4/3/2023 0 Comments Parallels toolbox 4.1.1 keyThis technological surge (and the ingenuity of the researchers themselves) has enabled us to shed light on many longstanding issues in high-energy astrophysics, including shocks (e.g., Frederiksen et al. We have recently arrived in the petaflop (10 15 floating-point operations per second, FLOPS) supercomputing era, and have started to pave our way toward exascale computing systems (10 18 FLOPS). 1992).Īn important factor in accelerating the use of plasma simulations is the ever-increasing computational speed and number of processors. In the early days, the research was mainly motivated by studies of basic plasma instabilities and confinement in fusion experiments, but the method of computationally solving the dynamics of charged particles quickly gained popularity also in understanding plasma in space (see, e.g., Tanaka 1983 Langdon et al. 1 IntroductionĮver since the introduction of computers, numerical simulations have been used to study the nonlinear behavior of plasma (see, e.g., Buneman 1959 Dawson 1962, 1964). Subscribe to A&A to support open access publication. This article is published in open access under the Subscribe-to-Open model. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License ( ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Here, we showcase the framework’s relativistic particle-in-cell (PIC) module by presenting (i) 1D simulations of relativistic Weibel instability, (ii) 2D simulations of relativistic kinetic turbulence in a suddenly stirred magnetically-dominated pair plasma, and (iii) 3D simulations of collisionless shocks in an unmagnetized medium. The framework supports heterogeneous multiphysics simulations in which different physical solvers can be combined and run simultaneously. The code can be run on various computing platforms ranging from laptops (shared-memory systems) to massively parallel supercomputer architectures (distributed-memory systems). The framework has a modular object-oriented design that allows the user to easily add new numerical algorithms to the system. The hybrid program design ensures good code performance together with ease of use. High-level functionality is operated with Python scripts. Computationally intensive low-level kernels are written in modern C++ taking advantage of polymorphic classes, multiple inheritance, and template metaprogramming. It is designed to function as an easy-to-extend general toolbox for simulating astrophysical plasmas with different theoretical and numerical models. Physics Department and Columbia Astrophysics Laboratory, Columbia University,Ĭenter for Computational Astrophysics, Flatiron Institute,Į-mail: is a new open-source plasma simulation framework implemented in C++ and Python. Nordita, KTH Royal Institute of Technology and Stockholm University,
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