Paul Torrey

It is often understood that supernova (SN) feedback in galaxies is responsible for regulating star formation (SF) and generating gaseous outflows. However, a detailed look at the small-scale effects of SNe on the interstellar medium (ISM) in simulations shows that the macroscopic processes of SF suppression and outflow generation proceed in distinct channels. We demonstrate this finding in two independent simulations of isolated dwarf galaxies with very high (m_gas ~ Msun) numerical resolution, LYRA and RIGEL. Our findings suggest that the macroscopic effect of a given SN on the galaxy is best predicted by its local density. Outflows are primarily linked to SNe in diffuse regions expanding to their cooling radii on large (~kpc) scales, while dense SF regions are disrupted in a localized (~pc) manner. However, these separate feedback channels are only distinguishable at very high resolutions capable of following mass scales ^2 . When averaging on coarser scales, ISM densities are greatly mis-estimated, and variations between different SF and SNe-affected regions are severely washed out. It therefore cannot be self-consistently determined, from coarse-resolution information alone , (1) whether a SN tends to contribute to outflows or direct SF suppression, and (2) the rate of SF in a given region. In particular, commonly used parameters in coarse-resolution (subgrid) models, such as the SN cooling radius and SF density threshold, may require more detailed treatments informed by high-resolution studies.

We investigate the origin of Little Red Dots (LRDs) using a realization of the BRAHMA cosmological hydrodynamic simulation that produces overmassive black holes at z ∼ 4 - 8 . We generate mock JWST observations by modeling galaxy spectral energy distributions (including dust attenuation) together with AGN emission using cloudy-based templates, and test whether such systems reproduce the observed LRD population. We consider both a standard low-redshift AGN emission model and a gas-enshrouded AGN emission model, in which the AGN is embedded within unresolved dense gas that produces a strong Balmer break, and find that LRDs emerge in significantly larger numbers with the latter model. Assuming that all AGN reside in this gas-enshrouded phase, we recover LRD number densities ( Φ ∼ 2 × 10 − 4 M p c − 3 ), close to the observed abundance. This implies an effective gas-enshrouded duty cycle approaching unity, which is not predicted by current theoretical models. Current JWST constraints on the high-z black hole mass function suggest that this tension may arise from a deficit of low-mass () LRDs in BRAHMA. Applying the same gas-enshrouded model to the ASTRID simulation, which lacks overmassive black holes, we find that the LRD abundance remains below observations. Overall, while the overmassive black holes in this BRAHMA realization substantially enhance the production of LRD-like systems, reproducing the observed LRD abundance requires them to reside in dense gas environments with unrealistically high duty cycles. We therefore conclude that overmassive black holes are unlikely to be the sole origin of the observed JWST LRD population, and may instead account for only a subset of these systems.

We present the first results from AMBRA simulation ( A STRID with M BH seeding from BRA HMA) evolved to z = 8. AMBRA combines the large cosmological volume and statistical power of ASTRID with the physically motivated gas-based black hole (BH) seeding models from BRAHMA . Motivated by James Webb Space Telescope’s (JWST) discoveries of massive BHs at z ≳ 9, AMBRA adopts a lenient heavy-seed prescription from the BRAHMA suite, allowing for the formation of 4 × 10 ⁴⁻⁵ M _⊙ seeds in halos with star-forming, metal-poor gas. The seeding model is motivated by scenarios in which heavy seeds form through stellar collisions in star clusters or from the rapid growth of Population III remnants. The improved seeding model enables AMBRA to form BH seeds much earlier and more efficiently compared to ASTRID . This significantly enhances early BH growth, producing a z = 8 BH number density more than an order of magnitude higher than that in ASTRID over the mass range 10 ⁵⁻⁷ M _⊙ . BHs reaching masses consistent with GN-z11 and CEERS-1019 typically originate in highly compact density peaks and undergo multiple early mergers. In these systems, ∼50% of BH masses by z = 11 is from BH mergers, after which gas accretion becomes the dominant growth channel. Without this early merger-driven assembly, ASTRID cannot reproduce the high-mass BH detected by JWST. Our results indicate that abundant early seed formation combined with frequent mergers can explain several JWST massive BH candidates without requiring sustained super-Eddington accretion. As a testable prediction, AMBRA yields ≈4 Laser Interferometer Space Antenna (LISA) detectable BH merger events per year at z ≥ 8, which is three orders of magnitude higher than that in ASTRID .

The James Webb Space Telescope (JWST) discoveries of supermassive black holes (BHs) at z ≳ 5 may provide key insights into their seeding origins. Using new [18–72 Mpc] ³ BRAHMA cosmological simulations, we investigate how variations in heavy-seed prescriptions, coupled with a subgrid dynamical friction model, shape BH populations at z ∼ 5 and ∼ 0. We consider two “lenient” seed models, in which all halos containing sufficiently dense and metal-poor gas form ∼10 ⁴ and ∼10 ⁵ M _⊙ seeds, and a “strict” seed model, in which ∼10 ⁵ M _⊙ seeds form only under additional constraints motivated by direct collapse BH formation. By z ∼ 5, all models produce M _* – M _BH relations broadly consistent with the observed local Universe for M _* ≳ 10 ⁹ M _⊙ galaxies, but only the lenient scenarios generate systems near the upper envelope of the observed local scatter. In galaxies hosting M _BH ∼ 10 ⁸ –10 ⁹ M _⊙ BHs, lenient production of ∼10 ⁵ M _⊙ seeds also produces multiple overmassive systems with M _BH / M _* ≳ 0.01. Although their growth is dominated by seeding and mergers, these systems reach luminosities of ∼10 ⁴³ –10 ⁴⁵ erg s ⁻¹ , comparable to those inferred for JWST-detected BHs. As a key observational signature, the lenient seed models yield merger rates of ≳100 yr ⁻¹ and near-unity local BH occupation fractions even in galaxies with M _* ≲ 10 ⁷ M _⊙ . In contrast, the strict seed model produces merger rates of only ∼1 yr ⁻¹ and local occupation fractions of ≲10% for galaxies with M _* ≲ 10 ⁸ M _⊙ . Future gravitational-wave event rates and measurements of local BH occupation fractions will therefore provide strong constraints on the dominant pathways responsible for high-redshift BH assembly.

We present spatially resolved parsec-scale measurements of nuclear conditions (gas density and kinetic temperature) relevant for black hole accretion rate predictions in the Seyfert 2 galaxy, NGC 1068. We inject these parameters into the prescription for a Bondi-like accretion model, then compare the resulting accretion rate prediction to the empirical accretion rate derived from hard X-ray observations. Cosmological simulations have spatial resolution ranging from ∼10 pc to approximately kiloparsec scales, and so for reasonable comparison we test these accretion rate predictions in pixel-sized radial steps out to 500 pc. Compared to warm H ₂ gas, CO gas is the dominant mass carrier close to the SMBH. We find that the Bondi accretion rate ( M ̇ Bondi ) of cold molecular gas alone (measured using CO) overestimates the true accretion rate by up to 14 dex in a small aperture ( r ≲5 pc) around the black hole, and by at least 8 dex inside large apertures ( r ≲500 pc). These results are the first in a series of direct tests of accretion rate prescriptions, and they suggest that using a Bondi accretion formalism to model supermassive black hole accretion in Seyfert 2 galaxies may lead to overestimated accretion rates in simulations.

We analyze the properties of satellite galaxies around 1024 Milky Way–mass hosts from the DREAMS Project, simulated within a ΛCDM cosmology. Utilizing the TNG galaxy-formation model, the DREAMS simulations incorporate both baryonic physics and cosmological uncertainties for a large sample of galaxies with diverse environments and formation histories. We investigate the relative impact of the physical uncertainty from the galaxy-formation model on predicted satellite properties using four metrics: the satellite stellar mass function, radial distribution, inner slope of the dark matter density profile, and stellar half-light radius. We compare these predictions to observations from the SAGA survey and the DREAMS N -body simulations and find that uncertainties from baryonic physics modeling are subdominant to the scatter arising from halo-to-halo variance. Where baryonic modeling does affect satellites, the supernova wind energy has the largest effect on the satellite properties that we investigate. Specifically, increased supernova wind energy suppresses the stellar mass of satellites and results in more extended stellar half-light radii. The adopted wind speed has only a minor impact, and other astrophysical and cosmological parameters show no measurable effect. Our findings highlight the robustness of satellite properties against uncertainties in baryonic physics modeling.

Dark matter (DM) halos form hierarchically in the Universe through a series of merger events. By pairing halo finder and postprocessing codes, merger series in cosmological simulations can be conveniently represented as a graph-like “tree” structure. Previous work has shown that these merger trees are sensitive to cosmological simulation parameters, but as structures comprised of DM halos, the outstanding question of their sensitivity to DM models remains unanswered. In this work, we investigate the feasibility of deep learning methods trained on merger trees to infer warm dark matter (WDM) particle masses from the DREAMS simulation suite. We organize the merger trees from 1024 zoom-in simulations into graphs with nodes representing halos at different epochs and edges denoting hereditary links. We vary the complexity of the node features included in the graphs, ranging from a single node feature up through an array of several galactic properties. We train a graph neural network (GNN) to predict the WDM mass using the graph representation of the merger tree as input. We find that the GNN can predict the mass of the WDM particle, with success depending on the graph complexity and node features. We extend the same methods to supernovae (SNe) and active galactic nuclei feedback parameters, successfully inferring the SNe parameters. With reduced accuracy, the GNN can even infer the WDM mass from merger tree histories without any node features, indicating that the structure of merger trees alone inherits information about the cosmological parameters of the simulations from which they form.

The origin and structure of the hot ( T ≳ 10 ⁶ K) gaseous halo around Milky Way (MW)-mass galaxies provide a critical test for galaxy formation models. We perform a comprehensive comparison for a sample of MW analogs from the TNG50 cosmological simulation by generating synthetic soft X-ray emission and O vii /O viii absorption lines, viewed from both internal (solar) and external perspectives. The simulated halos successfully reproduce the observed global soft X-ray luminosity, inner-halo X-ray surface brightness, emission measure, and O vii absorption strength. However, two interconnected discrepancies are identified. First, the azimuthally averaged X-ray surface brightness profile from external viewpoints declines too steeply with radius compared to the extended emission detected in eROSITA stacking of Sloan Digital Sky Survey galaxies, falling below the observations by up to ∼1 dex at R ≳ 100 kpc. Second, the halos systematically underproduce O viii absorption, with a median equivalent width ∼65% lower than that observed in the Galactic halo, pointing to a deficit of hotter-phase gas at T ∼ (1.6−3.2) × 10 ⁶ K. These findings indicate that the simulated hot halos are too spatially compact and lack a hotter gas phase, suggesting that the TNG50 feedback model, while generating hot gas, deposits energy too centrally and too vigorously to sustain a gently extended, multiphase corona.

We present new constraints on the mass–metallicity (MZR) and fundamental metallicity relations (FMR) using a sample of 34 galaxies at 1.38 ≤ z ≤ 3.5 (median z = 2.28). These galaxies have direct T _e measurements from [O iii ]4363 Å and/or [O ii ]7320,7331 Å auroral emission lines detected with JWST/NIRSpec as part of the AURORA survey. The detection of both oxygen auroral lines allows for dual-zone direct T _e measurements and expands the dynamic range in 12 + log ( O / H ) (7.68–8.65 dex), stellar mass (10 ⁸ –10 ^10.4 M _⊙ ), and star formation rate (1–100 M _⊙ yr ⁻¹ ) compared to previous direct T _e studies of the high-redshift MZR and FMR. We characterize the z ∼ 2 MZR and find a slope of 0.27 ± 0.04 and normalization of 12 + log ( O / H ) = 8.44 ± 0.04 at10 ¹⁰ M _⊙ with an intrinsic scatter of 0.10 dex, consistent with past strong-line MZR measurements. Comparisons with z ∼ 2 predictions from six simulations reveal that none reproduce our observed MZR normalization evolution between z ∼ 0 and z ∼ 2. This discrepancy suggests current models do not fully capture the chemical enrichment and feedback processes occurring at cosmic noon. However, all 34 galaxies are on or above the star-forming main sequence such that our sample may be biased toward lower 12 + log ( O / H ) if the FMR persists at z ∼ 2. Correcting for this selection effect would increase O/H by ≈0.1 dex at 10 ^9.3 M _⊙ (the median mass of our sample), bringing our MZR into better agreement with that of Illustris TNG . Lastly, we find our z ∼ 2.3 sample is consistent with the z ∼ 0 FMR within 0.1 dex in O/H, indicating that the smooth secular mechanisms regulating chemical enrichment, star formation, stellar mass, and outflows were in place at cosmic noon.

Dark matter direct detection experiments require information about the local dark matter speed distribution to produce constraints on dark matter candidates, or infer their properties in the event of a discovery. In this paper, we analyze how the uncertainty in the dark matter speed distribution near the Sun is affected by baryonic feedback, halo-to-halo variance, and halo mass. To do so, we harness the statistical power of the new DREAMS cold dark matter simulation suite, which is comprised of 1024 zoom-in Milky Way–mass halos with varied initial conditions as well as cosmological and astrophysical parameters. Applying a normalizing flows emulator to these simulations, we find that the uncertainty in the local dark matter speed distribution is dominated by halo-to-halo variance and, to a lesser extent, uncertainty in host halo mass. Uncertainties in supernova and black hole feedback (from the IllustrisTNG model in this case) are negligible in comparison. Using the DREAMS suite, we present a state-of-the-art prediction for the dark matter speed distribution in the Milky Way. Although the standard halo model is contained within the uncertainty of this prediction, individual galaxies may have distributions that differ from it. Lastly, we apply our DREAMS results to the XENON1T experiment and demonstrate that the astrophysical uncertainties are comparable to the experimental ones, solidifying previous results in the literature obtained with a smaller sample of simulated Milky Way–mass halos.