
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