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Sownak Bose

Publications and source records attributed to Sownak Bose.

At least 19 recordsLinked to original sources

Forged in Quenching: Morphological Transformation across Star-forming and Quiescent Galaxies in EAGLE

The connection between morphology and quenching in central galaxies is well established, but its physical origin remains widely debated. We address this by tracing the main progenitor branches of $z=0$ star-forming and quiescent central galaxies in the EAGLE cosmological simulation from $z\gtrsim4$. Their disc-to-total ratio and triaxiality tracks are indistinguishable until $z\approx 1$-$2$, when both diverge concurrently with the onset of quenching, whereas the size and supermassive black hole (SMBH) mass differences are established earlier. We identify four physically distinct channels linking galaxy morphology and quenching. First, mergers cause size growth, rotation suppression, triaxiality increase, and SMBH growth, with the accumulated SMBH mass subsequently causes the quenching of galaxies. Second, with merger history controlled, galaxy morphology modulates SMBH growth throughout the star-forming phase: compact, dispersion-dominated galaxies grow their SMBHs faster and are preferentially quenched, producing the size and morphology differences between star-forming and quiescent galaxies. Third, at fixed stellar mass and SMBH mass, compactness further facilitates the quenching of galaxies. Fourth, disc instability transforms compact oblate discs into prolate systems, with substantial size growth and suppressed rotation but negligible stellar mass growth. This secular channel contributes about half of the prolate galaxy population around $M_{\rm star}\approx 10^{10.6}\,\rm M_\odot$. Prior to quenching, the progenitors of quiescent galaxies already have smaller sizes, lower disc-to-total ratios, and more massive SMBHs than star-forming galaxies at the same epoch, by amounts comparable to their differences at $z=0$. Morphology therefore plays an active role in growing the SMBH and quenching the galaxy, rather than being passively inherited through progenitor bias.

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Modelling the expulsion of baryons from haloes: the role of feedback and of the cosmological constant

The extent to which galactic-scale astrophysical processes conspire with the underlying cosmological model to expel baryons from haloes remains a central question in galaxy formation. We present an analytical model for the gas distribution within and beyond haloes, based on the balance between gravitational collapse, hydrostatic pressure, and cosmic expansion. Our model predicts the halo-centric distance enclosing a baryon mass fraction equal to the cosmic value $f_{\rm b} = Ω_{\rm b}/Ω_{\rm m}$ (`closure radius') in an arbitrary $Λ$CDM cosmology. We compare the predictions with the results of six variants of the EAGLE cosmological, hydrodynamical simulation, encompassing values of the cosmological constant ranging from 0 to 100 times its observed value in our Universe, $Λ_0$. Despite its simplicity, our model exhibits excellent agreement with the simulations for haloes with mass $M_{\rm 200c} > 10^{11} M_\odot$ in the redshift range $0<z<3$, suggesting that it captures the key astrophysical processes and highlighting its robustness to the cosmological parameters. Thus, it provides the first physical explanation for the empirical closure radius--halo mass relation previously observed in simulations. Furthermore, we find that dark energy plays a non-negligible role in baryon evacuation: the simulations reveal that in the fiducial cosmological model, the closure radius at $z<2$ is $\sim 30\%$ larger than in an Einstein-de Sitter universe. In cosmologies with $Λ\geq 10 Λ_0$, dark energy emerges as the dominant factor in this process -- suggesting that, as our Universe transitions towards $Λ$-domination, dark energy eventually becomes the primary driver of baryon evacuation from massive haloes.

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PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

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Little Red Dots host Black Hole Stars: A unified family of gas-reddened AGN revealed by JWST/NIRSpec spectroscopy

We use the DAWN JWST Archive to construct and characterise a sample of 146 little red dots (LRDs) across 2.0<z<9.3, selecting all sources with v-shaped UV-optical continua from NIRSpec/PRISM spectra and compact morphologies in NIRCam/F444W imaging. We show that LRD continuum spectra are ubiquitously well described by modified blackbodies across ~$0.4-1.0μ$m, with typical T~5000K or $λ_{peak}$~$0.65μ$m across 2 dex in luminosity, and a tail toward T~2000K. LRDs therefore trace a locus in the Hertzsprung-Russell diagram that is directly analogous to stars on the Hayashi track, strongly supporting the picture that LRDs are AGN embedded in optically-thick dense gas envelopes. Hotter LRDs with $λ_{peak}<0.65μ$m typically have strong Balmer breaks, redder UV slopes and high optical luminosities; other LRDs show weak or no Balmer breaks, and wide variety in $β_{UV}$ and $L_{5100}$. Crucially, we demonstrate that the UV-optical continuum shapes and luminosities are strongly linked to the $Hα,\ Hβ$, [OIII] and OI line properties. There is a tight linear relation between the H$α$ and optical continuum luminosities, as well as H$α$ and OI$_{8446}$, indicating that Balmer, OI and optical emission must primarily be powered by the same source. The Balmer decrement increases strongly toward higher $L_{Hα}$, $L_{5100}$ and Balmer break strength, providing key evidence for luminosity-dependent effects of collisional (de-)excitation and resonant scattering in the gaseous envelopes. In contrast, we show that [OIII] emission likely originates from star-forming host galaxies, and that its strong correlation with Balmer break strength arises naturally from variation in the AGN-to-host ratio among the LRD population. Our work presents an empirical description of the nature and structure of LRDs, defining a new benchmark for ongoing LRD model developments.

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Galaxy formation in modified gravity -- II. galaxy halo connection and assembly bias

Modern surveys such as DESI and \textit{Euclid}, which collect data for hundreds of millions of galaxies to map the large-scale structure (LSS) of the Universe, hold the key to determining the cosmological parameters and testing new physics. This ambition, however, is limited by uncertainties in the galaxy-halo connection: the link between observed galaxies and the underlying, unobservable matter field, by accounting for effects such as galaxy bias and assembly bias (AB). These are particularly poorly-understood for modified gravity (MG) models, which are popular alternatives to the cosmological constant to explain accelerated expansion. We approach this problem using mock emission line galaxy (ELG) and luminous red galaxy (LRG) catalogues in $f(R)$ gravity matching the specifications of ongoing Stage-IV galaxy surveys, generated from state-of-the-art MG hydrodynamical simulations. While the interplay between MG -- especially the chameleon screening mechanism -- and galaxy formation leaves complicated imprints in the galaxy-halo connection, a simple physical picture emerges in which halo and galaxy formation are enhanced for progressively more massive haloes over time. We confirm that the basic galaxy-halo connection model, the halo occupation distribution (HOD), in which galaxy occupation is determined solely by halo mass, underestimates galaxy clustering strength in $Λ$CDM by $10$--$20\%$ at $z\lesssim1$ when neglecting AB, and demonstrate that MG introduces further complexity. Extending this model with a suitably-chosen environment density as a secondary HOD variable reduces the AB effect in all models to $2$--$3\%$ for $z\lesssim0.5$. This provides a well-motivated starting point for further works on minimising the impact of AB when testing non-standard cosmological models with LSS.

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Ruffled Feathers: Merger-driven galaxy size growth and structural transformation in EAGLE

Galaxy mergers drive both the size growth and the transformation from discs to spheroids, yet the prescriptions used to model these processes in semi-analytic frameworks have not been tested against the realistic merger population in cosmological hydrodynamical simulations. Using $\approx 4{,}500$ mergers identified in the EAGLE simulation, we test an energy-conservation estimator for post-merger galaxy sizes and quantify merger-driven morphological transformation. The predicted remnant half-stellar-mass radius matches the simulated descendant size with a scatter of $\approx 0.12$-$0.15$ dex and no significant systematic dependence on progenitor properties, while a commonly used dissipation correction applied to gas-rich mergers under-predicts the post-merger size by up to $\approx 0.4$ dex in a cosmological context and increases the overall scatter. The per-merger size growth increases monotonically with the stellar mass ratio of the merging pair, from $\lesssim 0.03$ dex for minor mergers to $\approx 0.10$ dex for equal-mass mergers. From the energy-conservation estimator, we analytically derive the size growth efficiency per unit accreted stellar mass, $η\equiv \mathrm{d}\log_{10} r_{\star}/\mathrm{d}\log_{10} M_{\star}$, and show that $η$ reaches $\approx 2$ only in the idealised limit of collisionless minor mergers with zero orbital energy; as $η$ is highly sensitive to the orbital energy at the time of merging, the minor merger channel cannot be established as the driver of the rapid size growth of massive galaxies without better constraints on this quantity. Beyond the size growth, mergers systematically reduce rotational support and increase triaxiality in proportion to mass ratio, but even the most nearly equal-mass mergers do not always fully destroy the disc, in tension with the complete disc destruction assumed in several semi-analytic models.

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Inflow-driven galaxy evolution - I. Revealing the physics of the fundamental metallicity relation

We present a unified physical framework for the fundamental metallicity relation (FMR), based on the mass-continuity equations. The FMR is not merely the anti-correlation between star formation rate (SFR) and gas metallicity ($Z_{\rm g}$) at fixed stellar mass ($M_\star$); it is a redshift-invariant surface in the $(M_\star,{\rm SFR},Z_{\rm g})$ space. We construct a minimal cosmological gas flow model, calibrated to reproduce the mass-metallicity relation, star-forming main sequence, and stellar-to-halo mass relation at $z=0-3$, and show that the FMR emerges as a prediction of the calibrated physics. Through controlled experiments that progressively simplify the model, we reveal that in a universe where both the star formation efficiency ($ε$) and mass-loading factor ($η$) are constants, the FMR reduces to a universal scaling between $Z_{\rm g}$ and $M_\star/$SFR, whose shape traces the transition from inflow-driven regime to equilibrium. The specific parameterisation of the observed FMR is not a fundamental symmetry but a contingent consequence of how $ε$ and $η$ depend on stellar mass and redshift. We show that the gaseous FMR (gFMR), defined in the $(M_\star,M_{\rm g},Z_{\rm g})$ space, is more fundamental than the standard FMR: in the inflow-driven limit, $Z_{\rm g}$ is proportional to $M_\star/M_{\rm g}$, and the approach to equilibrium is governed by $M_\star/M_{\rm g}$ and $η$ alone. We derive an analytic solution for an idealised version of the model that provides closed-form expressions relating $Z_{\rm g}$, $M_{\rm g}/M_\star$, and $η$, and show this framework accurately reproduces the cosmological gas flow model. By establishing the physical origin of the FMR and its connection to the more fundamental gFMR, we provide the theoretical foundation to turn metallicity scaling relations into precision probes of the baryon cycle over cosmic history.

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The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective

We present a model for the power spectrum of the density field of galaxies weighted by their star formation rate. This weighting is relevant in line-intensity mapping (LIM) when the observed line luminosity is strongly correlated with star formation, as is the case for the H$α$ line. Our model reproduces the measured power spectrum in the IllustrisTNG simulation to within a few per cent across all scales, with fitting parameters that have clear physical interpretations. On scales of tens of megaparsecs, the model accounts for the weighted non-linear bias of galaxies as well as halo exclusion (2-halo term). On smaller scales, it incorporates the weighted distribution of satellite galaxies within haloes (1-halo term). The random sampling of satellite galaxies introduces a galaxy shot noise term to the power spectrum on small scales, and their confinement to haloes introduces a halo shot noise term on large scales. Omitting satellite galaxies from the analysis results in an underestimation of both the large-scale bias and the mean intensity by approximately 30 per cent each at redshift 1.5. Assigning the intensity of satellites to the centre of their respective haloes affects the power spectrum on scales $k > 0.3$ h Mpc$^{-1}$. Our fitting function provides a well-motivated parametrisation that can be used to interpret data from upcoming LIM surveys.

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EFT-Ramses: a code to simulate the effective field theory of dark energy

While the standard $Λ$CDM paradigm is in excellent agreement with most current cosmological observations, theoretical challenges surrounding the cosmological constant ($Λ$) have strongly motivated the exploration of dynamical dark energy (DE) and modified gravity (MG) models. Investigating the physical nature of the cosmic acceleration requires N-body simulations to probe the non-linear growth of cosmic structure and prepare for the high-precision data from Stage-IV surveys. In this paper, we present EFT-RAMSES, a comprehensive extension of the ECOSMOG cosmological simulation code designed to explore non-linear structure formation in DE and MG scenarios. We embed the effective field theory of dark energy (EFTofDE) framework into this new numerical pipeline, utilising the $α$-basis parameterisation to provide a versatile, model-agnostic, computational engine. By consolidating diverse scalar and vector-tensor theories---including the normal and self-accelerating Dvali-Gabadadze-Porrati (DGP) models, cubic Galileons (cubic scalar Galileon (csG), cubic vector Galileon (cvG) and generalised cubic covariant Galileon (GCCG)), and generic effective field theory (EFT) parameterisation---into a single "master" Vainshtein equation, this pipeline bypasses the need for model-specific solvers and easily specialises to any particular model. As validations, we perform high-resolution N-body simulations for the normal-branch DGP (nDGP), csG, GCCG, and EFT models, comparing the resulting matter power spectra against dependent and independent codes such as legacy ECOSMOG and HiCOLA, as well as linear theory, and find excellent agreement. EFT-RAMSES provides a robust and versatile computational tool for precision cosmological tests of DE and MG using upcoming cosmological surveys. The code is available for download from the GitHub EFT-RAMSES repository.

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The dark matter halo mass function in the $Λ\mathrm{CDM}$ cosmology at all times and over all scales -- from planetary to galaxy cluster masses

The dark matter halo mass function is one of the most fundamental predictions of structure formation theory and cosmological simulations. We present the full halo mass function in the $Λ$ cold dark matter ($Λ\mathrm{CDM}$) model, ranging from a planetary mass ($10^{-6}\,\mathrm{M}_\odot$; the thermal cutoff in the initial power spectrum for a fiducial CDM particle mass of $100\,\mathrm{GeV}$) to the mass of a rich galaxy cluster ($10^{15.5}\,\mathrm{M}_\odot$), and from redshift, $z=30$ to the present. To span this very large dynamic range, we combine our earlier Voids-within-Voids-within-Voids (VVV) set of simulations (Wang et al) with large volume, lower resolution cosmological simulations. We develop a subsampling method to extract subvolumes from the original simulations, allowing us to reconstruct the global halo mass function from the biased underdense VVV regions. We show that the results agree reasonably well among the sets of simulations on different scales and environments. We provide a fitting formula for the dark matter halo mass function based on the work of Reed et al. calibrated with our simulations, such that it can be applied at all scales, all environments and all times, with deviations of $\sim2-3\%$ at $z < 2$ and $\sim 7\%$ at higher redshift $z \gtrsim 5$. This formula is also accurate at least for a restricted set of models we tested with modest deviations from $Λ\mathrm{CDM}$ in the values of some of the cosmological parameters. A python code is publicly available at https://github.com/haonan-zheng/hmfc.

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JWST spectroscopy of galaxies at $z>10$: Damped Ly$α$ absorbers reveal efficient star formation and hidden redshift biases

Recent observations with JWST have revealed a remarkable population of surprisingly luminous galaxies at redshifts $z>10$. Their abundance exceed predictions from simulations and empirical extrapolations from lower redshifts, suggesting a transition in the physical conditions under which the first stars formed. Here we investigate the physical conditions of a select sample of 25 galaxies with robust redshift measurements at $z_{\rm spec}\geq 10$ observed with JWST/NIRSpec Prism. We characterize their star-formation efficiency, `burstiness', and presence of strong rest-frame UV nebular lines in relation to the density of the local neutral atomic hydrogen (HI) gas reservoirs they are embedded in. We find that the prominence of strong rest-UV lines are correlated with the burstiness of the galaxies, defined as ${\rm SFR_{10\,Myr} / SFR_{100\,Myr}}$. In contrast, there are no strong connections between the HI gas column density derived from the damped Ly$α$ absorption (DLA) and the $M_{\rm UV}$ brightness, ${\rm SFR_{10\,Myr} / SFR_{100\,Myr}}$, and prominence of rest-UV lines. The most bursty galaxies show a large variation in star-formation efficiencies and HI gas surface densities, though typically with very short depletion timescales, $t_{\rm dep} \lesssim 20$\,Myr. This necessites rapid gas depletion times and external replenishment from infalling, pristine gas, powering starburst episodes on equally short timescales. We further quantify the impact of strong DLAs in galaxy spectra on photometric and Ly$α$-break redshift-inferences, finding average redshift biases of $\langle z \rangle =0.39$ and $0.14$, respectively, when not incorporating DLAs on the emergent spectra. We show the effect of this bias on new measurements of the cosmic UV luminosity density, $ρ_{\rm UV}$, derived here at $z>10$, finding that this has a marginal impact on the UV luminosity function.

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Interpretable machine learning of halo gas density profiles: a sensitivity analysis of cosmological hydrodynamical simulations

Stellar and AGN-driven feedback processes affect the distribution of gas on a wide range of scales, from within galaxies well into the intergalactic medium. Yet, it remains unclear how feedback, through its connection to key galaxy properties, shapes the radial gas density profile in the host halo. We tackle this question using suites of the EAGLE, IllustrisTNG, and Simba cosmological hydrodynamical simulations, which span a variety of feedback models. We develop a random forest algorithm that predicts the radial gas density profile within haloes from the total halo mass and five global properties of the central galaxy: gas and stellar mass; star formation rate; mass and accretion rate of the central black hole (BH). The algorithm reproduces the simulated gas density profiles with an average accuracy of $\sim$83-90% over the halo mass range $10^{9.5} \, \mathrm{M}_{\odot} < M_{\rm 200c} < 10^{15} \, \mathrm{M}_{\odot}$ and redshift interval $0<z<4$. For the first time, we apply Sobol statistical sensitivity analysis to full cosmological hydrodynamical simulations, quantifying how each feature affects the gas density as a function of distance from the halo centre. Across all simulations and redshifts, the total halo mass and the gas mass of the central galaxy are the most strongly tied to the halo gas distribution, while stellar and BH properties are generally less informative. The exact relative importance of the different features depends on the feedback scenario and redshift. Our framework can be readily embedded in semi-analytic models of galaxy formation to incorporate halo gas density profiles consistent with different hydrodynamical simulations. Our work also provides a proof of concept for constraining feedback models with future observations of galaxy properties and of the surrounding gas distribution.

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Dwarf stellar haloes: a powerful probe of small-scale galaxy formation and the nature of dark matter

We use N-body cosmological simulations and empirical galaxy models to study the merger history of dwarf-mass galaxies (with M_halo~10^10 M_Sun). Our input galaxy models describe the stellar mass-halo mass relation, and the galaxy occupation fraction. The number of major and minor mergers depends on the type of dark matter; in particular, minor mergers are greatly suppressed in warm dark matter models. In addition, the number of mergers that bring in stars is strongly dependent on the galaxy occupation model. For example, minor mergers are negligible for stellar halo growth in models with a high mass threshold for galaxy formation (i.e. 10^9.3 M_Sun at z=0). Moreover, this threshold for galaxy formation can also determine the relative difference (if any) between the stellar haloes of satellite and field dwarfs. Using isolated simulations of dwarf-dwarf mergers, we show that the relative frequency of major and minor mergers predict very different stellar haloes: Typically, "intermediate" dark matter merger ratios (~1:5) maximise the growth of distant stellar haloes. We discuss the observability of dwarf stellar haloes and find that the surface brightness of these features are incredibly faint. However, when several dwarfs are stacked together models that form particularly rich stellar haloes could be detectable. Finally, we show that stellar streams in the Galactic halo overlapping in phase-space with known dwarf satellites are likely remnants of their stripped stellar haloes. The mere existence of dwarf stellar haloes can already put constraints on some small-scale models, and thus observational probes should be a high priority.

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Halo mass functions in mixed cold and fuzzy dark matter models

We investigate the impact of mixed cold and fuzzy dark matter (MDM) cosmologies on the halo mass function (HMF) using numerical simulations performed with the AxiREPO framework. We consider models in which an ultralight axion-like component with mass $m =10^{-24.5} \mathrm{eV}$ constitutes a fraction $f \leq 0.3$ of the total dark matter. To enable consistent halo identification in mixed-species scenarios, we develop a grid-based halo-finding pipeline that combines the particle-based cold dark matter (CDM) and wave-like fuzzy dark matter (FDM) components into a unified density field. We find that FDM traces the large-scale CDM distribution while suppressing small-scale structure through wave interference effects, leading to a reduction in the abundance of low-mass haloes and modifying the HMF in a manner dependent on redshift and FDM fraction. Increasing the FDM fraction produces a systematic downward shift in the HMF and modifies its high-mass slope. Motivated by these trends, we introduce a phenomenological model that maps CDM HMFs to their MDM counterparts using a suppression function with parameters dependent on redshift and FDM fraction. This model reproduces the simulated HMFs within approximately 0.1 to 0.2 dex across the parameter space explored ($1 \leq z \leq 4$, $f \leq 0.3$). Our results provide a computationally efficient method for predicting structure formation in MDM cosmologies without requiring dedicated simulations for each parameter choice, and establish a framework for exploring the impact of MDM on cosmological structure formation.

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Implications of the nanoHertz Gravitational-Wave Background for Galactic Feedback and Massive Black Hole Growth

We investigate how pulsar timing array (PTA) measurements of the nanoHertz gravitational-wave background (GWB) can constrain models for the growth history of supermassive black holes (SMBHs) and how active galactic nucleus (AGN) and stellar feedback models can affect GWB predictions. Feedback regulates supermassive black hole (SMBH) growth, altering the black hole mass function (BHMF). Using BHMFs drawn from multiple cosmological simulation suites including IllustrisTNG, MillenniumTNG, Simba, and CAMELS, and combining these with a quasar-based SMBH binary population framework, we predict the resulting GWB amplitude under a range of different stellar and AGN feedback prescriptions. We find that the choice of both stellar and AGN feedback models alters the high-mass end of the BHMF and changes the predicted GWB amplitude by up to a factor of 2 for the fiducial simulations and a factor 10 for extreme feedback variations in CAMELS. Models with inefficient or absent AGN feedback produce abundant SMBHs and yield GWB amplitudes consistent with PTA data, yet fail in producing realistic galaxies. Fiducial models of AGN and stellar feedback suppress SMBH growth too much and under-predict the expected signal, an effect which could possibly be mitigated by more realistic black hole seeding and growth prescriptions. The mismatch between the GWB amplitudes predicted by cosmological simulations and that inferred by PTA measurements suggests that SMBH growth is more efficient or occurs earlier than captured by current models. This demonstrates that PTA measurements provide a powerful new probe of not only the SMBH population but also feedback physics.

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Little Red Dot $-$ Host Galaxy $=$ Black Hole Star: A Gas-Enshrouded Heart at the Center of Every Little Red Dot

The central engines of Little Red Dots (LRDs) may be ``black hole stars" (BH*s), early stages of black hole growth characterized by dense gas envelopes. So far, the most direct evidence for BH*s comes from a handful of sources where the host galaxy is completely outshone as suggested by their remarkably steep Balmer breaks. Here we present a novel scheme to disentangle BH*s from their host galaxies assuming that the [OIII]5008Å line arises exclusively from the host. Using a sample of 98 LRDs ($z$~$2-9$) with high quality NIRSpec/PRISM spectra, we demonstrate that the host-subtracted median stack displays a Balmer break $>2\times$ stronger than massive quiescent galaxies, with the rest-optical continuum resembling a blackbody-like SED ($T_{\rm{eff}}$~$4050$ K, $\log(L_{\rm{bol}})$~$43.9$ erg s$^{-1}$, $R_{\rm{eff}}$~$1300$ au). We measure a steep Balmer decrement (H$α$/H$β>10$) and numerous density-sensitive features (e.g., FeII, HeI, OI). These are hallmark signatures of dense gas envelopes, providing population-level evidence that BH*s indeed power LRDs. In the median LRD, BH*s account for $\sim20\%$ of the UV emission, $\sim50\%$ at the Balmer break, and $\sim90\%$ at wavelengths longer than H$α$ with the remainder arising from the host. BH*s preferentially reside in low-mass galaxies ($M_{\rm{\star}}$~$10^{8}\,{\rm M}_{\rm{\odot}}$) undergoing recent starbursts, as evidenced by extreme emission line EWs (e.g., [OIII]5008Å~$1100$Å, CIII]~$12$Å), thereby favoring BH* origins linked to star-formation. We show V-shaped LRD selections are biased to high BH*/host fractions ($\gtrsim60\%$ at 5500Å) -- less dominant BH*s may be powering JWST's blue broad-line AGN. We find BH*s are so commonplace and transient (duty cycle $\sim1\%$, lifetime $\sim10$ Myrs) that every massive black hole may have once shone as a BH*.

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The galaxy ultraviolet luminosity function from $z=7$ to $15$ in the COLIBRE simulations

JWST has enabled the detection of galaxies in the earliest stages of cosmic history. We compare the ultraviolet luminosity functions (UVLFs) at redshifts $z=7-15$ predicted by the new cosmological hydrodynamics simulations, COLIBRE with observations, including those from JWST. The UV luminosities of COLIBRE galaxies are derived using the radiative transfer code SKIRT, which tracks stellar emission and its processing through the multi-phase interstellar medium and dust distribution predicted by COLIBRE. We find that although COLIBRE is consistent with the observed evolution of the stellar mass function up to $z=12$, its dust-attenuated UVLFs fall systematically below the observations at the bright end: at the number density of $10^{-6}\,\mathrm{Mpc^{-3}\,mag^{-1}}$, the brightest galaxies are underluminous by $\approx 1\,\rm mag$ at $z=7$, increasing to $\approx 2.5\,\rm mag$ at $z=15$. Accounting for observational uncertainties brings the COLIBRE UVLFs closer to the observational data, but does not fully resolve the discrepancy. Ignoring dust attenuation allows COLIBRE to produce sufficiently bright galaxies at $7\lesssim z \lesssim 12$, while at $z=15$, COLIBRE still underpredicts the luminosities of the brightest galaxies, indicating the need for additional physical mechanisms to boost the UV luminosities at the earliest cosmic epochs, such as a ''top-heavy'' stellar initial mass function. We fit the COLIBRE UVLFs with Schechter functions and calculate the evolution of the best-fit parameters. We find that the galaxy number density decreases, the characteristic luminosity becomes fainter and the faint-end slope becomes steeper towards higher redshifts. The UV luminosity density decreases by a factor of $\approx 300$ from $z = 7$ to $z = 15$.

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Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric model for galaxy clusters can lead to biases in the estimates of cluster properties. In this work, we present a deep-learning approach for estimating the triaxiality and orientations of massive galaxy clusters (those with masses $\gtrsim 10^{14}\,M_\odot h^{-1}$) from 2D observables. We utilize the flagship hydrodynamical volume of the suite of cosmological-hydrodynamical MillenniumTNG (MTNG) simulations as our ground truth. Our model combines the feature extracting power of a convolutional neural network (CNN) and the message passing power of a graph neural network (GNN) in a multi-modal, fusion network. Our model is able to extract 3D geometry information from 2D idealized cluster multi-wavelength images (soft X-ray, medium X-ray, hard X-ray and tSZ effect) and mathematical graph representations of 2D cluster member observables (line-of-sight radial velocities, 2D projected positions and V-band luminosities). Our network improves cluster geometry estimation in MTNG by $30\%$ compared to assuming spherical symmetry. We report an $R^2 = 0.85$ regression score for estimating the major axis length of triaxial clusters and correctly classifying $71\%$ of prolate clusters with elongated orientations along our line-of-sight.

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