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Arkenstone is a new scheme that allows multiphase, stellar feedback-driven winds to be included in coarse resolution cosmological simulations. The evolution of galactic winds and their subsequent impact on the circumgalactic medium are altered by exchanges of mass, energy, momentum, and metals between their component phases. These exchanges are governed by complex, small-scale physical processes that cannot be resolved in cosmological simulations. In this second presentation paper, we describe Arkenstone's novel cloud particle approach for modelling unresolvable cool clouds entrained in hot, fast winds. This general framework allows models of the cloud-wind interaction, derived from state-of-the-art high-resolution simulations, to be applied in a large-scale context. In this work, we adopt a cloud evolution model that captures simultaneous cloud mass loss to and gain from the ambient hot phase via turbulent mixing and radiative cooling, respectively. We demonstrate the scheme using non-cosmological idealized simulations of a galaxy with a realistic circumgalactic medium component, using the Arepo code. We show that the ability of a high-specific energy wind component to perform preventative feedback may be limited by heavy loading of cool clouds coupled into it. We demonstrate that the diverging evolution of clouds of initially differing masses leads to a complex velocity field for the cool phase and a cloud mass function that varies both spatially and temporally in a non-trivial manner. These latter two phenomena can manifest in the simulation because of our choice of a Lagrangian discretisation of the cloud population, in contrast to other proposed schemes. This is a Learning the Universe publication., Comment: Submitted to MNRAS. 27 pages, 11 figures. This is a Learning the Universe publication

The first infall of the LMC into the Milky Way (MW) represents a large and recent disruption to the MW circumgalactic medium (CGM). In this work, we use idealized, hydrodynamical simulations of a MW-like CGM embedded in a live dark matter halo with an infalling LMC-like satellite initialized with its own CGM to understand how the encounter is shaping the global physical and kinematic properties of the MW CGM. First, we find that the LMC sources order-unity enhancements in MW CGM density, temperature, and pressure from a $\mathcal{M} \approx 2$ shock from the supersonic CGM-CGM collision, extending from the LMC to beyond $\sim R_{\rm 200, MW}$, enhancing column densities, X-ray brightness, the thermal Sunyaev-Zeldovich (tSZ) distortion, and potentially synchrotron emission from cosmic rays over large angular scales across the Southern Hemisphere. Second, the MW's reflex motion relative to its outer halo produces a dipole in CGM radial velocities, with $v_{\rm R} \pm 30-50$ km/s at $R > 50$ kpc in the Northern/Southern hemispheres respectively, consistent with measurements in the stellar halo. Finally, ram pressure strips most of the LMC CGM gas by the present day, leaving $\sim 10^{8-9} M_{\odot}$ of warm, ionized gas along the past orbit of the LMC moving at high radial and/or tangential velocities $\sim 50-100$ kpc from the MW. Massive satellites like the LMC leave their mark on the CGM structure of their host galaxies, and signatures from this interaction may manifest in key all-sky observables of the CGM of the MW and other massive galaxies., Comment: Submitted to ApJ. 22 pages, 15 Figures. Comments welcomed

We introduce a GPU-accelerated hybrid hydro/N-body code (Enzo-N) designed to address the challenges of concurrently simulating star clusters and their parent galaxies. This task has been exceedingly challenging, primarily due to the considerable computational time required, which stems from the substantial scale difference between galaxies (~ 0.1 Mpc) and star clusters (~ pc). Yet, this significant scale separation means that particles within star clusters perceive those outside the star cluster in a semi-stationary state. By leveraging this aspect, we integrate the direct N-body code (Nbody6++GPU) into the cosmological (magneto-)hydrodynamic code (Enzo) through the utilization of the semi-stationary background acceleration approximation. We solve the dynamics of particles within star clusters using the direct N-body solver with regularization for few-body interactions, while evolving particles outside -- dark matter, gas, and stars -- using the particle-mesh gravity solver and hydrodynamic methods. We demonstrate that Enzo-N successfully simulates the co-evolution of star clusters and their parent galaxies, capturing phenomena such as core collapse of the star cluster and tidal stripping due to galactic tides. This comprehensive framework opens up new possibilities for studying the evolution of star clusters within galaxies, offering insights that were previously inaccessible., Comment: 15 pages, 13 figures, Accepted for publication in ApJ

We present a new simulation suite for the star-forming interstellar medium (ISM) in galactic disks using the TIGRESS-NCR framework. Distinctive aspects of our simulation suite are: (1) sophisticated and comprehensive numerical treatments of essential physical processes including magnetohydrodynamics, self-gravity, and galactic differential rotation, as well as photochemistry, cooling, and heating coupled with ray-tracing UV radiation transfer and resolved supernova feedback and (2) wide parameter coverage including metallicity over $Z'\equiv Z/Z_\odot\sim0.1-3$, gas surface density $\Sigma_{\rm gas}\sim5-150 M_{\odot}{\rm pc^{-2}}$, and stellar surface density $\Sigma_{\rm star}\sim 1-50 M_{\odot}{\rm pc^{-2}}$. The range of emergent star formation rate surface density is $\Sigma_{\rm SFR}\sim 10^{-4}-0.5 M_{\odot}{\rm kpc^{-2}yr^{-1}}$ and ISM total midplane pressure is $P_{\rm tot}/k_B=10^3-10^6{\rm cm^{-3}K}$, with $P_{\rm tot}$ equal to the ISM weight $W$. For given $\Sigma_{\rm gas}$ and $\Sigma_{\rm star}$, we find $\Sigma_{\rm SFR} \propto Z'^{0.3}$. We provide an interpretation based on the pressure-regulated feedback-modulated (PRFM) star formation theory. We characterize feedback modulation in terms of the yield $\Upsilon$, defined as the ratio of each stress to $\Sigma_{\rm SFR}$. The thermal feedback yield varies sensitively with both weight and metallicity as $\Upsilon_{\rm th}\propto W^{-0.46}Z'^{-0.53}$, while the combined turbulent and magnetic feedback yield shows weaker dependence $\Upsilon_{\rm turb+mag}\propto W^{-0.22}Z'^{-0.18}$. The reduction in $\Sigma_{\rm SFR}$ at low metallicity is due mainly to enhanced thermal feedback yield, resulting from reduced attenuation of UV radiation. With the metallicity-dependent calibrations we provide, PRFM theory can be used for a new subgrid star formation prescription in cosmological simulations where the ISM is unresolved., Comment: Resubmitted to ApJ after minor revision

We introduce the RIGEL model, a novel framework to self-consistently model the effects of stellar feedback in the multiphase ISM of dwarf galaxies with radiative transfer (RT) on a star-by-star basis. The RIGEL model integrates detailed implementations of feedback from individual massive stars into the RHD code, AREPO-RT. It forms individual massive stars from the resolved multiphase ISM by sampling the IMF and tracks their evolution individually. The lifetimes, photon production rates, mass-loss rates, and wind velocities of these stars are determined by their initial masses and metallicities based on a library that incorporates a variety of stellar models. The RT equations are solved in seven spectral bins accounting for the IR to HeII ionizing bands, using an M1 RT scheme. The thermochemistry model tracks the non-equilibrium H, He chemistry and the equilibrium abundance of CI, CII, OI, OII, and CO to capture the thermodynamics of all ISM phases. We evaluate the performance of the RIGEL model using $1\,{\rm M}_\odot$ resolution simulations of isolated dwarf galaxies. We found that the SFR and ISRF show strong positive correlations to the metallicity of the galaxy. Photoionization and photoheating can reduce the SFR by an order of magnitude by removing the available cold-dense gas fuel for star formation. The ISRF also changes the thermal structure of the ISM. Radiative feedback occurs immediately after the birth of massive stars and rapidly disperses the molecular clouds within 1 Myr. As a consequence, radiative feedback reduces the age spread of star clusters to less than 2 Myr, prohibits the formation of massive star clusters, and shapes the cluster initial mass function to a steep power-law form with a slope of $\sim-2$. The mass-loading factor of the fiducial galaxy has a median of $\sim50$, while turning off radiative feedback reduces this factor by an order of magnitude., Comment: 27 pages, 18 figures; submitted to A&A; abstract slightly abridged; comments welcome

Bubbles driven by energy and mass injection from small scales are ubiquitous in astrophysical fluid systems and essential to feedback across multiple scales. In particular, O stars in young clusters produce high velocity winds that create hot bubbles in the surrounding gas. We demonstrate that the dynamical evolution of these bubbles is critically dependent upon the geometry of their interfaces with their surroundings and the nature of heat transport across these interfaces. These factors together determine the amount of energy that can be lost from the interior through cooling at the interface, which in turn determines the ability of the bubble to do work on its surroundings. We further demonstrate that the scales relevant to physical dissipation across this interface are extremely difficult to resolve in global numerical simulations of bubbles for parameter values of interest. This means the dissipation driving evolution of these bubbles in numerical simulations is often of a numerical nature. We describe the physical and numerical principles that determine the level of dissipation in these simulations; we use this, along with a fractal model for the geometry of the interfaces, to explain differences in convergence behavior between hydrodynamical and magneto-hydrodynamical simulations presented here. We additionally derive an expression for momentum as a function of bubble radius expected when the relevant dissipative scales are resolved and show that it still results in efficiently-cooled solutions as postulated in previous work., Comment: 41 pages, 20 figures, submitted to ApJ, comments welcome

The presence of dense, neutral hydrogen clouds in the hot, diffuse intra-group and intra-cluster medium is an important clue to the physical processes controlling the survival of cold gas and sheds light on cosmological baryon flows in massive halos. Advances in numerical modeling and observational surveys means that theory and observational comparisons are now possible. In this paper, we use the high-resolution TNG50 cosmological simulation to study the HI distribution in seven halos with masses similar to the Fornax galaxy cluster. Adopting observational sensitivities similar to the MeerKAT Fornax Survey (MFS), an ongoing HI survey that will probe to column densities of $10^{18}$ cm$^{-2}$, we find that Fornax-like TNG50 halos have an extended distribution of neutral hydrogen clouds. Within one virial radius, we predict the MFS will observe a total HI covering fraction around $\sim$ 12\% (mean value) for 10 kpc pixels and 6\% for 2 kpc pixels. If we restrict this to gas more than 10 half-mass radii from galaxies, the mean values only decrease mildly, to 10\% (4\%) for 10 (2) kpc pixels (albeit with significant halo-to-halo spread). Although there are large amounts of HI outside of galaxies, the gas seems to be associated with satellites, judging both by the visual inspection of projections and by comparison of the line of sight velocities of galaxies and intracluster HI., Comment: 20 pages, 13 figures, Accepted for publication in ApJ

The physical processes responsible for shaping how galaxies form and quench over time leave imprints on both the spatial (galaxy morphology) and temporal (star formation history; SFH) tracers that we use to study galaxies. While the morphology-SFR connection is well studied, the correlation with past star formation activity is not as well understood. To quantify this we present Katachi, an interpretable convolutional neural network (CNN) framework that learns the connection between the factors regulating star formation in galaxies on different spatial and temporal scales. Katachi is trained on 9904 galaxies at 0.02$<$z$<$0.1 in the SDSS-IV MaNGA DR17 sample to predict stellar mass (M$_*$; RMSE 0.22 dex), current star formation rate (SFR; RMSE 0.31 dex) and half-mass time (t$_{50}$; RMSE 0.23 dex). This information allows us to reconstruct non-parametric SFHs for each galaxy from \textit{gri} imaging alone. To quantify the morphological features informing the SFH predictions we use SHAP (SHapley Additive exPlanations). We recover the expected trends of M$_*$ governed by the growth of galaxy bulges, and SFR correlating with spiral arms and other star-forming regions. We also find the SHAP maps of D4000 are more complex than those of M$_*$ and SFR, and that morphology is correlated with t$_{50}$ even at fixed mass and SFR. Katachi serves as a scalable public framework to predict galaxy properties from large imaging surveys including Rubin, Roman, and Euclid, with large datasets of high SNR imaging across limited photometric bands., Comment: 35 pages, 25 figures. Accepted for publication in ApJ, comments are welcomed

The circumgalactic medium (CGM) of star-forming dwarf galaxies plays a key role in regulating the galactic baryonic cycle. We investigate how susceptible the CGM of dwarf satellite galaxies is to ram pressure stripping (RPS) in Milky Way-like environments. In a suite of hydrodynamical wind tunnel simulations, we model an intermediate-mass dwarf satellite galaxy ($M_{*} = 10^{7.2}~M_{\odot}$) with a multiphase interstellar medium (ISM; $M_{\rm ISM} = 10^{7.9}~M_{\odot}$) and CGM ($M_{\rm CGM,vir} = 10^{8.5}~M_{\odot}$) along two first-infall orbits to more than 500 Myr past pericenter of a Milky Way-like host. The spatial resolution is $\sim$79 pc in the star-forming ISM and $316-632$ pc in the CGM. Our simulations show that the dwarf satellite CGM removal is fast and effective: more than $95\%$ of the CGM mass is ram-pressure-stripped within a few hundred Myrs, even under a weak ram pressure orbit where the ISM stripping is negligible. The conditions for CGM survival are consistent with the analytical halo gas stripping predictions in McCarthy et al. (2008). We also find that including the satellite CGM does not effectively shield its galaxy, and therefore the ISM stripping rate is unaffected. Our results imply that a dwarf galaxy CGM is unlikely to be detected in satellite galaxies; and that the star formation of gaseous dwarf satellites is likely devoid of replenishment from a CGM., Comment: submitted to ApJ, comments welcome

Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with non-trivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally challenging to sample these high dimensional parameter spaces with simulations, particularly for halos in the high-mass end of the mass function. In this work, we develop a novel sampling and reduced variance regression method, CARPoolGP, which leverages built-in correlations between samples in different locations of high dimensional parameter spaces to provide an efficient way to explore parameter space and generate low variance emulations of summary statistics. We use this method to extend the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) to include a set of 768 zoom-in simulations of halos in the mass range of $10^{13} - 10^{14.5} M_\odot\,h^{-1}$ that span a 28-dimensional parameter space in the IllustrisTNG model. With these simulations and the CARPoolGP emulation method, we explore parameter trends in the Compton $Y-M$, black hole mass-halo mass, and metallicity-mass relations, as well as thermodynamic profiles and quenched fractions of satellite galaxies. We use these emulations to provide a physical picture of the complex interplay between supernova and active galactic nuclei feedback. We then use emulations of the $Y-M$ relation of massive halos to perform Fisher forecasts on astrophysical parameters for future Sunyaev-Zeldovich observations and find a significant improvement in forecasted constraints. We publicly release both the simulation suite and CARPoolGP software package., Comment: The manuscript was submitted to arxiv after receiving and responding to comments from the first referee report

This paper presents the Learning the Universe Implicit Likelihood Inference (LtU-ILI) pipeline, a codebase for rapid, user-friendly, and cutting-edge machine learning (ML) inference in astrophysics and cosmology. The pipeline includes software for implementing various neural architectures, training schemata, priors, and density estimators in a manner easily adaptable to any research workflow. It includes comprehensive validation metrics to assess posterior estimate coverage, enhancing the reliability of inferred results. Additionally, the pipeline is easily parallelizable and is designed for efficient exploration of modeling hyperparameters. To demonstrate its capabilities, we present real applications across a range of astrophysics and cosmology problems, such as: estimating galaxy cluster masses from X-ray photometry; inferring cosmology from matter power spectra and halo point clouds; characterizing progenitors in gravitational wave signals; capturing physical dust parameters from galaxy colors and luminosities; and establishing properties of semi-analytic models of galaxy formation. We also include exhaustive benchmarking and comparisons of all implemented methods as well as discussions about the challenges and pitfalls of ML inference in astronomical sciences. All code and examples are made publicly available at https://github.com/maho3/ltu-ili., Comment: 22 pages, 10 figures, accepted in the Open Journal of Astrophysics. Code available at https://github.com/maho3/ltu-ili

We present new high-spectral resolution observations (R = $\lambda/\Delta\lambda$ = 7000) of the filamentary nebula surrounding NGC 1275, the central galaxy of the Perseus cluster. These observations have been obtained with SITELLE, an imaging Fourier transform spectrometer installed on the Canada-France-Hawai Telescope (CFHT) with a field of view of $11\text{ arcmin }\times 11 \text{ arcmin}$ encapsulating the entire filamentary structure of ionised gas despite its large size of $80 \text{ kpc}\times50 \text{ kpc}$. Here, we present renewed flux, velocity and velocity dispersion maps that show in great detail the kinematics of the optical nebula at \sii$\lambda6716$, \sii$\lambda6731$, \nii$\lambda6584$, H$\alpha$(6563\AA), and \nii$\lambda6548$. These maps reveal the existence of a bright flattened disk-shaped structure in the core extending to r $\sim 10$ kpc and dominated by a chaotic velocity field. This structure is located in the wake of X-ray cavities and characterised by a high mean velocity dispersion of $134$ km/s. The disk-shaped structure is surrounded by an extended array of filaments spread out to $r\sim 50$ kpc that are 10 times fainter in flux, remarkably quiescent and has a uniform mean velocity dispersion of $44$ km/s. This stability is puzzling given that the cluster core exhibits several energetic phenomena. Based on these results, we argue that there are two mechanisms to form multiphase gas in clusters of galaxies: a first triggered in the wake of X-ray cavities leading to more turbulent multiphase gas and a second, distinct mechanism, that is gentle and leads to large-scale multiphase gas spread throughout the core.

In the absence of supplementary heat, the radiative cooling of halo gas around massive galaxies (Milky Way mass and above) leads to an excess of cold gas or stars beyond observed levels. AGN jet-induced heating is likely essential, but the specific properties of the jets remain unclear. Our previous work (Su et al. 2021) concludes from simulations of a halo with $10^{14} M_\odot$ that a successful jet model should have an energy flux comparable to the free-fall energy flux at the cooling radius and should inflate a sufficiently wide cocoon with a long enough cooling time. In this paper, we investigate three jet modes with constant fluxes satisfying the criteria, including high-temperature thermal jets, cosmic ray (CR)-dominant jets, and widely precessing kinetic jets in $10^{12}-10^{15}\,{\rm M}_{\odot}$ halos using high-resolution, non-cosmological MHD simulations with the FIRE-2 (Feedback In Realistic Environments) stellar feedback model, conduction, and viscosity. We find that scaling the jet energy according to the free-fall energy at the cooling radius can successfully suppress the cooling flows and quench galaxies without obviously violating observational constraints. We investigate an alternative scaling method in which we adjust the energy flux based on the total cooling rate within the cooling radius. However, we observe that the strong interstellar medium (ISM) cooling dominates the total cooling rate in this scaling approach, resulting in a jet flux that exceeds the amount needed to suppress the cooling flows. With the same energy flux, the CR-dominant jet is most effective in suppressing the cooling flow across all the surveyed halo masses due to the enhanced CR pressure support. We confirm that the criteria for a successful jet model, which we proposed in Su et al. (2021), work across a much wider range, encompassing halo masses of $10^{12}-10^{15} {\rm M_\odot}$., Comment: 15 pages, 10 figures, Submitted to MNRAS; comments welcome!

The 3D geometry of high-redshift galaxies remains poorly understood. We build a differentiable Bayesian model and use Hamiltonian Monte Carlo to efficiently and robustly infer the 3D shapes of star-forming galaxies in JWST-CEERS observations with $\log M_*/M_{\odot}=9.0-10.5$ at $z=0.5-8.0$. We reproduce previous results from HST-CANDELS in a fraction of the computing time and constrain the mean ellipticity, triaxiality, size and covariances with samples as small as $\sim50$ galaxies. We find high 3D ellipticities for all mass-redshift bins suggesting oblate (disky) or prolate (elongated) geometries. We break that degeneracy by constraining the mean triaxiality to be $\sim1$ for $\log M_*/M_{\odot}=9.0-9.5$ dwarfs at $z>1$ (favoring the prolate scenario), with significantly lower triaxialities for higher masses and lower redshifts indicating the emergence of disks. The prolate population traces out a ``banana'' in the projected $b/a-\log a$ diagram with an excess of low $b/a$, large $\log a$ galaxies. The dwarf prolate fraction rises from $\sim25\%$ at $z=0.5-1.0$ to $\sim50-80\%$ at $z=3-8$. If these are disks, they cannot be axisymmetric but instead must be unusually oval (triaxial) unlike local circular disks. We simultaneously constrain the 3D size-mass relation and its dependence on 3D geometry. High-probability prolate and oblate candidates show remarkably similar S\'ersic indices ($n\sim1$), non-parametric morphological properties and specific star formation rates. Both tend to be visually classified as disks or irregular but edge-on oblate candidates show more dust attenuation. We discuss selection effects, follow-up prospects and theoretical implications., Comment: Accepted version to appear in ApJ, main body is 36 pages of which ~half are full-page figures

Modelling galaxy formation in hydrodynamic simulations has increasingly adopted various radiative transfer methods to account for photoionization feedback from young massive stars. However, the evolution of HII regions around stars begins in dense star-forming clouds and spans large dynamical ranges in both space and time, posing severe challenges for numerical simulations in terms of both spatial and temporal resolution that depends strongly on gas density ($\propto n^{-1}$). In this work, we perform a series of idealized HII region simulations using the moving-mesh radiation-hydrodynamic code Arepo-RT to study the effects of numerical resolution. The simulated results match the analytical solutions and the ionization feedback converges only if the Str\"omgren sphere is resolved by at least $10$--$100$ resolution elements and the size of each time integration step is smaller than $0.1$ times the recombination timescale. Insufficient spatial resolution leads to reduced ionization fraction but enhanced ionized gas mass and momentum feedback from the HII regions, as well as degrading the multi-phase interstellar medium into a diffuse, partially ionized, warm ($\sim8000$ K) gas. On the other hand, insufficient temporal resolution strongly suppresses the effects of ionizing feedback. This is because longer timesteps are not able to resolve the rapid variation of the thermochemistry properties of the gas cells around massive stars, especially when the photon injection and thermochemistry are performed with different cadences. Finally, we provide novel numerical implementations to overcome the above issues when strict resolution requirements are not achievable in practice., Comment: 19 pages, 14 figures; MNRAS published

We investigate how a satellite's star formation rate (SFR) and surviving gas respond to ram pressure stripping in various environments. Using a suite of high-resolution "wind-tunnel" simulations with radiative cooling, star formation, and supernovae feedback, we model the first infall orbit of a low-mass disk galaxy ($M_{*} = 10^{9.7} M_{\odot}$) in different host halos, ranging from Milky Way-like to cluster hosts. When the ram pressure is moderate, we find that the stripping satellite shows an enhanced SFR relative to the isolated control case, despite gas loss due to stripping. The SFR enhancement is caused, not directly by compression, but by ram pressure-driven mass flows, which can increase the dense gas fraction in the central disk regions. The spatially-resolved star formation main sequence and Kennicutt-Schmidt relations in our simulations are consistent with recent findings of the VERTICO and GASP surveys. Our results predict the environmental signals of RPS in future multiwavelength, high-angular resolution observations: the star formation and gas surface densities will be centralized, and symmetrically enhanced within the stripping radius., Comment: submitted to ApJ, revised version after referee report

We explore the role of galactic feedback on the low redshift Lyman-$\alpha$ (Ly$\alpha$)~forest ($z \lesssim 2$) 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 sub-grid models. We find that both AGN and stellar feedback in Simba play a role in setting the Ly$\alpha$ forest 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 the $b$-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 Ly$\alpha$ forest, but varying the stellar feedback model does produce subtle changes. Our results imply that the low-$z$ Ly$\alpha$ forest can be sensitive to changes in the ultraviolet background (UVB), stellar and black hole feedback, and that AGN jet feedback in particular can have a strong effect on the thermal state of the IGM., Comment: 27 pages, 12 figures, 2 tables, accepted to ApJ

Cloud-wind interactions play an important role in long-lived multiphase flows in many astrophysical contexts. When this interaction is primarily mediated by hydrodynamics and radiative cooling, the survival of clouds can be phrased in terms of the comparison between a timescale that dictates the evolution of the cloud-wind interaction, (the dynamical time-scale $\tau_{\rm dyn}$) and the relevant cooling timescale $\tau_{\rm cool}$. Previously proposed survival criteria, which can disagree by large factors about the size of the smallest surviving clouds, differ in both their choice of $\tau_{\rm cool}$ and (to a lesser extent) $\tau_{\rm dyn}$. Here we present a new criterion which agrees with a previously proposed empirical formulae but is based on simple physical principles. The key insight is that clouds can grow if they are able to mix and cool gas from the hot wind faster than it advects by the cloud. Whereas prior criteria associate $\tau_{\rm dyn}$ with the cloud crushing timescale, our new criterion links it to the characteristic cloud-crossing timescale of a hot-phase fluid element, making it more physically consistent with shear-layer studies. We develop this insight into a predictive expression and validate it with hydrodynamic ENZO-E simulations of ${\sim}10^4\, {\rm K}$, pressure-confined clouds in hot supersonic winds, exploring, in particular, high wind/cloud density contrasts, where disagreements are most pronounced. Finally, we illustrate how discrepancies among previous criteria primarily emerged due to different choices of simulation conditions and cooling properties, and discuss how they can be reconciled., Comment: 6.5 pages, 4 figures, submitted to ApJL

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 idealised non-cosmological simulations of a galaxy with a realistic 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 ISM/CGM transition region which also provides the necessary level of refinement at the base of the wind. In the absence of 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 SFR of galaxies. In future work, we will demonstrate other aspects of the Arkenstone model., Comment: Published MNRAS, 27 pages, 17 figures; updated for consistency with journal version

We present the first results from a high resolution simulation with a focus on galactic wind driving for an isolated galaxy with a halo mass of $\sim 10^{11}$ M$_{\odot}$ (similar to the Large Magellanic Cloud) and a total gas mass of $\sim 6 \times 10^{8}$ M$_{\odot}$, resulting in $\sim 10^{8}$ gas cells at $\sim 4$ M$_{\odot}$ mass resolution. We adopt a resolved stellar feedback model with non-equilibrium cooling and heating, including photoelectric heating and photo-ionizing radiation, as well as supernovae (SNe), coupled to the second order meshless finite mass (MFM) method for hydrodynamics. These features make this the largest resolved-ISM galaxy model run to date. We find mean star formation rates around $0.05$ M$_{\odot}$ yr$^{-1}$ and evaluate typical time averaged loading factors for mass ($\eta_\mathrm{M}$ $\sim$ 1.0, in good agreement with recent observations) and energy ($\eta_\mathrm{E}$ $\sim$ 0.01). The bulk of the mass of the wind is transported by the warm ($T < 5 \times 10^5$K) phase, while there is a similar amount of energy transported in the warm and the hot phases ($T > 5 \times 10^5$K). We find an average opening angle of 30 degrees for the wind, decreasing with higher altitude above the midplane. The wind mass loading is decreasing (flat) for the warm (hot) phase as a function of the star formation surface rate density $\Sigma_{\rm SFR}$, while the energy loading shows inverted trends with $\Sigma_{\rm SFR}$, decreasing for the warm wind and increasing for the hot wind, although with very shallow slopes. These scalings are in good agreement with previous simulations of resolved wind driving in the multi-phase ISM., Comment: submitted to ApJ, 26 pages, 14 figures, comments welcome

In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators on ~1000 cosmological simulations from the CAMELS project to estimate simulated observables, taking as input the cosmological and astrophysical parameters, and use these emulators as surrogates to the cosmological simulations. Using the cosmic star formation rate density (SFRD) and, separately, stellar mass functions (SMFs) at different redshifts, we perform ILI on selected cosmological and astrophysical parameters (Omega_m, sigma_8, stellar wind feedback, and kinetic black hole feedback) and obtain full 6-dimensional posterior distributions. In the performance test, the ILI from the emulated SFRD (SMFs) can recover the target observables with a relative error of 0.17% (0.4%). We find that degeneracies exist between the parameters inferred from the emulated SFRD, confirmed with new full cosmological simulations. We also find that the SMFs can break the degeneracy in the SFRD, which indicates that the SMFs provide complementary constraints for the parameters. Further, we find that the parameter combination inferred from an observationally-inferred SFRD reproduces the target observed SFRD very well, whereas, in the case of the SMFs, the inferred and observed SMFs show significant discrepancies that indicate potential limitations of the current galaxy formation modeling and calibration framework, and/or systematic differences and inconsistencies between observations of the stellar mass function., Comment: This is the revised version from the reviewer's report (submitted to ApJ)

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 halos. 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 timescale 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 halos, 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., Comment: 22 pages, 20 figures, accepted for publication in MNRAS, comments welcome

The circumgalactic medium (CGM) plays a pivotal role in regulating gas flows around galaxies and thus shapes their evolution. However, the details of how galaxies and their CGM co-evolve remain poorly understood. We present a new time-dependent two-zone model that self-consistently tracks not just mass and metal flows between galaxies and their CGM but also the evolution of the global thermal and turbulent kinetic energy of the CGM. Our model accounts for heating and turbulence driven by both supernova winds and cosmic accretion as well as radiative cooling, turbulence dissipation, and halo outflows due to CGM overpressurization. We demonstrate that, depending on parameters, the CGM can undergo a phase transition (``thermalization'') from a cool, turbulence-supported phase to a virial-temperature, thermally-supported phase. This CGM phase transition is largely determined by the ability of radiative cooling to balance heating from supernova winds and turbulence dissipation. We perform an initial calibration of our model to the FIRE-2 cosmological hydrodynamical simulations and show that it can approximately reproduce the baryon cycles of the simulated halos. In particular, we find that, for these parameters, the phase transition occurs at high-redshift in ultrafaint progenitors and at low redshift in classical $M_{\rm vir}\sim10^{11}M_{\odot}$ dwarfs, while Milky Way-mass halos undergo the transition at $z\approx0.5$. We see a similar transition in the simulations though it is more gradual, likely reflecting radial dependence and multi-phase gas not captured by our model. We discuss these and other limitations of the model and possible future extensions., Comment: Updated to reflect version accepted by ApJ; minor text edits to clarify limitations and caveats of model

Galactic outflows driven by supernovae (SNe) are thought to be a powerful regulator of a galaxy's star-forming efficiency. Mass, energy, and metal outflows ($\eta_M$, $\eta_E$, and $\eta_Z$, here normalized by the star formation rate, the SNe energy and metal production rates, respectively) shape galaxy properties by both ejecting gas and metals out of the galaxy and by heating the circumgalactic medium (CGM), preventing future accretion. Traditionally, models have assumed that galaxies self-regulate by ejecting a large fraction of the gas which enters the interstellar medium (ISM), even though such high mass-loadings are in growing tension with observations. To better understand how the relative importance of ejective (i.e. high mass-loading) vs preventative (i.e. high energy-loading) feedback affects the present-day properties of galaxies, we develop a simple gas-regulator model of galaxy evolution, where the stellar mass, ISM, and CGM are modeled as distinct reservoirs which exchange mass, metals, and energy at different rates within a growing halo. Focusing on the halo mass range from $10^{10}$ to $10^{12} M_{\odot}$, we demonstrate that, with reasonable parameter choices, we can reproduce the stellar-to-halo mass relation and the ISM-to-stellar mass relation with low mass-loaded ($\eta_M \sim 0.1-10$) but high energy-loaded ($\eta_E \sim 0.1-1$) winds, with self-regulation occurring primarily through heating and cooling of the CGM. We show that the model predictions are robust against changes to the mass-loading of outflows but are quite sensitive to our choice of the energy-loading, preferring $\eta_E \sim 1$ for the lowest mass halos and $\sim 0.1$ for Milky Way-like halos., Comment: 19 pages, 9 Figures, submitted to ApJ

Turbulent Radiative Mixing Layers (TRMLs) form at the interface of cold, dense gas and hot, diffuse gas in motion with each other. TRMLs are ubiquitous in and around galaxies on a variety of scales, including galactic winds and the circumgalactic medium. They host the intermediate temperature gases that are efficient in radiative cooling, thus play a crucial role in controlling the cold gas supply, phase structure, and spectral features of galaxies. In this work, we develop an intuitive analytic 1.5 dimensional model for TRMLs that includes a simple parameterization of the effective turbulent conductivity and viscosity and a piece-wise power-law cooling curve. Our analytic model reproduces the mass flux, total cooling, and phase structure of 3D simulations of TRMLs at a fraction of the computational cost. It also reveals essential insights into the physics of TRMLs, particularly the importance of the viscous dissipation of relative kinetic energy in balancing radiative cooling as the shear Mach number approaches unity. This dissipation takes place both in the intermediate temperature phase, which reduces the enthalpy flux from the hot phase, and in the cold phase, which enhances radiative cooling. Additionally, our model provides a fast and easy way of computing the column density and surface brightness of TRMLs, which can be directly linked to observations., Comment: 32 pages, 22 figures. Published in ApJ, 22 June 2023

Turbulent radiative mixing layers (TRMLs) play an important role in many astrophysical contexts where cool ($\lesssim 10^4$ K) clouds interact with hot flows (e.g., galactic winds, high velocity clouds, infalling satellites in halos and clusters). The fate of these clouds (as well as many of their observable properties) is dictated by the competition between turbulence and radiative cooling; however, turbulence in these multiphase flows remains poorly understood. We have investigated the emergent turbulence arising in the interaction between clouds and supersonic winds in hydrodynamic ENZO-E simulations. In order to obtain robust results, we employed multiple metrics to characterize the turbulent velocity, $v_{\rm turb}$. We find four primary results, when cooling is sufficient for cloud survival. First, $v_{\rm turb}$ manifests clear temperature dependence. Initially, $v_{\rm turb}$ roughly matches the scaling of sound speed on temperature. In gas hotter than the temperature where cooling peaks, this dependence weakens with time until $v_{\rm turb}$ is constant. Second, the relative velocity between the cloud and wind initially drives rapid growth of $v_{\rm turb}$. As it drops (from entrainment), $v_{\rm turb}$ starts to decay before it stabilizes at roughly half its maximum. At late times cooling flows appear to support turbulence. Third, the magnitude of $v_{\rm turb}$ scales with the ratio between the hot phase sound crossing time and the minimum cooling time. Finally, we find tentative evidence for a length-scale associated with resolving turbulence. Under-resolving this scale may cause violent shattering and affect the cloud's large-scale morphological properties., Comment: 25 pages + appendix, 17 figures, Submitted to ApJ. For associated movies, see http://matthewabruzzo.com/visualizations/

Fuzzy dark matter (FDM) is a proposed modification for the standard cold dark matter (CDM) model motivated by small-scale discrepancies in low-mass galaxies. Composed of ultra-light (mass $\sim 10^{-22}$ eV) axions with kpc-scale de Broglie wavelengths, this is one of a class of candidates that predicts that the first collapsed objects form in relatively massive dark matter halos. This implies that the formation history of the first stars and galaxies would be very different, potentially placing strong constraints on such models. Here we numerically simulate the formation of the first stars in an FDM cosmology, following the collapse in a representative volume all the way down to primordial protostar formation including a primordial non-equilibrium chemical network and cooling for the first time. We find two novel results: first, the large-scale collapse results in a very thin and flat gas "pancake"; second, despite the very different cosmology, this pancake fragments until it forms protostellar objects indistinguishable from those in CDM. Combined, these results indicate that the first generation of stars in this model are also likely to be massive and, because of the sheet morphology, do not self-regulate, resulting in a massive Pop III starburst. We estimate the total number of first stars forming in this extended structure to be $10^4$ over 20 Myr using a simple model to account for the ionizing feedback from the stars, and should be observable with JWST. These predictions provide a potential smoking gun signature of FDM and similar dark matter candidates., Comment: 9 pages, 6 figures, Accepted for publication in ApJL

Active galactic nuclei (AGN) feedback models are generally calibrated to reproduce galaxy observables such as the stellar mass function and the bimodality in galaxy colors. We use variations of the AGN feedback implementations in the IllustrisTNG (TNG) and Simba cosmological hydrodynamic simulations to show that the low redshift Lyman-$\alpha$ forest can provide constraints on the impact of AGN feedback. We show that TNG over-predicts the number density of absorbers at column densities $N_{\rm HI} < 10^{14}$ cm$^{-2}$ compared to data from the Cosmic Origins Spectrograph (in agreement with previous work), and we demonstrate explicitly that its kinetic feedback mode, which is primarily responsible for galaxy quenching, has a negligible impact on the column density distribution (CDD) of absorbers. In contrast, we show that the fiducial Simba model which includes AGN jet feedback is the preferred fit to the observed CDD of the $z = 0.1$ Lyman-$\alpha$ forest across five orders of magnitude in column density. We show that the Simba results with jets produce a quantitatively better fit to the observational data than the Simba results without jets, even when the UVB is left as a free parameter. AGN jets in Simba are high speed, collimated, weakly-interacting with the interstellar medium (via brief hydrodynamic decoupling) and heated to the halo virial temperature. Collectively these properties result in stronger long-range impacts on the IGM when compared to TNG's kinetic feedback mode, which drives isotropic winds with lower velocities at the galactic radius. Our results suggest that the low redshift Lyman-$\alpha$ forest provides plausible evidence for long-range AGN jet feedback., Comment: 15 pages, 5 figures, 1 table, accepted to ApJL

We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain $\lesssim$5,000 halos with masses $\gtrsim 10^{10}~h^{-1}M_\odot$ in a periodic volume of $(25~h^{-1}{\rm Mpc})^3$; every halo in the catalogue is characterized by several properties such as position, mass, velocity, concentration, and maximum circular velocity. Our models, built to be permutationally, translationally, and rotationally invariant, do not impose a minimum scale on which to extract information and are able to infer the values of $\Omega_{\rm m}$ and $\sigma_8$ with a mean relative error of $\sim6\%$, when using positions plus velocities and positions plus masses, respectively. More importantly, we find that our models are very robust: they can infer the value of $\Omega_{\rm m}$ and $\sigma_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses. Surprisingly, the model trained to infer $\Omega_{\rm m}$ also works when tested on thousands of state-of-the-art CAMELS hydrodynamic simulations run with four different codes and subgrid physics implementations. Using halo properties such as concentration and maximum circular velocity allow our models to extract more information, at the expense of breaking the robustness of the models. This may happen because the different N-body codes are not converged on the relevant scales corresponding to these parameters., Comment: 25 pages, 11 figures, summary video: https://youtu.be/qkw92Z6owJU

The dividing line between galaxies that are quenched by reionization ("relics") and galaxies that survive reionization (i.e. continue forming stars) is commonly discussed in terms of a halo mass threshold. We probe this threshold in a physically more complete and accurate way than has been possible to date, using five extremely high resolution ($M_\mathrm{target}=4M_\odot$) cosmological zoom-in simulations of dwarf galaxies within the halo mass range $1-4\times10^9M_\odot$. The employed LYRA simulation model features resolved interstellar medium physics and individual, resolved supernova explosions. In our results, we discover an interesting intermediate population of dwarf galaxies close to the threshold mass but which are neither full reionization relics nor full reionization survivors. These galaxies initially quench at the time of reionization but merely remain quiescent for ~500Myr. At $z\approx5$ they recommence star formation in a synchronous way, and remain star-forming until the present day. These results demonstrate that the halo mass at $z=0$ is not a good indicator of survival close to the threshold. While the star formation histories we find are diverse, we show that they are directly related to the ability of a given halo to retain and cool gas. Whereas the latter is most strongly dependent on the mass (or virial temperature) of the host halo at the time of reionization, it also depends on its growth history, the UV background (and its decrease at late times) and the amount of metals retained within the halo., Comment: 15 pages, 12 figures, 2 tables, submitted to ApJ

We present a suite of high-resolution simulations of an isolated dwarf galaxy using four different hydrodynamical codes: {\sc Gizmo}, {\sc Arepo}, {\sc Gadget}, and {\sc 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 sub-grid 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 supernova-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 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., Comment: accepted version by ApJ (including a new simulation in Appendix B suggested by the referee)

In this work, we analyze a sample of $\sim$4000 massive ($M_*\geq 10^{11} M_\odot$ at $z=0$) galaxies in TNG300, the $(300 \mathrm{Mpc})^3$ box of the IllustrisTNG simulation suite. We characterize the shape and kinematics of these galaxies with a focus on the kinematic misalignment ($\Psi_\mathrm{int}$) between the angular momentum (AM) and morphological major axis. We find that the traditional purely shape- or kinematics-based classifications are insufficient to characterize the diversity of our sample and define a new set of classes based on the rates of change of the galaxies' morphological and kinematic axes. We show that these classes are mostly stable over time and correspond to six distinct populations of galaxies: the rapid AM reorienters (58% of our sample), unsettled galaxies (10%), spinning disks (10%), twirling cigars (16%), misaligned slow reorienters (3%), and regular prolate rotators (galaxies that display major axis rotation; 2%). We demonstrate that the most-recent significant (mass-ratio $\mu>1/10$) mergers of these galaxies are the primary cause for their present-day properties and find that these mergers are best characterized at the point of the satellite's final infall -- that is, much closer to the final coalescence than has been previously thought. We show that regular prolate rotators evolve from spinning disk progenitors that experience a radial merger along their internal AM direction. Finally, we argue that these regular prolate rotators are distinct from the similarly-sized population of rapid AM reorienters with large $\Psi_\mathrm{int}$, implying that a large $\Psi_\mathrm{int}$ is not a sufficient condition for major axis rotation., Comment: 26 pages, 17 figures; accepted for publication in ApJ

The early growth of black holes (BHs) in high-redshift galaxies is likely regulated by their feedback on the surrounding gas. While radiative feedback has been extensively studied, the role of mechanical feedback has received comparatively less scrutiny to date. Here we use high-resolution parsec-scale hydrodynamical simulations to study jet propagation and its effect on BH accretion onto 100 ${\rm M_\odot}$ BHs in the dense, low-metallicity gas expected in early protogalaxies. As the jet propagates, it shocks the surrounding gas and forms a jet cocoon. The cocoon consists of a rapidly-cooling cold phase at the interface with the background gas and an over-pressured subsonic phase of reverse shock-heated gas filling the cocoon interior. We systematically vary the background gas density and temperature, BH feedback efficiency, and the jet model. We found that the jet cocoon width roughly follows a scaling derived by assuming momentum conservation in the jet propagation direction, and energy conservation in the lateral directions. Depending on the assumed gas and jet properties, the cocoon either stays elongated out to a large radius or isotropizes before reaching the Bondi radius, forming a nearly spherical bubble. Lower jet velocities and higher background gas densities result in self-regulation to higher momentum fluxes and elongated cocoons. In all cases, the outward momentum flux of the cocoon balances the inward momentum flux of the inflowing gas near the Bondi radius, which ultimately regulates BH accretion. The larger the distance the jet cocoon reaches, the longer the variability timescale of the BH accretion rate. Overall, the average accretion rate always remains below the Bondi rate, and exceeds the Eddington rate only if the ambient medium is dense and cold, and/or the jet is weak. We derive the combination of jet and ambient gas parameters yielding super-Eddington growth., Comment: 16 pages, 11 figures

About ten to 20 percent of massive stars may be kicked out of their natal clusters before exploding as supernovae. These "runaway stars" might play a crucial 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 O/B stars above 8 M$_{\odot}$. 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 multi-phase interstellar medium (ISM), and include non-equilibrium cooling and chemistry channels. We adopt a resolved feedback scheme (\textsc{Griffin}) where we sample individual massive stars from an IMF. We follow the lifetime of these stars and add their photoionising radiation, their UV radiation field, and their photoelectric heating rate to the surrounding gas. At the end of their lifetime we explode the massive population as core collapse supernovae (CCSN). In the simulations with runaway massive 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 the inclusion of runaway or walkaway star scenarios has an impact on mass, metal, momentum and energy outflows as well as the respective loading factors. We find an increase in mass, metal and momentum loading by a factor of 2-3, whereas we find an increase in the mean energy loading by a factor of 5 in the runaway case and a factor of 3 in the walkaway case. However, we find that the peak values are increased by a factor of up to 10, independent of the adopted velocity kick model. We conclude that the inclusion of runaway stars could have a significant impact on the global outflow properties of dwarf galaxies., Comment: 18 pages, 13 Figures, 3 tables, submitted to MNRAS, comments welcome :-)

We study the sensitivity of the $z=0.1$ Lyman-$\alpha$ Forest observables, such as the column density distribution function (CDD), flux PDF, flux power spectrum, and line width distribution, to sub-grid models of active galactic nuclei (AGN) feedback using the Illustris and IllustrisTNG (TNG) cosmological simulations. The two simulations share an identical Ultraviolet Background (UVB) prescription and similar cosmological parameters, but TNG features an entirely reworked AGN feedback model. Due to changes in the AGN radio mode model, the original Illustris simulations have a factor of 2-3 fewer Lyman-$\alpha$ absorbers than TNG at column densities $N_{\rm HI}< 10^{15.5}$ cm$^{-2}$. We compare the simulated forest statistics to UV data from the Cosmic Origins Spectrograph (COS) and find that neither simulation can reproduce the slope of the absorber distribution. Both Illustris and TNG also produce significantly smaller line width distributions than observed in the COS data. We show that TNG is in much better agreement with the observed $z=0.1$ flux power spectrum than Illustris. We explore which statistics can disentangle the effects of AGN feedback from alternative UVB models by rescaling the UVB of Illustris to produce a CDD match to TNG. While this UVB rescaling is degenerate with the effect of AGN feedback on the CDD, the amplitude and shape of the flux PDF and 1D flux power spectrum change in a way distinct from a scaling of the UVB. Our study suggests that the $z=0.1$ Lyman-$\alpha$ forest observables can be used as a diagnostic of AGN feedback models., Comment: ApJL

The driving of turbulence in galaxies is deeply connected with the physics of feedback, star formation, outflows, accretion, and radial transport in disks. The velocity dispersion of gas in galaxies therefore offers a promising observational window into these processes. However, the relative importance of each of these mechanisms remains controversial. In this work we revisit the possibility that turbulence on galactic scales is driven by the direct impact of accreting gaseous material on the disk. We measure this effect in a disk-like star-forming galaxy in IllustrisTNG, using the high-resolution cosmological magnetohydrodynamical simulation TNG50. We employ Lagrangian tracer particles with a high time cadence of only a few Myr to identify accretion and other events, such as star formation, outflows, and movement within the disk. The energies of particles as they arrive in the disk are measured by stacking the events in bins of time before and after the event. The average effect of each event is measured on the galaxy by fitting explicit models for the kinetic and turbulent energies as a function of time in the disk. These measurements are corroborated by measuring the cross-correlation of the turbulent energy in the different annuli of the disk with other time series, and searching for signals of causality, i.e. asymmetries in the cross-correlation across zero time lag. We find that accretion contributes to the large-scale turbulent kinetic energy even if it is not the dominant driver of turbulence in this $\sim 5 \times 10^{9} M_\odot$ stellar mass galaxy. Extrapolating this finding to a range of galaxy masses, we find that there are regimes where energy from direct accretion may dominate the turbulent energy budget, particularly in disk outskirts, galaxies less massive than the Milky Way, and at redshift $\sim 2$., Comment: Submitted to AAS Journals, comments welcome

The cycle of baryons through the circumgalactic medium (CGM) is important to understand in the context of galaxy formation and evolution. In this study we forecast constraints on the feedback processes heating the CGM with current and future Sunyaev-Zeldovich (SZ) observations. To constrain these processes, we use a suite of cosmological simulations, the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS), that varies four different feedback parameters of two previously existing hydrodynamical simulations, IllustrisTNG and SIMBA. We capture the dependencies of SZ radial profiles on these feedback parameters with an emulator, calculate their derivatives, and forecast future constraints on these feedback parameters from upcoming experiments. We find that for a DESI-like (Dark Energy Spectroscopic Instrument) galaxy sample observed by the Simons Observatory all four feedback parameters are able to be constrained (some within the $10\%$ level), indicating that future observations will be able to further restrict the parameter space for these sub-grid models. Given the modeled galaxy sample and forecasted errors in this work, we find that the inner SZ profiles contribute more to the constraining power than the outer profiles. Finally, we find that, despite the wide range of AGN feedback parameter variation in the CAMELS simulation suite, we cannot reproduce the tSZ signal of galaxies selected by the Baryon Oscillation Spectroscopic Survey as measured by the Atacama Cosmology Telescope., Comment: 23 pages, 7 figures, comments welcome

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogues, power spectra, bispectra, Lyman-$\alpha$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic Model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies and summary statistics. We provide further technical details on how to access, download, read, and process the data at \url{https://camels.readthedocs.io}., Comment: 18 pages, 3 figures. More than 350 Tb of data from thousands of simulations publicly available at https://www.camel-simulations.org

A wealth of cosmological and astrophysical information is expected from many ongoing and upcoming large-scale surveys. It is crucial to prepare for these surveys now and develop tools that can efficiently extract most information. We present HIFlow: a fast generative model of the neutral hydrogen (HI) maps that is conditioned only on cosmology ($\Omega_{m}$ and $\sigma_{8}$) and designed using a class of normalizing flow models, the Masked Autoregressive Flow (MAF). HIFlow is trained on the state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. HIFlow has the ability to generate realistic diverse maps without explicitly incorporating the expected 2D maps structure into the flow as an inductive bias. We find that HIFlow is able to reproduce the CAMELS average and standard deviation HI power spectrum (Pk) within a factor of $\lesssim$ 2, scoring a very high $R^{2} > 90\%$. By inverting the flow, HIFlow provides a tractable high-dimensional likelihood for efficient parameter inference. We show that the conditional HIFlow on cosmology is successfully able to marginalize over astrophysics at the field level, regardless of the stellar and AGN feedback strengths. This new tool represents a first step toward a more powerful parameter inference, maximizing the scientific return of future HI surveys, and opening a new avenue to minimize the loss of complex information due to data compression down to summary statistics., Comment: updated: 14 pages, 10 figures, a new section on inference has been added during revision. Accepted for publication in ApJ

Galaxy mergers are known to host abundant young massive cluster (YMC) populations, whose formation mechanism is still not well-understood. Here, we present a high-resolution galaxy merger simulation with explicit star formation and stellar feedback prescriptions to investigate how mergers affect the properties of the interstellar medium and YMCs. Compared with a controlled simulation of an isolated galaxy, the mass fraction of dense and high-pressure gas is much higher in mergers. Consequently, the mass function of both molecular clouds and YMCs becomes shallower and extends to higher masses. Moreover, cluster formation efficiency is significantly enhanced and correlates positively with the star formation rate surface density and gas pressure. We track the orbits of YMCs and investigate the time evolution of tidal fields during the course of the merger. At an early stage of the merger, the tidal field strength correlates positively with YMC mass, $\lambda_{\rm tid}\propto M^{0.71}$, which systematically affects the shape of the mass function and age distribution of the YMCs. At later times, most YMCs closely follow the orbits of their host galaxies, gradually sinking into the center of the merger remnant due to dynamical friction, and are quickly dissolved via efficient tidal disruption. Interestingly, YMCs formed during the first passage, mostly in tidal tails and bridges, are distributed over a wide range of galactocentric radii, greatly increasing their survivability because of the much weaker tidal field in the outskirts of the merger system. These YMCs are promising candidates for globular clusters that survive to the present day., Comment: 15 pages, 12 figures. MNRAS accepted on Mar. 9th

We present a novel analytic framework to model the steady-state structure of multiphase galactic winds comprised of a hot, volume-filling component and a cold, clumpy component. We first derive general expressions for the structure of the hot phase for arbitrary mass, momentum, and energy sources terms. Next, informed by recent simulations, we parameterize the cloud-wind mass transfer rates, which are set by the competition between turbulent mixing and radiative cooling. This enables us to cast the cloud-wind interaction as a source term for the hot phase and thereby simultaneously solve for the evolution of both phases fully accounting for their bidirectional influence. With this model, we explore the nature of galactic winds over a broad range of conditions. We find that: (i) with realistic parameter choices, we naturally produce a hot, low-density wind that transports energy while entraining a significant flux of cold clouds, (ii) mixing dominates the cold cloud acceleration and decelerates the hot wind, (iii) during mixing thermalization of relative kinetic energy provides significant heating, (iv) systems with low hot-phase mass loading factors and/or star formation rates can sustain higher initial cold phase mass loading factors, but the clouds are quickly shredded, and (v) systems with large hot-phase mass loading factors and/or star formation rates cannot sustain large initial cold-phase mass loading factors, but the clouds tend to grow with radius. Our results highlight the necessity of accounting for the multiphase structure of galactic winds, both physically and observationally, and have important implications for feedback in galactic systems., Comment: 41 pages, 11 figures, submitted to ApJ. Schematic overview shown in Fig. 1 available at https://dfielding14.github.io/images/Multiphase_Winds_Schematic.pdf . Example code available at https://github.com/dfielding14/MultiphaseGalacticWind

We characterize mass, momentum, energy and metal outflow rates of multi-phase galactic winds in a suite of FIRE-2 cosmological "zoom-in" simulations from the Feedback in Realistic Environments (FIRE) project. We analyze simulations of low-mass dwarfs, intermediate-mass dwarfs, Milky Way-mass halos, and high-redshift massive halos. Consistent with previous work, we find that dwarfs eject about 100 times more gas from their interstellar medium (ISM) than they form in stars, while this mass "loading factor" drops below one in massive galaxies. Most of the mass is carried by the hot phase ($>10^5$ K) in massive halos and the warm phase ($10^3-10^5$ K) in dwarfs; cold outflows ($<10^3$ K) are negligible except in high-redshift dwarfs. Energy, momentum and metal loading factors from the ISM are of order unity in dwarfs and significantly lower in more massive halos. Hot outflows have $2-5\times$ higher specific energy than needed to escape from the gravitational potential of dwarf halos; indeed, in dwarfs, the mass, momentum, and metal outflow rates increase with radius whereas energy is roughly conserved, indicating swept up halo gas. Burst-averaged mass loading factors tend to be larger during more powerful star formation episodes and when the inner halo is not virialized, but we see effectively no trend with the dense ISM gas fraction. We discuss how our results can guide future controlled numerical experiments that aim to elucidate the key parameters governing galactic winds and the resulting associated preventative feedback., Comment: Accepted to MNRAS with minor revisions, main body is 25 pages with 14 figures

The circumgalactic medium (CGM) contains information on gas flows around galaxies, such as accretion and supernova-driven winds, which are difficult to constrain from observations alone. Here, we use the high-resolution TNG50 cosmological magnetohydrodynamical simulation to study the properties and kinematics of the CGM around star-forming galaxies in $10^{11.5}-10^{12}\;M_{\odot}$ halos at $z\simeq$ 1 using mock MgII absorption lines, which we generate by postprocessing halos to account for photoionization in the presence of a UV background. We find that the MgII gas is a very good tracer of the cold CGM, which is accreting inward at inflow velocities of up to 50 km s$^{-1}$. For sight lines aligned with the galaxy's major axis, we find that MgII absorption lines are kinematically shifted due to the cold CGM's significant corotation at speeds up to 50% of the virial velocity for impact parameters up to 60 kpc. We compare mock MgII spectra to observations from the MusE GAs FLow and Wind (MEGAFLOW) survey of strong MgII absorbers ($\rm{EW}^{2796\r{A}}_{0}>0.5 \; \r{A}$). After matching the equivalent-width (EW) selection, we find that the mock MgII spectra reflect the diversity of observed kinematics and EWs from MEGAFLOW, even though the sight lines probe a very small fraction of the CGM. MgII absorption in higher-mass halos is stronger and broader than in lower-mass halos but has qualitatively similar kinematics. The median-specific angular momentum of the MgII CGM gas in TNG50 is very similar to that of the entire CGM and only differs from non-CGM components of the halo by normalization factors of $\lesssim$ 1 dex., Comment: Accepted to ApJ. 17 pages, 11 figures. The TNG50 data is now publicly available at https://www.tng-project.org

Ram Pressure Stripping can remove gas from satellite galaxies in clusters via a direct interaction between the intracluster medium (ICM) and the interstellar medium. This interaction is generally thought of as a contact force per area, however we point out that these gases must interact in a hydrodynamic fashion, and argue that this will lead to mixing of the galactic gas with the ICM wind. We develop an analytic framework for how mixing is related to the acceleration of stripped gas from a satellite galaxy. We then test this model using three "wind-tunnel" simulations of Milky Way-like galaxies interacting with a moving ICM, and find excellent agreement with predictions using the analytic framework. Focusing on the dense clumps in the stripped tails, we find that they are nearly uniformly mixed with the ICM, indicating that all gas in the tail mixes with the surroundings, and dense clumps are not separate entities to be modeled differently than diffuse gas. We find that while mixing drives acceleration of stripped gas, the density and velocity of the surrounding wind will determine whether the mixing results in the heating of stripped gas into the ICM, or the cooling of the ICM into dense clouds., Comment: submitted to AAS Journals

Without additional heating, radiative cooling of gas in the halos of massive galaxies (Milky Way and above) produces cold gas or stars in excess of that observed. Previous work suggested that AGN jets are likely required, but the form of jet energy required to quench remains unclear. This is particularly challenging for galaxy simulations, in which the resolution is orders of magnitude coarser than necessary to form and evolve the jet. On such scales, the uncertain parameters include: jet energy form (kinetic, thermal, and cosmic ray (CR) energy), energy, momentum, and mass flux, magnetic field strength and geometry, jet precession angle and period, opening-angle, and duty cycle. We investigate all of these parameters in a $10^{14}\,{\rm M}_{\odot}$ halo using high-resolution non-cosmological MHD simulations with the FIRE-2 (Feedback In Realistic Environments) stellar feedback model, conduction, and viscosity. We explore which scenarios match observational constraints and show that CR-dominated jets can most efficiently quench the central galaxy through a combination of CR pressure support and a modification of the thermal instability. Jets with most energy in mildly relativistic ($\sim$ MeV or $\sim10^{10}$ K) thermal plasma work, but require a factor $\sim 10$ larger energy input. For a fixed energy flux, jets with higher specific energy (longer cooling times) quench more effectively. For this halo size, kinetic jets are less efficient in quenching unless they have wide opening or precession angles. Magnetic fields play a minor role except when the magnetic flux reaches $\gtrsim 10^{44}$ erg s$^{-1}$ in a kinetic jet model, which causes the jet cocoon to significantly widen, and the quenching to become explosive. We conclude that the criteria for a successful jet model are an optimal energy flux and a sufficiently wide jet cocoon with long enough cooling time at the cooling radius., Comment: 29 pages, 20 figures

We introduce a simple entropy-based formalism to characterize the role of mixing in pressure-balanced multiphase clouds, and demonstrate example applications using Enzo-E (magneto)hydrodynamic simulations. Under this formalism, the high-dimensional description of the system's state at a given time is simplified to the joint distribution of mass over pressure ($P$) and entropy ($K=P/\rho^\gamma$). As a result, this approach provides a way for (empirically and analytically) quantifying the impact of different initial conditions and sets of physics on the system evolution. We find that mixing predominantly alters the distribution along the $K$ direction and illustrate how the formalism can be used to model mixing and cooling for fluid elements originating in the cloud. We further confirm and generalize a previously suggested criterion for cloud growth in the presence of radiative cooling, and demonstrate that the shape of the cooling curve, particularly at the low temperature end, can play an important role in controlling condensation. Moreover, we discuss the capacity of our approach to generalize such a criterion to apply to additional sets of physics, and to build intuition for the impact of subtle higher order effects not directly addressed by the criterion., Comment: 21 pages + appendices, 17 figures, Submitted to ApJ. For associated movies, see http://matthewabruzzo.com/visualizations/

Galactic outflows have density, temperature, and velocity variations at least as large as that of the multiphase, turbulent interstellar medium (ISM) from which they originate. We have conducted a suite of parsec-resolution numerical simulations using the TIGRESS framework, in which outflows emerge as a consequence of interaction between supernovae (SNe) and the star-forming ISM. The outflowing gas is characterized by two distinct thermal phases, cool (T<10^4 K) and hot (T>10^6 K), with most mass carried by the cool phase and most energy and newly-injected metals carried by the hot phase. Both components have a broad distribution of outflow velocity, and especially for cool gas this implies a varying fraction of escaping material depending on the halo potential. Informed by the TIGRESS results, we develop straightforward analytic formulae for the joint probability density functions (PDFs) of mass, momentum, energy, and metal loading as distributions in outflow velocity and sound speed. The model PDFs have only two parameters, SFR surface density \Sigma_SFR and the metallicity of the ISM, and fully capture the behavior of the original TIGRESS simulation PDFs over \Sigma_SFR~(10^{-4},1)M_sun/kpc^2/yr. Employing PDFs from resolved simulations will enable galaxy formation subgrid model implementations with wind velocity and temperature (as well as total loading factors) that are based on theoretical predictions rather than empirical tuning. This is a critical step to incorporate advances from TIGRESS and other high-resolution simulations in future cosmological hydrodynamics and semi-analytic galaxy formation models. We release a python package to prototype our model and to ease its implementation., Comment: ApJL accepted. For associated python package, see https://twind.readthedocs.io/en/latest/

A critical dark matter halo mass ($M_{\rm crit}$) for Population III (Pop III) stars can be defined as the typical minimum halo mass that hosts sufficient cold dense gas required for the formation of the first stars. The presence of Lyman-Werner (UV) radiation, which can dissociate molecular hydrogen, and the baryon-dark matter streaming velocity both delay the formation of Pop III stars by increasing $M_{\rm crit}$. In this work, we constrain $M_{\rm crit}$ as a function of Lyman-Werner flux (including self-shielding), baryon-dark matter streaming, and redshift using cosmological simulations with a large sample of halos utilizing the adaptive mesh refinement (AMR) code ENZO. We provide a fit for $M_{\rm crit}$ as a function of these quantities which we expect to be particularly useful for semi-analytical models of early galaxy formation. In addition, we find: (i) the measured redshift dependence of $M_{\rm crit}$ in the absence of radiation or streaming is $(1+z)^{-1.58}$, consistent with a constant virial temperature; (ii) increasing the UV background increases $M_{\rm crit}$ while steepening the redshift dependence, up to $(1+z)^{-5.7}$; (iii) baryon-dark matter streaming boosts $M_{\rm crit}$ but flattens the dependence on redshift; (iv) the combination of the two effects is not simply multiplicative., Comment: Submitted to ApJ. 15 pages, 9 figures; corrected typos

We present the Cosmology and Astrophysics with MachinE Learning Simulations --CAMELS-- project. CAMELS is a suite of 4,233 cosmological simulations of $(25~h^{-1}{\rm Mpc})^3$ volume each: 2,184 state-of-the-art (magneto-)hydrodynamic simulations run with the AREPO and GIZMO codes, employing the same baryonic subgrid physics as the IllustrisTNG and SIMBA simulations, and 2,049 N-body simulations. The goal of the CAMELS project is to provide theory predictions for different observables as a function of cosmology and astrophysics, and it is the largest suite of cosmological (magneto-)hydrodynamic simulations designed to train machine learning algorithms. CAMELS contains thousands of different cosmological and astrophysical models by way of varying $\Omega_m$, $\sigma_8$, and four parameters controlling stellar and AGN feedback, following the evolution of more than 100 billion particles and fluid elements over a combined volume of $(400~h^{-1}{\rm Mpc})^3$. We describe the simulations in detail and characterize the large range of conditions represented in terms of the matter power spectrum, cosmic star formation rate density, galaxy stellar mass function, halo baryon fractions, and several galaxy scaling relations. We show that the IllustrisTNG and SIMBA suites produce roughly similar distributions of galaxy properties over the full parameter space but significantly different halo baryon fractions and baryonic effects on the matter power spectrum. This emphasizes the need for marginalizing over baryonic effects to extract the maximum amount of information from cosmological surveys. We illustrate the unique potential of CAMELS using several machine learning applications, including non-linear interpolation, parameter estimation, symbolic regression, data generation with Generative Adversarial Networks (GANs), dimensionality reduction, and anomaly detection., Comment: 34 pages, 19 figures, Matches published version. CAMELS webpage at https://www.camel-simulations.org