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Register a new userStar Formation and Clumps in Cosmological Galaxy Simulations with Radiation Pressure Feedback
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Cosmological simulations of galaxies have typically produced too many stars at early times. We study the global and morphological effects of radiation pressure (RP) in eight pairs of high-resolution cosmological galaxy formation simulations. We find that the additional feedback suppresses star formation globally by a factor of ~2. Despite this reduction, the simulations still overproduce stars by a factor of ~2 with respect to the predictions provided by abundance matching methods for halos more massive than 5E11 Msun/h (Behroozi, Wechsler & Conroy 2013). We also study the morphological impact of radiation pressure on our simulations. In simulations with RP the average number of low mass clumps falls dramatically. Only clumps with stellar masses Mclump/Mdisk <= 5% are impacted by the inclusion of RP, and RP and no-RP clump counts above this range are comparable. The inclusion of RP depresses the contrast ratios of clumps by factors of a few for clump masses less than 5% of the disk masses. For more massive clumps, the differences between and RP and no-RP simulations diminish. We note however, that the simulations analyzed have disk stellar masses below about 2E10 Msun/h. By creating mock Hubble Space Telescope observations we find that the number of clumps is slightly reduced in simulations with RP. However, since massive clumps survive the inclusion of RP and are found in our mock observations, we do not find a disagreement between simulations of our clumpy galaxies and observations of clumpy galaxies. We demonstrate that clumps found in any single gas, stellar, or mock observation image are not necessarily clumps found in another map, and that there are few clumps common to multiple maps.
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Over the last decades, cosmological simulations of galaxy formation have been instrumental for advancing our understanding of structure and galaxy formation in the Universe. These simulations follow the non-linear evolution of galaxies modeling a variety of physical processes over an enormous range of scales. A better understanding of the physics relevant for shaping galaxies, improved numerical methods, and increased computing power have led to simulations that can reproduce a large number of observed galaxy properties. Modern simulations model dark matter, dark energy, and ordinary matter in an expanding space-time starting from well-defined initial conditions. The modeling of ordinary matter is most challenging due to the large array of physical processes affecting this matter component. Cosmological simulations have also proven useful to study alternative cosmological models and their impact on the galaxy population. This review presents a concise overview of the methodology of cosmological simulations of galaxy formation and their different applications.
We present results from seventy-one zoom simulations of a Milky Way-sized (MW) halo, exploring the parameter space for a widely-used star formation and feedback model in the {tt Enzo} simulation code. We propose a novel way to match observations, using functional fits to the observed baryon makeup over a wide range of halo masses. The model MW galaxy is calibrated using three parameters: the star formation efficiency $left(f_*right)$, the efficiency of thermal energy from stellar feedback $left(epsilonright)$ and the region into which feedback is injected $left(r {rm and} sright)$. We find that changing the amount of feedback energy affects the baryon content most significantly. We then identify two sets of feedback parameter values that are both able to reproduce the baryonic properties for haloes between $10^{10},mathrm{M_odot}$ and $10^{12},mathrm{M_odot}$. We can potentially improve the agreement by incorporating more parameters or physics. If we choose to focus on one property at a time, we can obtain a more realistic halo baryon makeup. We show that the employed feedback prescription is insensitive to dark matter mass resolution between $10^5,{rm M_odot}$ and $10^7,{rm M_odot}$. Contrasting both star formation criteria and the corresponding combination of optimal feedback parameters, we also highlight that feedback is self-consistent: to match the same baryonic properties, with a relatively higher gas to stars conversion efficiency, the feedback strength required is lower, and vice versa. Lastly, we demonstrate that chaotic variance in the code can cause deviations of approximately 10% and 25% in the stellar and baryon mass in simulations evolved from identical initial conditions.
We investigate the spatially-resolved star formation relation using a galactic disk formed in a comprehensive high-resolution (3.8 pc) simulation. Our new implementation of stellar feedback includes ionizing radiation as well as supernova explosions, and we handle ionizing radiation by solving the radiative transfer equation rather than by a subgrid model. Photoheating by stellar radiation stabilizes gas against Jeans fragmentation, reducing the star formation rate. Because we have self-consistently calculated the location of ionized gas, we are able to make spatially-resolved mock observations of star formation tracers, such as H-alpha emission. We can also observe how stellar feedback manifests itself in the correlation between ionized and molecular gas. Applying our techniques to the disk in a galactic halo of 2.3e11 Msun, we find that the correlation between star formation rate density (estimated from mock H-alpha emission) and molecular hydrogen density shows large scatter, especially at high resolutions of <~ 75 pc that are comparable to the size of giant molecular clouds (GMCs). This is because an aperture of GMC size captures only particular stages of GMC evolution, and because H-alpha traces hot gas around star-forming regions and is displaced from the molecular hydrogen peaks themselves. By examining the evolving environment around star clusters, we speculate that the breakdown of the traditional star formation laws of the Kennicutt-Schmidt type at small scales is further aided by a combination of stars drifting from their birthplaces, and molecular clouds being dispersed via stellar feedback.
Here we introduce GAMESH, a novel pipeline which implements self-consistent radiative and chemical feedback in a computational model of galaxy formation. By combining the cosmological chemical-evolution model GAMETE with the radiative transfer code CRASH, GAMESH can post process realistic outputs of a N-body simulation describing the redshift evolution of the forming galaxy. After introducing the GAMESH implementation and its features, we apply the code to a low-resolution N-body simulation of the Milky Way formation and we investigate the combined effects of self-consistent radiative and chemical feedback. Many physical properties, which can be directly compared with observations in the Galaxy and its surrounding satellites, are predicted by the code along the merger-tree assembly. The resulting redshift evolution of the Local Group star formation rates, reionisation and metal enrichment along with the predicted Metallicity Distribution Function of halo stars are critically compared with observations. We discuss the merits and limitations of the first release of GAMESH, also opening new directions to a full implementation of feedback processes in galaxy formation models by combining semi-analytic and numerical methods.
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 contrast, common fully-thermal (energy-dump) or fully-kinetic (particle-kicking) schemes in the literature depend strongly on resolution: when applied at mass resolution >100 solar masses, they diverge by orders-of-magnitude from the converged solution. In galaxy-formation simulations, this divergence leads to orders-of-magnitude differences in galaxy properties, unless those models are adjusted in a resolution-dependent way. We show that all models that individually time-resolve SNe converge to the FIRE-2 solution at sufficiently high resolution. However, in both idealized single-SN simulations and cosmological galaxy-formation simulations, the FIRE-2 algorithm converges much faster than other sub-grid models without re-tuning parameters.
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