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Abstract We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback and magnetic fields, to investigate the effectiveness of different fitting methods for volume and column density probability distribution functions (PDFs). The first method fits a piecewise lognormal and power-law (PL) function to recover PDF parameters such as the PL slope and transition density. The second method fits a polynomial spline function and examines the first and second derivatives of the spline to determine the PL slope and the functional transition density. The first PL (set by the transition between lognormal and PL function) can also be visualized in the derivatives directly. In general, the two methods produce fits that agree reasonably well for volume density but vary for column density, likely due to the increased statistical noise in the column density PDFs as compared to the volume density PDFs. We test a well-known conversion for estimating volume density PL slopes from column density slopes and find that the spline method produces a better match (χ²of 3.34 versusχ²of 5.92), albeit with a significant scatter. Ultimately, we recommend the use of both fitting methods on column density data to mitigate the effects of noise. 

ABSTRACT We present an investigation of clustered stellar feedback in the form of superbubbles identified within 11 galaxies from the FIRE-2 (Feedback in Realistic Environments) cosmological zoom-in simulation suite, at both cosmic noon (1 < z < 3) and in the local universe. We study the spatially resolved multiphase outflows that these supernovae drive, comparing our findings with recent theory and observations. These simulations consist of five Large Magellanic Cloud–mass galaxies and six Milky Way-mass progenitors (with a minimum baryonic particle mass of $$m_{\rm b.min} = 7100\,{\rm M}_{\odot }$$). For all galaxies, we calculate the local and galaxy-averaged mass and energy-loading factors from the identified outflows. We also characterize the multiphase morphology and properties of the identified superbubbles, including the ‘shell’ of cool ($$T\lt 10^5$$ K) gas and break out of energetic hot ($$T\gt 10^5$$ K) gas when the shell bursts. We find that these simulations, regardless of redshift, have mass-loading factors and momentum fluxes in the cool gas that largely agree with recent observations. Lastly, we also investigate how methodological choices in measuring outflows can affect loading factors for galactic winds. 

Abstract The observed rest-UV luminosity function at cosmic dawn (z∼ 8–14) measured by JWST revealed an excess of UV-luminous galaxies relative to many prelaunch theoretical predictions. A high star formation efficiency (SFE) and a top-heavy initial mass function (IMF) are among the mechanisms proposed for explaining this excess. Although a top-heavy IMF has been proposed for its ability to increase the light-to-mass ratio (Ψ_UV), the resulting enhanced radiative pressure from young stars could decrease the SFE, potentially driving galaxy luminosities back down. In this Letter, we use idealized radiation hydrodynamic simulations of star cluster formation to explore the effects of a top-heavy IMF on the SFE of clouds typical of the high-pressure conditions found at these redshifts. We find that the SFE in star clusters with solar-neighborhood-like dust abundance decreases with increasingly top-heavy IMFs—by ∼20% for an increase of a factor of 4 in Ψ_UVand by 50% for a factor of ∼10 in Ψ_UV. However, we find that an expected decrease in the dust-to-gas ratio (∼0.01 × solar) at these redshifts can completely compensate for the enhanced light output. This leads to a (cloud-scale; ∼10 pc) SFE that is ≳70% even for a factor of 10 increase in Ψ_UV, implying that highly efficient star formation is unavoidable for high surface density and low-metallicity conditions. Our results suggest that a top-heavy IMF, if present, likely coexists with efficient star formation in these galaxies. 

Abstract Advancing our understanding of astrophysical turbulence is bottlenecked by the limited resolution of numerical simulations that may not fully sample scales in the inertial range. Machine-learning (ML) techniques have demonstrated promise in upscaling resolution in both image analysis and numerical simulations (i.e., superresolution). Here we employ and further develop a physics-constrained convolutional neural network ML model called “MeshFreeFlowNet” (MFFN) for superresolution studies of turbulent systems. The model is trained on both the simulation images and the evaluated partial differential equations (PDEs), making it sensitive to the underlying physics of a particular fluid system. We develop a framework for 2D turbulent Rayleigh–Bénard convection generated with theDedaluscode by modifying the MFFN architecture to include the full set of simulation PDEs and the boundary conditions. Our training set includes fully developed turbulence sampling Rayleigh numbers (Ra) ofRa= 10⁶–10¹⁰. We evaluate the success of the learned simulations by comparing the power spectra of the directDedalussimulation to the predicted model output and compare both ground-truth and predicted power spectral inertial range scalings to theoretical predictions. We find that the updated network performs well at allRastudied here in recovering large-scale information, including the inertial range slopes. The superresolution prediction is overly dissipative at smaller scales than that of the inertial range in all cases, but the smaller scales are better recovered in more turbulent than laminar regimes. This is likely because more turbulent systems have a rich variety of structures at many length scales compared to laminar flows. 

ABSTRACT ‘Runaway stars’ might play a role in driving galactic outflows and enriching the circumgalactic medium with metals. To study this effect, we carry out high-resolution dwarf galaxy simulations that include velocity ‘kicks’ to massive stars above eigth solar masses. We consider two scenarios, one that adopts a power law velocity distribution for kick velocities, resulting in more stars with high-velocity kicks, and a more moderate scenario with a Maxwellian velocity distribution. We explicitly resolve the multiphase interstellar medium (ISM) and include non-equilibrium cooling and chemistry. We sample individual massive stars from an IMF and follow their radiation input and SN feedback (core-collapse) channel at the end of their lifetime. In the simulations with runaway stars, we add additional (natal) velocity kicks that mimic two- and three-body interactions that cannot be fully resolved in our simulations. We find that including runaway or ‘walkaway’ star scenarios impacts mass, metal, momentum, and energy outflows as well as the corresponding loading factors. The effect on the mass loading factor is small, but we find an increase in the metal loading by a factor of 1.5 to 2. The momentum loading increases by a factor of 1.5–2. The energy loading increases by roughly a factor of 5 when runaway stars are included. Additionally, we find that the overall level of star formation is increased in the models that include runaway stars. We conclude that the inclusion of runaway stars could have an impact on the global star formation and subsequent outflow properties of dwarf galaxies. 

Abstract We investigate the conditions for the Hi-to-H₂transition in the solar neighborhood by analyzing Hiemission and absorption measurements toward 58 Galactic lines of sight (LOSs) along with¹²CO(1–0) (CO) and dust data. Based on the accurate column densities of the cold and warm neutral medium (CNM and WNM), we first perform a decomposition of gas into atomic and molecular phases, and show that the observed LOSs are mostly Hi-dominated. In addition, we find that the CO-dark H₂, not the optically thick Hi, is a major ingredient of the dark gas in the solar neighborhood. To examine the conditions for the formation of CO-bright molecular gas, we analyze the kinematic association between Hiand CO, and find that the CNM is kinematically more closely associated with CO than the WNM. When CNM components within CO line widths are isolated, we find the following characteristics: spin temperature < 200 K, peak optical depth > 0.1, CNM fraction of ∼0.6, andV-band dust extinction > 0.5 mag. These results suggest that CO-bright molecular gas preferentially forms in environments with high column densities where the CNM becomes colder and more abundant. Finally, we confront the observed CNM properties with the steady-state H₂formation model of Sternberg et al. and infer that the CNM must be clumpy with a small volume filling factor. Another possibility would be that missing processes in the model, such as cosmic-rays and gas dynamics, play an important role in the Hi-to-H₂transition. 

Abstract We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback, magnetic fields, and driven turbulence, to study the compression and expansion rates of the gas as functions of density. We show that, around the mean density, supersonic turbulence promotes rough equilibrium between the amounts of compressing and expanding gas, consistent with continuous gas cycling between high- and low-density states. We find that the inclusion of protostellar jets produces rapidly expanding and compressing low-density gas. We find that the gas mass flux peaks at the transition between the lognormal and power-law forms of the density probability distribution function (PDF). This is consistent with the transition density tracking the post-shock density, which promotes an enhancement of mass at this density (i.e., shock compression and filament formation). At high densities, the gas dynamics are dominated by self-gravity: the compression rate in all of our runs matches the rate of the run with only gravity, suggesting that processes other than self-gravity have little effect at these densities. The net gas mass flux becomes constant at a density below the sink formation threshold, where it equals the star formation rate. The density at which the net gas mass flux equals the star formation rate is one order of magnitude lower than our sink threshold density, corresponds to the formation of the second power-law tail in the density PDF, and sets the overall star formation rates of these simulations. 

Abstract 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. 

Abstract We employ the Feedback In Realistic Environments (FIRE-2) physics model to study how the properties of giant molecular clouds (GMCs) evolve during galaxy mergers. We conduct a pixel-by-pixel analysis of molecular gas properties in both the simulated control galaxies and galaxy major mergers. The simulated GMC pixels in the control galaxies follow a similar trend in a diagram of velocity dispersion (σ_v) versus gas surface density (Σ_mol) to the one observed in local spiral galaxies in the Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey. For GMC pixels in simulated mergers, we see a significant increase of a factor of 5–10 in both Σ_molandσ_v, which puts these pixels above the trend of PHANGS galaxies in theσ_vversus Σ_moldiagram. This deviation may indicate that GMCs in the simulated mergers are much less gravitationally bound compared with simulated control galaxies with virial parameters (α_vir) reaching 10–100. Furthermore, we find that the increase inα_virhappens at the same time as the increase in global star formation rate, which suggests that stellar feedback is responsible for dispersing the gas. We also find that the gas depletion time is significantly lower for high-α_virGMCs during a starburst event. This is in contrast to the simple physical picture that low-α_virGMCs are easier to collapse and form stars on shorter depletion times. This might suggest that some other physical mechanisms besides self-gravity are helping the GMCs in starbursting mergers collapse and form stars. 

Abstract We explore the role of galactic feedback on the low-redshift Lyα(Lyα) forest (z≲ 2) statistics and its potential to alter the thermal state of the intergalactic medium. Using the Cosmology and Astrophysics with Machine Learning Simulations (CAMELS) suite, we explore variations of the AGN and stellar feedback models in the IllustrisTNG and Simba subgrid models. We find that both AGN and stellar feedback in Simba play a role in setting the Lyαforest column density distribution function (CDD) and the Doppler width (b-value) distribution. The Simba AGN jet feedback mode is able to efficiently transport energy out to the diffuse IGM, causing changes in the shape and normalization of the CDD and a broadening of theb-value distribution. We find that stellar feedback plays a prominent role in regulating supermassive black hole growth and feedback, highlighting the importance of constraining stellar and AGN feedback simultaneously. In IllustrisTNG, the AGN feedback variations explored in CAMELS do not affect the Lyαforest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low-zLyαforest can be sensitive to changes in the ultraviolet background, stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM.