Simulating galactic outflows with thermal supernova feedback
Claudio Dalla Vecchia, Joop Schaye

TL;DR
This paper introduces a stochastic thermal feedback method for galaxy simulations that effectively suppresses star formation and drives outflows by ensuring injected energy heats gas to a minimum temperature, overcoming radiative losses.
Contribution
The authors propose and validate a new stochastic thermal feedback technique that improves the efficiency of supernova energy injection in galaxy simulations, applicable to both particle and grid codes.
Findings
Strong suppression of star formation in simulated galaxies.
Generation of large-scale outflows without disabling radiative cooling.
Results become resolution-independent at high resolution.
Abstract
Cosmological simulations make use of sub-grid recipes for the implementation of galactic winds driven by massive stars because direct injection of supernova energy in thermal form leads to strong radiative losses, rendering the feedback inefficient. We argue that the main cause of the catastrophic cooling is a mismatch between the mass of the gas in which the energy is injected and the mass of the parent stellar population. Because too much mass is heated, the temperatures are too low and the cooling times too short. We use analytic arguments to estimate, as a function of the gas density and the numerical resolution, the minimum heating temperature that is required for the injected thermal energy to be efficiently converted into kinetic energy. We then propose and test a stochastic implementation of thermal feedback that uses this minimum temperature increase as an input parameter and…
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