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Kevin J Bowers

Publications and source records attributed to Kevin J Bowers.

2 recordsLinked to original sources

Theory of laser acceleration of light-ion beams from interaction of ultrahigh-intensity lasers with layered targets.

Experiments at the LANL Trident facility demonstrated the production of monoenergetic ion beams from the interaction of an ultraintense laser with a target comprising a heavy ion substrate and thin layer of light ions. An analytic model is obtained that predicts how the mean energy and quality of monoenergetic ion beams and the energy of substrate ions vary with substrate material and light-ion layer composition and thickness. Dimensionless parameters controlling the dynamics are derived and the model is validated with particle-in-cell simulations and experimental data.

Journal Article↗

The midpoint method for parallelization of particle simulations.

The evaluation of interactions between nearby particles constitutes the majority of the computational workload involved in classical molecular dynamics (MD) simulations. In this paper, we introduce a new method for the parallelization of range-limited particle interactions that proves particularly suitable to MD applications. Because it applies not only to pairwise interactions but also to interactions involving three or more particles, the method can be used for evaluation of both nonbonded and bonded forces in a MD simulation. It requires less interprocessor data transfer than traditional spatial decomposition methods at all but the lowest levels of parallelism. It gains an additional practical advantage in certain commonly used interprocessor communication networks by distributing the communication burden more evenly across network links and by decreasing the associated latency. When used to parallelize MD, it further reduces communication requirements by allowing the computations associated with short-range nonbonded interactions, long-range electrostatics, bonded interactions, and particle migration to use much of the same communicated data. We also introduce certain variants of this method that can significantly improve the balance of computational load across processors.

Algorithms↗