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Register a new userOsaka Feedback Model: Isolated Disk Galaxy Simulations
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We study various implementations of supernova feedback model and present the results of our `Osaka feedback model using isolated galaxy simulations performed by the smoothed particle hydrodynamics (SPH) code {small GADGET-3}. Our model is a modified version of Stinson et al.s work, and we newly add the momentum kick for SN feedback rather than only thermal feedback. We incorporate the physical properties of SN remnants from the results of Chevalier and McKee & Ostriker, such as the effective radius of SN bubble and the remnant life-time, in the form of Sedov-Taylor (ST)-like solutions with the effect of radiative cooling. Our model utilizes the local, physical parameters such as density and temperature of the ISM rather than galactic or halo properties to determine the galactic wind velocity or mass-loading factor. The Osaka model succeeds in self-regulating star formation, and naturally produces galactic outflow with variable velocities depending on the local environment and available SN energy as a function of time.An important addition to our previous work by Aoyama et al. is the implementation of the {small CELib} chemistry library which allows us to deal with the time-dependent input of energy and metal yields for type Ia & II supernovae (SNe) and asymptotic giant branch (AGB) stars. As initial tests of our model, we apply it to isolated galaxy simulations, and examine various galactic properties and compare with observational data including metal abundances.
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Using an isolated Milky Way-mass galaxy simulation, we compare results from 9 state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt-Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly-formed stellar clump mass functions show more significant variation (difference by up to a factor of ~3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low density region, and between more diffusive and less diffusive schemes in the high density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.
We study the magnetic field evolution of an isolated spiral galaxy, using isolated Milky Way-mass galaxy formation simulations and a novel prescription for magnetohydrodynamic (MHD) supernova feedback. Our main result is that a galactic dynamo can be seeded and driven by supernova explosions, resulting in magnetic fields whose strength and morphology is consistent with observations. In our model, supernovae supply thermal energy, and a low level magnetic field along with their ejecta. The thermal expansion drives turbulence, which serves a dual role by efficiently mixing the magnetic field into the interstellar medium, and amplifying it by means of turbulent dynamo. The computational prescription for MHD supernova feedback has been implemented within the publicly available ENZO code, and is fully described in this paper. This improves upon ENZOs existing modules for hydrodynamic feedback from stars and active galaxies. We find that the field attains $mu G$-levels over Gyr-time scales throughout the disk. The field also develops large-scale structure, which appears to be correlated with the disks spiral arm density structure. We find that seeding of the galactic dynamo by supernova ejecta predicts a persistent correlation between gas metallicity and magnetic field strength. We also generate all-sky maps of the Faraday rotation measure from the simulation-predicted magnetic field, and present a direct comparison with observations.
In this study, we present and validate a variation of recently-developed physically motivated sub-grid prescriptions for supernova feedback that account for the unresolved energy-conserving phase of the bubble expansion. Our model builds upon the implementation publicly available in the mesh-less hydrodynamic code GIZMO, and is coupled with the chemistry library KROME. Here, we test it against different setups, to address how it affects the formation/dissociation of molecular hydrogen (H$_2$). First, we explore very idealised conditions, to show that it can accurately reproduce the terminal momentum of the blast-wave independent of resolution. Then, we apply it to a suite of numerical simulations of an isolated Milky Way-like galaxy and compare it with a similar run employing the delayed-cooling sub-grid prescription. We find that the delayed-cooling model, by pressurising ad-hoc the gas, is more effective in suppressing star formation. However, to get this effect, it must maintain the gas warm/hot at densities where it is expected to cool efficiently, artificially changing the thermo-chemical state of the gas, and reducing the H$_2$ abundance even in dense gas. Mechanical feedback, on the other hand, is able to reproduce the H$_2$ column densities without altering the gas thermodynamics, and, at the same time, drives more powerful outflows. However, being less effective in suppressing star formation, it over-predicts the Kennicutt-Schmidt relation by a factor of about 2.5. Finally, we show that the model is consistent at different resolution levels, with only mild differences.
Various heuristic approaches to model unresolved supernova (SN) feedback in galaxy formation simulations exist to reproduce the formation of spiral galaxies and the overall inefficient conversion of gas into stars. Some models, however, require resolution dependent scalings. We present a sub-resolution model representing the three major phases of supernova blast wave evolution $-$free expansion, energy conserving Sedov-Taylor, and momentum conserving snowplow$-$ with energy scalings adopted from high-resolution interstellar-medium simulations in both uniform and multiphase media. We allow for the effects of significantly enhanced SN remnant propagation in a multiphase medium with the cooling radius scaling with the hot volume fraction, $f_{mathrm{hot}}$, as $(1 - f_{mathrm{hot}})^{-4/5}$. We also include winds from young massive stars and AGB stars, Stromgren sphere gas heating by massive stars, and a gas cooling limiting mechanism driven by radiative recombination of dense HII regions. We present initial tests for isolated Milky-Way like systems simulated with the GADGET based code SPHgal with improved SPH prescription. Compared to pure thermal SN input, the model significantly suppresses star formation at early epochs, with star formation extended both in time and space in better accord with observations. Compared to models with pure thermal SN feedback, the age at which half the stellar mass is assembled increases by a factor of 2.4, and the mass loading parameter and gas outflow rate from the galactic disk increase by a factor of 2. Simulation results are converged for a two order of magnitude variation in particle mass in the range (1.3$-$130)$times 10^4$ solar masses.
Direct comparisons between galaxy simulations and observations that both reach scales < 100 pc are strong tools to investigate the cloud-scale physics of star formation and feedback in nearby galaxies. Here we carry out such a comparison for hydrodynamical simulations of a Milky Way-like galaxy, including stochastic star formation, HII region and supernova feedback, and chemical post-processing at 8 pc resolution. Our simulation shows excellent agreement with almost all kpc-scale and larger observables, including total star formation rates, radial profiles of CO, HI, and star formation through the galactic disc, mass ratios of the ISM components, both whole-galaxy and resolved Kennicutt-Schmidt relations, and giant molecular cloud properties. However, we find that our simulation does not reproduce the observed de-correlation between tracers of gas and star formation on < 100 pc scales, known as the star formation uncertainty principle, which indicates that observed clouds undergo rapid evolutionary lifecycles. We conclude that the discrepancy is driven by insufficiently-strong pre-supernova feedback in our simulation, which does not disperse the surrounding gas completely, leaving star formation tracer emission too strongly associated with molecular gas tracer emission, inconsistent with observations. This result implies that the cloud-scale de-correlation of gas and star formation is a fundamental test for feedback prescriptions in galaxy simulations, one that can fail even in simulations that reproduce all other macroscopic properties of star-forming galaxies.
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