The Astrophysical Journal (Jan 2023)

Code Comparison in Galaxy-scale Simulations with Resolved Supernova Feedback: Lagrangian versus Eulerian Methods

  • Chia-Yu Hu,
  • Matthew C. Smith,
  • Romain Teyssier,
  • Greg L. Bryan,
  • Robbert Verbeke,
  • Andrew Emerick,
  • Rachel S. Somerville,
  • Blakesley Burkhart,
  • Yuan Li,
  • John C. Forbes,
  • Tjitske Starkenburg

DOI
https://doi.org/10.3847/1538-4357/accf9e
Journal volume & issue
Vol. 950, no. 2
p. 132

Abstract

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We present a suite of high-resolution simulations of an isolated dwarf galaxy using four different hydrodynamical codes: Gizmo , Arepo , Gadget , and Ramses . All codes adopt the same physical model, which includes radiative cooling, photoelectric heating, star formation, and supernova (SN) feedback. Individual SN explosions are directly resolved without resorting to subgrid models, eliminating one of the major uncertainties in cosmological simulations. We find reasonable agreement on the time-averaged star formation rates as well as the joint density–temperature distributions between all codes. However, the Lagrangian codes show significantly burstier star formation, larger SN-driven bubbles, and stronger galactic outflows compared to the Eulerian code. This is caused by the behavior in the dense, collapsing gas clouds when the Jeans length becomes unresolved: Gas in Lagrangian codes collapses to much higher densities than that in Eulerian codes, as the latter is stabilized by the minimal cell size. Therefore, more of the gas cloud is converted to stars and SNe are much more clustered in the Lagrangian models, amplifying their dynamical impact. The differences between Lagrangian and Eulerian codes can be reduced by adopting a higher star formation efficiency in Eulerian codes, which significantly enhances SN clustering in the latter. Adopting a zero SN delay time reduces burstiness in all codes, resulting in vanishing outflows as SN clustering is suppressed.

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