Computer Simulations of Plasmas and Beams: A View From Multiple Angles
Lawrence Livermore National Laboratory
2017 Charles K. Birdsall Award Recipient
Physical science and engineering practice have been, over most of history, advanced through experimentation and observation, along with analysis, calculations, and analog simulation. The use of digital computer simulations is a relatively recent development, but has matured rapidly and is now a full peer to the classical approaches.
In the fields of plasmas and particle beams, such simulations have been especially effective. Here, the underlying physical processes are largely understood, and equations describing the fundamental dynamics to good approximation (e.g., the Vlasov-Maxwell set) are known. However, first-principles treatments are (more often than not) intractable. Thus, considerable innovation of descriptive models and the methods of their solution has taken place over recent decades. The development of efficient computer models embodying a suitable level of description has thus been a central element of computational plasma and beam physics. The speed of at least some computations has benefited more from algorithmic innovation than from computer hardware advances1.
The author has had the privilege of participating in this enterprise, and in this talk seeks to illustrate how topics arose and interacted over the course of his career. Themes such as the nature of collective behaviors, avoidance of numerical instability, appropriately accurate single-particle motion, and the value of user-programmable software appeared repeatedly.
The presentation will touch on simulations of field-reversed ion rings, implicit techniques, laser raytracing for inertial fusion, beam physics for heavy-ion inertial fusion (using the Warp code, and reduced models), and other applications2-6.
1. “Software Progress Beats Moore’s Law,” New York Times, March 7, 2011, and comments thereto.
2. A. Friedman, A. B. Langdon, and B. I. Cohen, “A Direct Method for Implicit Particle-in-Cell Simulation,” Comments on Plasma Phys. and Controlled Fusion 6, 225 (1981).
3. A. Friedman, R. N. Sudan, and J. Denavit, “Stability of Field Reversed Ion Rings,” Phys. Fluids 29, 3317 (1986).
4. A. Friedman and S. P. Auerbach, “Numerically Induced Stochasticity,” J. Comput. Phys. 93, 171 (1991) et seq.
5. A. Friedman, et al., “Beam dynamics of the Neutralized Drift Compression Experiment-II, a novel pulse-compressing ion accelerator,” Phys. Plasmas 17, 056704 (2010).
6. A. Friedman, et al., “Computational Methods in the Warp Code Framework for Kinetic Simulations of Particle Beams and Plasmas,” IEEE Trans. Plasma Phys. 42, 1321 (2014).