A pairwise nuclear fusion algorithm for particle-in-cell simulations: Weighted particles at relativistic energies

D. Wu; Z. M. Sheng; W. Yu; S. Fritzsche; X. T. He

doi:10.1063/5.0051178

journal article·2021-07-01Open access

A pairwise nuclear fusion algorithm for particle-in-cell simulations: Weighted particles at relativistic energies

D. Wu, Z. M. Sheng, W. Yu, S. Fritzsche, X. T. He

AIP Advances· Volume 11· Issue 7

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Source abstract

Abstract

A pairwise nuclear fusion algorithm for particle-in-cell simulations for arbitrarily weighted macro-particles at relativistic energies is proposed. When comparing with a recent study by Higginson et al. [J. Comput. Phys. 388, 439 (2019)], our method is also fitted with the widely used Coulomb scattering algorithm by Nanbu and Yonemura [J. Comput. Phys. 145, 639 (1998)] and Sentoku and Kemp [J. Comput. Phys. 227, 6846 (2008)] and can be implemented into a particle-in-cell simulation code with marginal efforts. The algorithm is benchmarked in situations with like-particles, unlike-particles, thermonuclear plasmas, and beam–target fusion. It is shown that only 50–100 macro-particles per cell are needed for the repeatability of fusion yields around 1%.

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Research context

OpenAlex topics: Laser-Plasma Interactions and Diagnostics · Fusion materials and technologies · Magnetic confinement fusion research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute for Fusion Theory and Simulation, Department of Physics, Zhejiang University 1 , 310058 Hangzhou, China

Collaborative Innovation Center of IFSA, Shanghai Jiao Tong University 2 , Shanghai 200240, China

Shanghai Institute of Optics and Fine Mechanics 3 , 201800 Shanghai, China

Helmholtz Institut Jena and Theoretisch Physikalisches Institut, Friedrich Schiller University Jena 4 , D-07743 Jena, Germany

Key Laboratory of HEDP of the Ministry of Education, CAPT, and State Key Laboratory of Nuclear Physics and Technology, Peking University 5 , 100871 Beijing, China

Funding

Strategic Priority Research Program of Chinese Academy of Sciences · Science Challenge Project · National Natural Science Foundation of China

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