High-Order Particle-in-Cell Algorithms for Laser Plasma Simulations
Laser-plasma interactions recently have been used to accelerate ~1 nC electron bunches to ~100 MeV over ~3 mm with ~5% energy spread. This result demonstrates the potential for reducing the size and cost of future high-energy accelerators by orders of magnitude. Massively parallel, particle-in-cell (PIC) simulations have correctly captured the qualitative features of these laser wakefield accelerator (LWFA) experiments and have played a key role in their success. Now, there is a strong need for the PIC software to move beyond the qualitative features to quantitative prediction and system optimization. In this project, several high-order algorithms will be implemented in a state-of-the-art parallel PIC code, with emphasis on reducing particle-driven noise and improving the dispersive properties of electromagnetic waves. The relative benefits of these algorithms will be tested via comparison with theory and with data from on-going LWFA experiments. In Phase I, high-risk technical issues will be resolved through the initial implementation and testing, in one and two dimensions, of high-order particle shapes. The numerically sensitive problem of resonant electron injection into the plasma wake, through the use of colliding laser pulses, will be used as a test case. Commercial Applications And Other Benefits as described by the Applicant: The algorithmic enhancements for the PIC simulation code should have application to scientific collaborators in the high-energy physics community.
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