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Rachel S. Somerville

Publications and source records attributed to Rachel S. Somerville.

At least 19 recordsLinked to original sources
arXiv2026

Prevention is better than cure? Feedback from high specific energy winds in cosmological simulations with Arkenstone

We deploy the new Arkenstone galactic wind model in cosmological simulations for the first time, allowing us to robustly resolve the evolution and impact of high specific energy winds. In a (25 $h^{-1}$ Mpc)$^3$ box we perform a set of numerical experiments that systematically vary the mass and energy loadings of such winds, finding that their energy content is the key parameter controlling the stellar to dark matter mass ratio. Increasing the mass loading, at fixed energy, actually results in mildly enhanced star formation, counter to prevailing wisdom, due to the wind becoming cooler. Of the simple parametrisations that we test, we find that an energy loading that scales inversely with halo mass best matches a wide range of observations and can do so with mass loadings drastically lower than those in most previous cosmological simulations. In this scenario, much less material is ejected from the interstellar medium. Instead, winds both heat gas in the circumgalactic medium, slowing infall onto the galaxy, and also drive shocks beyond the virial radius, decreasing the halo-scale accretion rate. We can also report that a much lower fraction of the available supernova energy is needed in preventative galaxy regulation than required by ejective wind feedback models such as IllustrisTNG. This is a Learning the Universe collaboration publication.

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arXiv2026

Little Red Dots: One Photometric Tag Concealing Diverse Spectroscopic Flavors of Massive Star Formation and Black Hole Activity

We compile JWST/NIRSpec prism and MIRI data for 249 Little Red Dots (LRDs) at 2.3<z<9.3, forming a representative spectroscopic subset of NIRCam-selected LRDs. We derive a median stacked spectrum covering rest-frame 0.09-1.2 $μ$m, with MIRI photometry extending the spectral energy distribution to 4 $μ$m. Four additional stacks for subsamples defined by optical-to-UV luminosity ratios show that LRDs form a heterogeneous population spanning diverse continuum slopes and line properties. Assuming LRDs host super-massive black holes (BHs) surrounded by dense gas clouds, and stars accompany this core, we infer masses of $M_{BH}\sim10^{6.0-6.5}$ M$_\odot$ and $M_\bigstar\sim10^{8.3}$ M$_\odot$, corresponding to BH-to-stellar mass ratios of 1-2%. The stacks show ubiquitous UV and optical FeII emission, indicating a direct view of the broad-line region and high (but sub-Eddington) accretion ($λ_{Edd}=0.6\pm0.2$). We find a significant stellar contribution in the far-UV, reaching $\sim80$% in the bluest systems. Possible Wolf-Rayet features (HeII$λ$4687, nitrogen lines) are identified, tracing a young (3-7 Myr) compact starburst event. We also detect strong Balmer breaks and atypical Balmer, Paschen, [OIII], and optical and near-infrared HeI line ratios, and an absorption at $\sim4550$ Angstrom (probably linked to FeII), all consistent with radiative-transfer effects in high-density gas with warm temperatures (4000-7000 K). We find a diversity of LRD flavors modulated by the luminosity ratio between between a short ($\lesssim20$ Myr) and intense phase of BH activity, the most extreme stage lasting $\sim3-7$ Myr, characterized by near-Eddington-limit radiation, and a nuclear and compact starburst dominated by massive stars (even super-massive, $\mathrm{M}_\mathrm{SMS}\sim10^{5}$ M$_\odot$), all embedded in dense gas with modest dust content producing a variety of optical depths.

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arXiv2026

Skyfire: A Spectroscopic Census of Little Red Dots and Broad-Line AGN in the CEERS Field

We present the Skyfire program, a 21-hour Cycle 3 JWST/NIRSpec survey with the G395M medium-resolution grating covering five pointings in the Extended Groth Strip. The survey is designed to carry out a systematic census of faint, broad-line AGN candidates with a range of rest-optical colors identified at z > 3 by the Cosmic Evolution Early Release Science (CEERS) Survey. Our primary targets include photometrically-selected Little Red Dots (LRDs), blue extreme emission line galaxies (EELGs), and X-ray-detected AGN. We present spectroscopic redshifts for 178 sources observed by Skyfire, as well as a catalog of 34 sources with broad emission lines in the redshift range 2.7 < z < 6.5. Our broad-line sample includes 18 LRDs, which brings the spectroscopic completeness of LRDs with $β_{\rm opt}>-0.02$ in the CEERS field to 73%. We explore the prevalence of broad emission lines in photometrically-selected LRDs as a function of their rest-frame continuum slope and observed color distributions. We find the broad-line detection fraction in LRDs remains high at relatively blue rest-optical colors and extends smoothly into the bluer regime occupied by Little Blue Dots (LBDs). We discuss the implications of this finding for LRD-LBD unification scenarios. We also find that only 18% (3/17) of EELGs selected primarily for their high-equivalent-width emission lines and compact morphologies exhibit broad emission lines, suggesting these criteria alone are poor predictors of broad-line activity. We present a revised set of LRD selection criteria that captures bluer sources by extending down to $β_{\rm opt}=-0.52$. Using this new threshold, we find that $80.9^{+4.6}_{-7.5}\%$ of photometrically-selected LRDs brighter than 26.5 in F444W show broad emission lines and that LRDs make up 54% of the overall broad-line population identified in the CEERS field.

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arXiv2026

Introducing sapphire: Towards Hybrid Physics-Informed, Data-Driven Modeling of Galaxy Formation

Semi-analytic models (SAMs) have been treating galaxy populations as dynamical systems for $\gtrsim50$ years, but their evolution equations remain poorly constrained. We introduce sapphire, a modular, automatically differentiable, GPU-accelerated SAM written in JAX. For the first time, we compute exact Jacobian and Hessian matrices of a galaxy formation SAM, using the Pandya et al. (2023) nonlinear differential equation system as an example. These allow efficient, interpretable local and global sensitivity analyses, which reveal that supernova energy loading is the key astrophysical parameter. We use gradient descent and Hamiltonian Monte Carlo (HMC) to perform comprehensive mock parameter recovery tests. These indicate that the $z=0$ stellar-to-halo-mass relation alone does not contain enough information to infer many astrophysical parameters. Using observations of star-forming galaxies from the MaNGA survey and the Behroozi et al. (2019) empirical model as one baseline, we derive multiple posteriors assuming different combinations of data, including $z=0$ interstellar medium gas fractions and metallicities. The inferred physical parameters suggest that galaxies self-regulate their star formation primarily through preventative rather than ejective feedback, though this remains uncertain due to the lack of satellite galaxies, black holes and multi-phase galactic atmosphere physics. Both Fisher and HMC forecasts demonstrate the potential of sapphire to enable precision inference for galaxy formation and cosmology in a hybrid physics-informed, data-driven way, but more work is needed to expand its library of models and methods. We make sapphire publicly available at https://github.com/virajpandya/sapphire.

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arXiv2026

Recycled Gas Dominates the Metal-rich Fuel of Supermassive Black Holes

Understanding the origin and chemical properties of gas accreted by supermassive black holes (SMBHs) is essential for linking black hole growth to galaxy evolution. Using a suite of 30 high-resolution cosmological zoom-in simulations, we investigate the chemical properties of gas accreted onto SMBHs in massive galaxies with stellar masses of $10^{10.9-11.9}\,\rm M_\odot$ and black hole masses of $10^{8.5-9.7}\,\rm M_\odot$ at $z=0$. By tracing the full cosmological histories of individual gas particles, we identify their origins and enrichment pathways. The accreted gas is classified into four categories: ``early'' gas accreted during the early assembly phase of the main halo, ``external'' gas originating from other galaxies or subhalos, ``recycled'' gas enriched through stellar evolution processes within the primary galaxy, including asymptotic giant branch (AGB) winds and supernova ejecta, and ``smooth'' gas accreted from the intergalactic medium. We find that recycled gas dominates the accretion budget and is already metal rich at early epochs. Gas from other origins typically undergoes gradual chemical enrichment within the galactic environment prior to black hole accretion. The mean abundance ratios show only weak redshift evolution and are broadly compatible with the high metallicities inferred for quasar broad-line regions. Our results suggest that metal-rich gas supply to SMBHs arises naturally from cosmological galaxy evolution and stellar recycling.

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arXiv2026

Galaxy Phase-Space and Field-Level Cosmology: The Strength of Semi-Analytic Models

Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physically motivated prescriptions. They have also proven to be an efficient alternative for generating accurate galaxy catalogs, offering a faster and less computationally expensive option compared to full hydrodynamical simulations. In this paper, we demonstrate that using only galaxy $3$D positions and radial velocities, we can train a graph neural network coupled to a moment neural network to obtain a robust machine learning based model capable of estimating the matter density parameters, $Ω_{\rm m}$, with a precision of approximately 10%. The network is trained on ($25 h^{-1}$Mpc)$^3$ volumes of galaxy catalogs from L-Galaxies and can successfully extrapolate its predictions to other semi-analytic models (GAEA, SC-SAM, and Shark) and, more remarkably, to hydrodynamical simulations (Astrid, SIMBA, IllustrisTNG, and SWIFT-EAGLE). Our results show that the network is robust to variations in astrophysical and subgrid physics, cosmological and astrophysical parameters, and the different halo-profile treatments used across simulations. This suggests that the physical relationships encoded in the phase-space of semi-analytic models are largely independent of their specific physical prescriptions, reinforcing their potential as tools for the generation of realistic mock catalogs for cosmological parameter inference.

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arXiv2026

How to raise a supermassive black hole: interpreting early JWST AGN with the AESOPICA simulations

The active black holes uncovered by JWST in the early Universe are highly abundant and seemingly overmassive with respect to local scaling relations, challenging standard models of black hole formation and growth. Yet it remains unclear whether they trace an efficient early growth channel, the observable tail of a broader population, or suffer from systematic uncertainties in mass estimates. We introduce the AESOPICA project, a suite of twelve mid-volume ($L = 60\,\mathrm{Mpc}$) cosmological simulations based on the FABLE galaxy formation model, varying the black hole seed mass across the theoretical formation channels ($M_\mathrm{seed} = 10^{2}$-$10^{5} \, \mathrm{M_{\odot}}$), the accretion efficiency, including super-Eddington bursts, and the supernova feedback strength. We forward-model observational selection with BALMERSOPICA, a mock JWST broad-line survey pipeline that assesses the detectability of each simulated AGN for a given grating and exposure time. We find that the bulk of the JWST AGN population can be assembled from any seed mass provided the accretion efficiency is high, although light seeds require the most favourable accretion conditions explored. Applying broad-line selection naturally recovers the apparently overmassive population, with the detected AGN lying furthest above the intrinsic $M_\mathrm{BH}$-$M_\mathrm{stellar}$ relation for inefficient accretion models. Notably, the selected AGN lie on the local, weakly evolving $M_\mathrm{BH}$-$σ_\mathrm{stellar}$ relation, supporting a scenario where black holes assemble before the stellar component is fully established. Since efficient accretion rapidly erases the imprint of the initial seed mass, the low-mass end of the black hole mass function and host gas-phase metallicities offer the most promising discriminants between seeding channels.

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arXiv2026

Reading Between the Lines: Forward Modeling Dust, Continuum, and Spectral Cleaning for Multi-Line Intensity Mapping

Line intensity mapping (LIM) offers a tomographic view of galaxy evolution by measuring the aggregate emission from unresolved galaxies. In the optical and near-infrared, the line emission is accompanied by much brighter continuum emission that must be removed to recover line auto- and cross-power spectra. We develop a forward-modeling framework using a $\sim2$deg$^2$ lightcone drawn from a cosmological $N$-body simulation populated with galaxies using a physics-based semi-analytic model (SAM). We construct intensity maps for the stellar continuum and for the strongest optical lines, H$α$, H$β$, [O III] $\lambda5007$, and [O II] $\lambda3727$, including nebular dust attenuation tied to galaxy properties. From these cubes, we measure cross-channel angular power spectra, $C_\ell(λ_i,λ_j)$, and the normalized correlation matrix $r_{ij}$. In line-only maps, the correlation matrices show same-redshift ridges between emission lines, demonstrating how multi-line intensity mapping (MLIM) can isolate large-scale structure and probe dust attenuation. We show that dust suppresses the line cross-power by an amount that depends on galaxy properties, wavelength, and line pair, so a single overall amplitude cannot capture its effect. In total maps, however, the continuum dominates the raw correlations and hides much of the line-ridge structure. We therefore apply principal component analysis (PCA)-based spectral cleaning and quantify the line-transfer function using the simulation truth. Removing 20 PCA modes gives the best trade-off between line recovery and continuum suppression in our mock maps. Our results demonstrate the promise and challenges of extracting dust-sensitive LIM observables from SPHEREx-like observations, and highlight the need to model continuum cleaning and its transfer function in quantitative inference pipelines.

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arXiv2026

Origins of Extreme Emission-Line Ratios in z > 3 Galaxies: Insights from the Lumen Model

Optical emission-line ratios in star-forming galaxies at $z \sim 3$-8, such as [OIII]/H$β$ and [OIII]/[OII], are strongly offset from those at $z \sim 0$-2, pointing to more extreme ionization and ISM conditions in the early Universe. To constrain the physical origin of these offsets, we developed Lumen, a framework for modelling nebular emission from spatially distributed HII regions in cosmological simulations. We apply Lumen to IllustrisTNG50, validate its predictions at low redshift, and test a suite of proposed mechanisms for producing extreme line ratios at $z = 3$-8. We focus on the [NII]/H$α$ versus [OIII]/H$β$ (N2-BPT) diagram, the [SII]/H$α$ versus [OIII]/H$β$ (S2-VO87) diagram, and the [OIII]/[OII] versus ([OII]+[OIII])/H$β$ (O32-R23) diagram. We find that $α$-enhancement alone cannot explain the bulk of observations. Moderate offsets emerge from the combined effects of $α$-enhancement, a higher IMF upper-mass cutoff, and AGN contributions. The most extreme [OIII]/H$β$ and [OIII]/[OII] values require high ionization parameters powered by massive star clusters of $\gtrsim 10^5$-$10^6\,\mathrm{M}_\odot$, consistent with recent JWST observations. Reproducing the highest [NII]/H$α$ ratios additionally requires enhanced nitrogen abundances. Although gas densities of $n \sim 10^4\,\mathrm{cm}^{-3}$ can boost several diagnostic ratios, they suppress [SII]/H$α$ and are therefore in tension with current observations. Overall, models combining harder ionizing spectra, elevated ionization parameters from massive star clusters, and enhanced nitrogen abundances reproduce the observed high-$z$ galaxy population across the N2-BPT, S2-VO87, and O32-R23 diagrams. This successful model also motivates new demarcation lines for star-forming galaxies in the N2-BPT and S2-VO87 diagrams.

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arXiv2026

Learning the Universe with cosmological rescaling of merger trees and semi-analytic galaxy formation models

Learning cosmology from galaxy surveys requires large suites of simulations spanning the cosmological and astrophysical parameter space, yet hydrodynamical simulations of galaxy formation remain prohibitively expensive. Semi-analytic models offer an inexpensive, physically grounded alternative, but still require halo merger trees from $N$-body simulations, and densely sampling cosmological parameters in sufficient volume remains expensive. We address this by extending cosmological rescaling to operate directly on merger trees and applying it in the $Ω_{\rm m}$-$σ_8$ plane, running the Santa Cruz semi-analytic model for galaxy formation on the rescaled trees to produce galaxy populations across new cosmological and astrophysical parameters at negligible additional cost. A novel halo-profile-based correction, controlled by a single free parameter, suppresses systematic bias in rescaled halo masses to below the per cent level. We apply the method to parameter estimation of $Ω_{\rm m}$ and $σ_8$ given either the stellar mass function or the two-point correlation function, finding that as few as 64, and potentially fewer, base $N$-body simulations, rescaled to $\sim1000$ training samples, match the accuracy of 750 dedicated $N$-body simulations; rescaling to 3200 realisations improves the prediction of $Ω_{\rm m}$ by $\sim25\%$. Rescaling all merger trees from a single CAMELS-SAM $N$-body simulation costs $\sim0.1$ CPUh, compared to several thousand CPUh to run the simulation itself. We demonstrate a practical route to obtaining predictions of galaxy summary statistics across cosmological and astrophysical parameters, even with a relatively small number of base $N$-body simulations.

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arXiv2026

Investigating the star formation histories of galaxies from Cosmic Dawn to the Epoch of Reionization with the Santa Cruz SAM

The James Webb Space Telescope (JWST) has opened a new window onto galaxy evolution in the very early Universe. In this work, we leverage halo merger trees extracted from the GUREFT dark-matter-only cosmological simulation suite together with the Santa Cruz semi-analytic model (SAM) for galaxy formation to investigate the predicted star formation histories (SFHs) of galaxies from cosmic dawn (z ~ 14) to the end of the Epoch of Reionization (EoR; z~6). While we find that on average, median SFHs of galaxies across all masses are uniformly and rapidly rising over time from 14 < z < 6 as expected, individual galaxy SFHs show a range of diverse SFHs, even for a fixed terminal mass or redshift, with bursts and mini-quenching episodes in agreement with SFHs inferred from observations. The median lookback time to form the youngest 50% (t_50) and 90% (t_90) of galaxies' stars decreases weakly with increasing stellar mass, and strongly with the redshift of observation. For galaxies at z>12, we find typical values of t_50 < 30 Myr and t_90 < 70 Myr, a factor of ~3 to 4 shorter than for comparable galaxies near the end of EoR (z ~ 6). The young-star dominated nature of stellar populations in ultra-high-z galaxies implies that careful modelling of young stellar populations is crucial for obtaining accurate synthetic photometry. In addition, our results have important implications for interpreting observational indicators of star formation histories and timescales.

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arXiv2026

TNG SAM: Bridging Hydrodynamical Complexity and Semi-Analytic Efficiency to Model Galaxy Formation

All cosmological models of galaxy formation must navigate the trade-off between physical accuracy and computational efficiency. Hydrodynamical simulations provide spatially resolved predictions for the co-evolution of dark matter, gas, stars, and black holes, but rely on phenomenological subgrid models for small-scale processes (e.g., star formation). Semi-analytic models (SAMs), by contrast, gain efficiency through simplified, analytic treatments of the same processes, at the cost of reduced predictive scope. In this work, we leverage the strengths of the Santa Cruz SAM and the IllustrisTNG hydrodynamical simulation to develop the TNG SAM. Calibrated to reproduce baryon cycling in stellar feedback-dominated TNG galaxies ($\sim 10^{10}M_\odot < M_{200} < 10^{12}M_\odot$), the TNG SAM introduces several key updates to the Santa Cruz framework regarding: 1) halo gas (re-)accretion efficiency, 2) a cooling model that moves beyond the traditional cold/hot mode dichotomy, 3) explicit treatment of both galactic- and halo-scale outflows, 4) star formation efficiency, and 5) the circulation of metals between galaxies and their surroundings. These changes enable the TNG SAM to reproduce TNG's flow of gas and metals from the scale of the galaxy to the halo, as well as global galaxy (e.g., stellar mass) and halo (e.g. hot halo gas mass) properties within $\lesssim 30\%$ accuracy out to $z=6$. This work demonstrates that, with appropriate calibration, SAMs can capture the complex physics of galaxy formation modeled in hydrodynamical simulations while providing a flexible framework for studying galaxy evolution across the large cosmological volumes targeted by future observational surveys.

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arXiv2026

Supermassive Black Hole Assembly from Heavy Seeds with Dynamical Friction in the BRAHMA Simulations: Implications for JWST, LISA, and the Local Universe

The JWST discoveries of supermassive black holes (BHs) at $z \gtrsim 5$ may provide key insights into their seeding origins. Using new $[18{-}72~\rm Mpc]^3$ BRAHMA cosmological simulations, we investigate how variations in heavy-seed prescriptions, coupled with a subgrid dynamical friction model, shape BH populations at $z \sim 5$ and $z \sim 0$. We consider two "lenient'' seed models, in which all halos containing sufficient dense & metal-poor gas form $\sim10^4$ and $\sim10^5~M_{\odot}$ seeds, and a "strict'' seed model, in which $\sim10^5 M_{\odot}$ seeds form only under additional constraints motivated by direct collapse black hole formation. By $z \sim 5$, all models produce $M_*-M_{\rm BH}$ relations broadly consistent with the observed local Universe for $M_*\gtrsim10^9~M_{\odot}$ galaxies, but only the lenient scenarios generate systems near the upper envelope of the observed local scatter. In galaxies hosting $M_{\rm BH} \sim 10^8$-$10^9~M_{\odot}$ BHs, lenient production of $\sim10^5~M_{\odot}$ seeds also produces multiple overmassive systems with $M_{\rm BH}/M_* \gtrsim 0.01$. Although their growth is dominated by seeding and mergers, these systems reach luminosities of $\sim10^{43}$-$10^{45}\mathrm{erg s^{-1}}$, comparable to those inferred for JWST-detected BHs. As a key observational signature, the lenient seed models yield merger rates of $\gtrsim100\mathrm{yr^{-1}}$ and near-unity local BH occupation fractions even in galaxies with $M_* \lesssim 10^7~M_{\odot}$. In contrast, the strict seed model produces merger rates of only $\sim1\mathrm{yr^{-1}}$ and local occupation fractions of $\lesssim10\%$ for galaxies with $M_* \lesssim 10^8~M_{\odot}$. 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.

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arXiv2026

Learning the Universe with PRFM-vol: Introducing a new subgrid model for star formation in cosmological simulations

We introduce PRFM-vol, a new subgrid model for star formation in cosmological simulations that aims to increase the physical realism of cosmological simulations by leveraging results obtained with focused ISM simulations. We deploy a modified effective equation of state and calculate the star formation rate for each gas cell as a function of the ambient densities of gas, dark matter, and stars, based on the pressure-regulated feedback-modulated (PRFM) theory of star formation. Test simulations of our model in isolated galaxies show that we match PRFM predictions and TIGRESS scaling relations remarkably well, provided sufficiently high resolution is available. In particular, we are able to clearly demonstrate the impact of the stellar potential on the star formation rate, thereby retaining an important prediction of PRFM. We then apply our new model to cosmological multizoom simulations and find, compared to our previous TIGRESS/Schmidt model, a significant increase in the stellar scale heights and a slight increase in stellar mass. We demonstrate that modifying the effective equation of state significantly affects the morphology of simulated galaxies. Pronounced stellar clumps appear if the effective pressure at low hydrogen number densities is low, and disappear for higher pressure. We show that the formation of clumps is a result of Toomre instabilities, and conclude that simulated galaxy morphologies can be used to constrain effective equation of state models. Overall, our results establish PRFM-vol as a new self-consistent, physics-motivated subgrid model for star formation in high-resolution cosmological simulations.

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arXiv2026

Learning the Universe: The Structure of Dust Attenuation Curves in Galaxy Simulations

Dust attenuation is a major source of systematic uncertainty in both SED fitting and forward modeling of galaxy populations, yet the functional form used to parameterize attenuation curves has received surprisingly little systematic scrutiny. Particular unanswered questions include: how many free parameters are genuinely needed, and which analytic expression best captures the full diversity of attenuation curve shapes in galaxies across cosmic time? Using a large library of synthetic attenuation curves from TNG50 and TNG100 galaxies post-processed with the SKIRT radiative transfer code using three dust mixtures (Milky Way, SMC, and stellar dust), we show via Information-Ordered Bottleneck analysis that exactly four parameters are needed to capture the diversity of attenuation curves. Guided by this result, we use symbolic regression to derive a new, interpretable four-parameter attenuation model that outperforms existing parameterizations in recovering both attenuation curves and emergent fluxes across all dust mixtures explored. The four parameters of this model have clear physical interpretations: UV bump strength, FUV slope, UV-bump transition curvature, and large-scale optical slope. Their correlations with galaxy properties are primarily regulated by star-formation rate surface density, metallicity, and stellar-dust geometry, and are largely preserved across dust mixtures -- except for the bump-sensitive parameters, which retain a stronger dependence on grain composition. We further provide symbolic-regression scaling relations linking all four parameters to quasi-observable galaxy properties, offering a physically motivated route to assign realistic attenuation curves in SED fitting and forward modeling without radiative-transfer calculations.

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arXiv2026

A Rapid Evolution in the Observed Mbh/M* Relation at z > 3 Revealed via Spectro-photometric SED-Modeling

Spectroscopic observations from JWST have uncovered a plethora of active galactic nuclei (AGN) at z > 4 with black hole (BH) mass (Mbh) to stellar mass (M*) ratios significantly above the local relation when using standard virial mass scaling relations. However, M* estimates of AGN may be inaccurate due to limitations in spectral energy distribution (SED) fitting codes, exemplified by a lack of physically-motivated AGN line emission models. Here, we fit NIRSpec/PRISM spectra of 39 galaxies at z ~ 3.5-7 selected as broad-line AGN from the CEERS and RUBIES surveys. Applying kinematic decompositions from NIRSpec/G395M spectra, we fit their continuum and narrow-component line fluxes using the BEAGLE-AGN SED fitting tool. While limitations of BEAGLE-AGN make it difficult to model little red dots (LRDs), we find that M* estimates of non-LRDs are, surprisingly, only modestly impacted by the inclusion or not of AGN narrow-line region (NLR) and continuum emission model components. We further find that non-LRD AGN at z < 3.5 are consistent with the local Mbh/M* relation while those at z > 4.5 display elevated ratios. While we cannot rule out observational biases or systematic uncertainties as partial causes, this transition over just ~500 Myr is driven entirely by changes in M* rather than an evolving Mbh distribution. These findings are consistent with models in which rapid BH growth results in elevated Mbh/M* ratios at early times, with a swift late-time assembly of host galaxies returning sources to the local relation at z < 4.

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arXiv2026

Massive Galaxies Form Early and Gray: Stellar Assembly and Dust Attenuation at $\mathbf{z>3.5}$ from CAPERS

The stellar mass assembly of massive galaxies in the first few billion years of cosmic history remains a central challenge in galaxy formation. Galaxies with $M_\star \gtrsim 10^{10}M_\odot$ observed at $z \gtrsim 4$ must grow rapidly under conditions of intense gas accretion, feedback, and dust production. Observationally, their star-formation histories (SFHs) have been poorly constrained due to degeneracies inherent to broadband photometry. The advent of JWST enables direct spectroscopic access to detailed continuum shapes and rest-frame optical diagnostics at high redshift, providing a critical opportunity to reconstruct formation timescales of massive early galaxies. Here, we investigate massive galaxies using joint spectro-photometric SED fitting of JWST/NIRSpec prism spectroscopy from the CANDELS-Area Prism Epoch of Reionization Survey (CAPERS). Our sample comprises 148 galaxies selected photometrically with log $(M_\star/M_\odot) > 9.5$ at $z > 3.5$. We find that the most massive galaxies (log $(M_\star/M_\odot) > 10.5$) preferentially exhibit shallow, gray dust attenuation curves, consistent with higher dust optical depths and large grain sizes. We also find significant diversity in the time at which galaxies form 25% of their stellar mass. While formation timescales converge toward later cosmic times, galaxies with lower sSFR ($\lesssim -9$) at the observation epoch formed significantly earlier than systems with higher sSFRs. Across the full mass range, inferred assembly times are systematically earlier than model predictions, suggesting more rapid early growth than currently captured theoretically. These results underscore the importance of spectroscopic constraints and flexible SFH and dust models for reconstructing high-redshift massive galaxy formation histories.

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arXiv2026

ArkenstoneBH. A model for high-specific energy black hole feedback in cosmological simulations

AGN feedback is a key piece of galaxy evolution but is difficult to model due to its high specific energies, multiphase nature, and limited simulation resolutions. Arkenstone is a subgrid framework for representing multiphase flows in coarse resolution simulations that has been used to model stellar feedback driven galactic winds. It ensures the correct treatment of high specific energy feedback that would otherwise be challenging to model accurately in Lagrangian simulations. We introduce the new Arkenstone BH model, which extends the Arkenstone framework to model black hole feedback. We focus on describing the first piece of this framework, which follows the hot, high specific energy phase of these outflows. The second piece, which treats their multiphase structure with a scheme for modeling unresolved cold clouds, will be implemented and described in a later paper. We present Arkenstone BH in simulations of an isolated galaxy to demonstrate the framework and its ability to capture high specific energy feedback that interacts only weakly with cold, dense gas. We show how these energetic outflows suppress star formation in our isolated galaxy by counteracting the inflow of gas from the circumgalactic medium into the interstellar medium. This work is part of the "Learning the Universe" collaboration, which aims to understand the Universe's underlying physics and initial conditions.

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