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  1. 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.

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  2. Abstract

    The James Webb Space Telescope (JWST) is capable of probing extremely early eras of our Universe, when the supersonic relative motions between dark matter and baryonic overdensities modulate structure formation (z≳ 10). We study low-mass galaxy formation, including this “stream velocity,” using high-resolutionAREPOhydrodynamics simulations and present theoretical predictions of the UV luminosity function (UVLF) and galaxy stellar mass function down to extremely faint and low-mass galaxies (MUV≳ −15, 104MM*≤ 108M). We show that, although the stream velocity suppresses early star formation overall, it induces a short period of rapid star formation in some larger dwarfs, leading to an enhancement in the faint end of the UVLF atz= 12. We demonstrate that JWST observations are close to this enhanced regime and propose that the UVLF may constitute an important probe of the stream velocity at high redshift for JWST and future observatories.

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  3. 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.

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  4. Abstract

    The formation mechanism of globular clusters (GCs) has long been debated by astronomers. It was recently proposed that supersonically induced gas objects (SIGOs)–which formed in the early Universe due to the supersonic relative motion of baryons and dark matter at recombination–could be the progenitors of early GCs. In order to become GCs, SIGOs must form stars relatively efficiently despite forming outside of dark matter halos. We investigate the potential for star formation in SIGOs using cosmological hydrodynamic simulations, including the aforementioned relative motions of baryons and dark matter, molecular hydrogen cooling in primordial gas clouds, and explicit star formation. We find that SIGOs do form stars and that the nascent star clusters formed through this process are accreted by dark matter halos on short timescales (∼a few hundred megayears). Thus, SIGOs may be found as intact substructures within these halos, analogous to many present-day GCs. From this result, we conclude that SIGOs are capable of forming star clusters with similar properties to globular clusters in the early Universe, and we discuss their detectability by upcoming JWST surveys.

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  5. 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.

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  6. Abstract

    An unprecedented array of new observational capabilities are starting to yield key constraints on models of the epoch of first light in the Universe. In this Letter we discuss the implications of the UV radiation background at cosmic dawn inferred by recent JWST observations for radio experiments aimed at detecting the redshifted 21 cm hyperfine transition of diffuse neutral hydrogen. Under the basic assumption that the 21 cm signal is activated by the Lyαphoton field produced by metal-poor stellar systems, we show that a detection at the low frequencies of the EDGES and SARAS3 experiments may be expected from a simple extrapolation of the declining UV luminosity density inferred atz≲ 14 from JWST early galaxy data. Accounting for an early radiation excess above the cosmic microwave background suggests a shallower or flat evolution to simultaneously reproduce low- and high-zcurrent UV luminosity density constraints, which cannot be entirely ruled out, given the large uncertainties from cosmic variance and the faint-end slope of the galaxy luminosity function at cosmic dawn. Our findings raise the intriguing possibility that a high star formation efficiency at early times may trigger the onset of intense Lyαemission at redshiftz≲ 20 and produce a cosmic 21 cm absorption signal 200 Myr after the Big Bang.

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  7. 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. 
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  8. 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 (σv) versus gas surface density (Σmol) 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 Σmolandσv, which puts these pixels above the trend of PHANGS galaxies in theσvversus Σmoldiagram. This deviation may indicate that GMCs in the simulated mergers are much less gravitationally bound compared with simulated control galaxies with virial parameters (αvir) reaching 10–100. Furthermore, we find that the increase inαvirhappens 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-αvirGMCs during a starburst event. This is in contrast to the simple physical picture that low-αvirGMCs 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.

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    Arkenstone is a new model for multiphase, stellar feedback-driven galactic winds designed for inclusion in coarse resolution cosmological simulations. In this first paper of a series, we describe the features that allow Arkenstone to properly treat high specific energy wind components and demonstrate them using idealized non-cosmological simulations of a galaxy with a realistic circumgalactic medium (CGM), using the arepo code. Hot, fast gas phases with low mass loadings are predicted to dominate the energy content of multiphase outflows. In order to treat the huge dynamic range of spatial scales involved in cosmological galaxy formation at feasible computational expense, cosmological volume simulations typically employ a Lagrangian code or else use adaptive mesh refinement with a quasi-Lagrangian refinement strategy. However, it is difficult to inject a high specific energy wind in a Lagrangian scheme without incurring artificial burstiness. Additionally, the low densities inherent to this type of flow result in poor spatial resolution. Arkenstone addresses these issues with a novel scheme for coupling energy into the transition region between the interstellar medium (ISM) and the CGM, while also providing refinement at the base of the wind. Without our improvements, we show that poor spatial resolution near the sonic point of a hot, fast outflow leads to an underestimation of gas acceleration as the wind propagates. We explore the different mechanisms by which low and high specific energy winds can regulate the star formation rate of galaxies. In future work, we will demonstrate other aspects of the Arkenstone model.

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    Feedback driven by jets from active galactic nuclei is believed to be responsible for reducing cooling flows in cool-core galaxy clusters. We use simulations to model feedback from hydrodynamic jets in isolated haloes. While the jet propagation converges only after the diameter of the jet is well resolved, reliable predictions about the effects these jets have on the cooling time distribution function only require resolutions sufficient to keep the jet-inflated cavities stable. Comparing different model variations, as well as an independent jet model using a different hydrodynamics code, we show that the dominant uncertainties are the choices of jet properties within a given model. Independent of implementation, we find that light, thermal jets with low momentum flux tend to delay the onset of a cooling flow more efficiently on a 50 Myr time-scale than heavy, kinetic jets. The delay of the cooling flow originates from a displacement and boost in entropy of the central gas. If the jet kinetic luminosity depends on accretion rate, collimated, light, hydrodynamic jets are able to reduce cooling flows in haloes, without a need for jet precession or wide opening angles. Comparing the jet feedback with a ‘kinetic wind’ implementation shows that equal amounts of star formation rate reduction can be achieved by different interactions with the halo gas: the jet has a larger effect on the hot halo gas while leaving the denser, star-forming phase in place, while the wind acts more locally on the star-forming phase, which manifests itself in different time-variability properties.

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