Abstract
ABSTRACT Smoothed particle hydrodynamics (SPH) is a ubiquitous numerical method for solving the fluid equations, and is prized for its conservation properties, natural adaptivity, and simplicity. We introduce the Sphenix SPH scheme, which was designed with three key goals in mind: to work well with sub-grid physics modules that inject energy, be highly computationally efficient (both in terms of compute and memory), and to be Lagrangian. sphenix uses a Density-Energy equation of motion, along with a variable artificial viscosity and conduction, including limiters designed to work with common sub-grid models of galaxy formation. In particular, we present and test a novel limiter that prevents conduction across shocks, preventing spurious radiative losses in feedback events. Sphenix is shown to solve many difficult test problems for traditional SPH, including fluid mixing and vorticity conservation, and it is shown to produce convergent behaviour in all tests where this is appropriate. Crucially, we use the same parameters within sphenix for the various switches throughout, to demonstrate the performance of the scheme as it would be used in production simulations. sphenix is the new default scheme in the swift cosmological simulation code and is available open source.
Highlights
The top row shows the Sphenix scheme without any artificial conduction enabled and highlights the typical end state for a Density-Energy Smoothed Particle Hydrodynamics (SPH) scheme on this problem
The rate of mixing of the blob is broadly consistent with that of modern SPH schemes and grid codes, our set of initial conditions appear to mix slightly slower than those used by other contemporary works (Agertz et al 2007; Read & Hayfield 2012; Hu et al 2014), ceed from a very basic particle set-up with a perfectly sharp contact
The cored central entropy profile with Sphenix is attained primarily due to the artificial conduction scheme and is not due to the other improvements over the traditional SPH base scheme
Summary
TED those presented in Monaghan (1997), but the key that led to the I community rallying around Gadget-2 was both its open source na-. In Heß & Springel (2010), the authors experimented with an extension to Gadget-2 using a Voronoi mesh to reduce errors inherrent in SPH and allow for better results on fluid mixing problems, eventually giving rise to the AREPO moving mesh scheme, allowing for significantly improved accuracy per particle but drastically increasing computational cost (Springel 2010; Weinberger, Springel & Pakmor 2020). In this case, the authors have steadily increased their computational cost per particle in an attempt to reduce errors inherrent in their hydrodynamics model as. These processes include radiative cooling, which has progressed from a simple one parameter model
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