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Area of Science:

  • Astrophysical fluid dynamics
  • Computational physics
  • Numerical methods

Background:

  • Radiation-hydrodynamics (RHD) simulations are computationally intensive due to vast differences in timescales and process importance.
  • Existing numerical methods struggle to efficiently handle these broad ranges across computational domains.

Purpose of the Study:

  • To introduce a novel implicit-explicit numerical method for non-relativistic RHD.
  • To address the challenges of broad timescales and varying process importance in RHD simulations.
  • To develop a method suitable for modern high-performance computing architectures.

Main Methods:

  • Developed an implicit-explicit RHD scheme based on moments.
  • Ensured machine-precision conservation of energy and momentum.
  • Implemented the method in the GPU-accelerated RHD code, quokka.

Main Results:

  • The method achieves machine-precision conservation of energy and momentum.
  • It requires minimal communication, suitable for massively parallel and GPU systems.
  • Demonstrated asymptotic accuracy in streaming, static diffusion, dynamic diffusion, and asymptotic diffusion regimes.
  • Successfully passed a wide range of numerical tests.

Conclusions:

  • The new implicit-explicit RHD method offers a robust and efficient solution for complex astrophysical simulations.
  • Its design makes it highly suitable for adaptive mesh refinement and massively parallel computing environments.
  • The method accurately handles various physical regimes, including unresolved photon mean-free paths.