A new class of accurate, mesh-free hydrodynamic simulation methods

By P. Hopkins. 2014

793 citations recorded by the source corpus.

We present two new Lagrangian methods for hydrodynamics, in a systematic comparison with moving-mesh, smoothed particle hydrodynamics (SPH), and stationary (non-moving) grid methods. The new methods are designed to simultaneously capture advantages of both SPH and grid-based/adaptive mesh refinement (AMR) schemes. They are based on a kernel discretization of the volume coupled to a high-order matrix gradient estimator and a Riemann solver acting over the volume ‘overlap’. We implement and test a parallel, second-order version of the method with self-gravity and cosmological integration, in the code gizmo:1 this maintains exact mass, energy and momentum conservation; exhibits superior angular momentum conservation compared to all other methods we study; does not require ‘artificial diffusion’ terms; and allows the fluid elements to move with the flow, so resolution is automatically adaptive. We consider a large suite of test problems, and find that on all problems the new methods appear competitive with moving-mesh schemes, with some advantages (particularly in angular momentum conservation), at the cost of enhanced noise. The new methods have many advantages versus SPH: proper convergence, good capturing of fluid-mixing instabilities, dramatically reduced ‘particle noise’ and numerical viscosity, more accurate sub-sonic flow evolution, and sharp shock-capturing. Advantages versus non-moving meshes include: automatic adaptivity, dramatically reduced advection errors and numerical overmixing, velocity-independent errors, accurate coupling to gravity, good angular momentum conservation and elimination of ‘grid alignment’ effects. We can, for example, follow hundreds of orbits of gaseous discs, while AMR and SPH methods break down in a few orbits. However, fixed meshes minimize ‘grid noise’. These differences are important for a range of astrophysical problems.

Subfields: Astronomy and Astrophysics, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/69e2220e5adfa465c55b335c0d13194f27e2a2ae

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Citations in the corpus

GRACKLE: a chemistry and cooling library for astrophysics (2016, neutral): “…et al. 2003, 2005) • Enzo (Bryan et al. 2014) • Gadget-3 (Springel 2005) • GAMER (Schive et al. 2010) • GASOLINE (Wadsley et al. 2004) • Gear (Revaz & Jablonka 2012b,a) • Gizmo (Hopkins 2015) • RAMSES (Teyssier 2002) • SPHS (Read & Hayfield 2012) • SWIFT (Gonnet et al. 2013; Schaller et al. 2016)”
BREATHING FIRE: HOW STELLAR FEEDBACK DRIVES RADIAL MIGRATION, RAPID SIZE FLUCTUATIONS, AND POPULATION GRADIENTS IN LOW-MASS GALAXIES (2015, methodology): “…simulations and other simulations that use explicit treatments of stellar feedback at high resolution with a high density threshold for star formation, nSF & 10 cm−3 (for example, Shen et al. 2014; Madau et al. 2014; Kawata et al. 2014; Hu et al. 2015; Sparre et al. 2015; Hayward & Hopkins 2015).”
Black holes on FIRE: stellar feedback limits early feeding of galactic nuclei (2017, methodology): “2 SI M U L AT I O N S We use the N-body+hydrodynamics code GIZMO2 (Hopkins 2015) to re-simulate four haloes from the A series of MassiveFIRE galaxies presented in Feldmann et al. (2017), which did not include BH physics.”
MUFASA: Galaxy Formation Simulations With Meshless Hydrodynamics (2016, methodology): “Compared to MassiveBlack-II, Mufasa employs a hydro solver that has been shown to yield better results for key test problems (Hopkins 2015), and additionally our outflow scalings better reproduce the observed GSMFs at the low-mass end.”
The cosmic baryon cycle and galaxy mass assembly in the FIRE simulations (2016, methodology): “…owing to a transition into a quiescent mode of star formation that does not drive large scale winds efficiently (Muratov et al. 2015; Hayward & Hopkins 2015), while (2) lower mass galaxies extend their bursty star formation histories down to lower redshift, continuously driving gas outflows…”
simba: Cosmological simulations with black hole growth and feedback (2019, methodology): “It performs very well in numerous standard hydrodynamics tests including strong shocks, rotating disks, and cold blobs moving through hot media (Hopkins 2015).”
RECONCILING DWARF GALAXIES WITH ΛCDM COSMOLOGY: SIMULATING A REALISTIC POPULATION OF SATELLITES AROUND A MILKY WAY–MASS GALAXY (2016, methodology): “GIZMO code and FIRE-2 model We run our simulations using the code GIZMO11 (Hopkins 2015) with the FIRE model for star formation and explicit feedback (Hopkins et al. 2014).”
The Local Group on FIRE: dwarf galaxy populations across a suite of hydrodynamic simulations (2018, methodology): “We also include the results of six simulations targeting isolated MW-mass haloes; all of these galaxies were also analysed in Garrison-Kimmel et al. (2018), but here we present higher resolution resimulations of m12b, m12c, and m12z that additionally include subgrid metal diffusion. m12b–m12m are pa”
Cold gas stripping in satellite galaxies: from pairs to clusters (2016, neutral): “…(2013) employ entropy-conserving smoothed particle hydrodynamics (SPH; Springel 2005) that has been shown to handle surface instabilities such as those that occur during gas stripping poorly compared to more recent hydrodynamics methods (see Agertz et al. 2007; Hopkins 2015; Schaller et al. 2015).”
Gravitational probes of dark matter physics (2017, background): “nsideration. Leaving aside improvements in the hydrodynamic modeling of gas and stellar evolution in galaxies, for which a vigorous program is underway in the galaxy simulation community (e.g., Refs. [430, 431, 432, 433, 434, 435, 436]), there are other technical challenges to achieve an accurate ca”
Theoretical Challenges in Galaxy Formation (2016, methodology): “The recent GIZMO implementation is based on the GADGET framework and shows some significant improvements on idealised test problems, in particular for low Mach number gas (Hopkins 2015).”
The EAGLE simulations of galaxy formation: the importance of the hydrodynamics scheme (2015, background): “For comprehensive descriptions and motivations, see the review by Price (2012) and the description of the alternative formalism by Hopkins (2013, 2015).”
FIRE-2 simulations: physics versus numerics in galaxy formation (2017, methodology): “While the methods will converge to an identical solution at sufficiently high resolution (Hopkins 2015), the concern is that at fixed resolution, MFM will under-estimate the metal-mixing owing to un-resolved smallscale eddies that should mix between the boundaries of neighboring resolution elements.”