How To Model Supernovae in Simulations of Star and Galaxy Formation
Philip F. Hopkins (Caltech), Andrew Wetzel (UC Davis), Dusan Keres, (UCSD), Claude-Andre Faucher-Giguere (Northwestern), Eliot Quataert, (Berkeley), Michael Boylan-Kolchin (UT Austin), Norman Murray (CITA),, Christopher C. Hayward (Flatiron), Kareem El-Badry (Berkeley)

TL;DR
This paper introduces the FIRE-2 algorithm for modeling supernova feedback in galaxy simulations, ensuring conservation laws and resolution independence, leading to more accurate and converged galaxy formation results.
Contribution
The FIRE-2 algorithm provides a novel, resolution-independent method for implementing supernova feedback in various hydrodynamics simulations, improving convergence and physical accuracy.
Findings
FIRE-2 reproduces converged solutions across resolutions.
Traditional schemes diverge significantly at lower resolutions.
FIRE-2 converges faster than other sub-grid models without re-tuning.
Abstract
We study the implementation of mechanical feedback from supernovae (SNe) and stellar mass loss in galaxy simulations, within the Feedback In Realistic Environments (FIRE) project. We present the FIRE-2 algorithm for coupling mechanical feedback, which can be applied to any hydrodynamics method (e.g. fixed-grid, moving-mesh, and mesh-less methods), and black hole as well as stellar feedback. This algorithm ensures manifest conservation of mass, energy, and momentum, and avoids imprinting 'preferred directions' on the ejecta. We show that it is critical to incorporate both momentum and thermal energy of mechanical ejecta in a self-consistent manner, accounting for SNe cooling radii when they are not resolved. Using idealized simulations of single SN explosions, we show that the FIRE-2 algorithm, independent of resolution, reproduces converged solutions in both energy and momentum. In…
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