arXiv subjects

William J. Roper

Publications and source records attributed to William J. Roper.

At least 19 recordsLinked to original sources

arXiv2026

First Light And Reionization Epoch Simulations (FLARES) XXI: The UV Indices of Galaxies in the Early Universe

UV absorption line indices trace chemical enrichment and star formation histories in high-redshift galaxies, yet their reliability as quantitative stellar metallicity, Z*, diagnostics remains uncertain. In this work, we combine synthetic spectral modelling with cosmological simulations to assess the behaviour of rest-frame UV indices in the early Universe. Using the forward-modelling package Synthesizer, we compute equivalent widths for UV indices based on BPASS stellar population synthesis models and examine their sensitivity to metallicity, star formation history, nebular emission, and model assumptions. We first investigate idealised stellar populations to establish the metallicity dependence of each index. Most indices show increasing equivalent width with metallicity, although the strength and linearity of this relation varies between features. The 1719 Angstrom index exhibits one of the most stable correlations with stellar metallicity, while the 1460 Angstrom index shows stronger sensitivity to nebular emission, bursty star formation, and model-dependent effects at high metallicity. We then apply these models to galaxies from the First Light and Reionization Epoch Simulations, FLARES, which provide realistic star formation and chemical enrichment histories. The simulated galaxy populations reproduce a stellar mass-metallicity relation and allow the UV indices to be tested in composite spectra. Although scatter increases due to population mixing and stochastic enrichment, the overall metallicity trends remain largely preserved. These predictions provide a theoretical framework for interpreting rest-frame UV spectra from JWST and future surveys, supporting the use of UV absorption indices as complementary tracers of stellar metallicity in early galaxies.

astro-ph.GA↗

arXiv2026

FLAGS II: Constraining Galaxy Formation Models with Dimensionality Reduction of Direct Observables

Comparisons between observations of galaxies and theoretical predictions are regularly performed using physical properties, which are inferred by the often slow and biased process of SED fitting. Forward modelling facilitates a reliable alternative, whereby models are evaluated using direct observables alone. However, these datasets become high-dimensional when collating observations from multiple telescopes, leading to sparse sampling, memory intensity and visualisation difficulties. We show that 2D embeddings of JWST and HST photometric fluxes, constructed using the non-linear dimensionality reduction algorithm UMAP, preserve sufficient information to differentiate between five models. Using a simple $χ^{2}$-like metric, we show that JAGUAR reproduces the population of bright galaxies $(m_{\mathrm{AB}}<26)$ in GOODS-S six times as well as SC-SAM and twelve times as well as SAGE. By adjusting the hyperparameters, we quantify how well each model replicates the distribution of SED shapes. The template SED approach of SPRITZ and the lack of photoionisation in SAGE cause significant discrepancies, highlighting the importance of comprehensive forward modelling. The embedded position of each galaxy can be identified $>100$ times faster than inferring its properties with Bayesian SED fitting, making this approach an ideal alternative for deriving statistical model constraints from large surveys such as LSST and Euclid, and performing simulation-based inference with CAMELS.

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arXiv2026

Stellar photoionisation modelling in SYNTHESIZER

Emission from photoionised gas surrounding young stellar populations ($H\text{II}$ regions) provides critical diagnostics of the physical conditions in star forming galaxies. This emission constrains the gas properties, the nature of ionising sources, and generates essential features for determining galaxy redshifts. To leverage spectroscopic observations to test galaxy formation models, it is essential to incorporate these emissions into synthetic datasets. Here, we present the integration of photoionised gas emission into the SYNTHESIZER package (https://synthesizer-project.github.io) and demonstrate its application. We quantify the impact of key modelling assumptions - including stellar population synthesis models, initial mass functions, ionisation parameter, gas density, geometry, abundance pattern, elemental depletion, and dust - on spectral diagnostics. Furthermore, we demonstrate the versatility of SYNTHESIZER through its application in different scenarios ranging from exploring emission in toy parametric models to large-volume cosmological simulations with realistic star formation and metal enrichment histories. Taken together, SYNTHESIZER provides a flexible, physically motivated framework to model stellar and nebular emissions, serving as a vital link between theory and observations in the era of next-generation spectroscopic missions.

astro-ph.GA↗

arXiv2026

Cloudy-Maraston: Integrating nebular continuum and line emission with the Maraston stellar population synthesis models

The James Webb Space Telescope has ushered in an era of abundant high-redshift observations of young stellar populations characterized by strong emission lines, motivating us to integrate nebular emission into the new Maraston stellar population model which incorporates the latest Geneva stellar evolutionary tracks for massive stars with rotation. We use the photoionization code Cloudy to obtain the emergent nebular continuum and line emission for a range of modelling parameters, then compare our results to observations on various emission line diagnostic diagrams. We carry out a detailed comparison with several other models in the literature assuming different input physics, including modified prescriptions for stellar evolution and the inclusion of binary stars, and find close agreement in the H$\rm β$, H$\rm α$, [N II]$λ6583$, and [S II]$λ6731$ luminosities between the models. However, we find significant differences in lines with high ionization energies, such as He II$λ$1640 and [O III]$λ5007$, due to large variations in the hard ionizing photon production rates. The models differ by a maximum of $\hat{Q}_{\rm [O III]λ5007} = \rm 6 \times 10^9 \; s^{-1} \, M_{\odot}^{-1}$, where these differences are mostly caused by the assumed stellar rotation and effective temperatures for the Wolf Rayet phase. Interestingly, rotation and uncorrected effective temperatures in our single star population models alone generate [O III] ionizing photon production rates higher than models including binary stars with ages between 1 to 8 Myr. These differences highlight the dependence of derived properties from SED fitting on the assumed model, as well as the sensitivity of predictions from cosmological simulations.

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arXiv2026

First Light and Reionization Epoch Simulations (FLARES) XXII: UV-dust spatial offsets at the Epoch of Reionisation

Recent observations have revealed intriguing offsets between the UV and FIR emission in high redshift galaxies. In this study, we use the First Light And Reionisation Epoch Simulations (\textsc{Flares}) to compute the spatial offset of ultraviolet (UV) and far-infrared (FIR) centres for a statistical sample (6890) of massive (M$_{\star}\, \gtrsim10^{9} \,{\rm M_{\odot}}$) high redshift galaxies ($z \in [5,10]$). The galaxies are post-processed with the \textsc{skirt} radiative transfer code, to obtain the full spectral energy distribution and surface brightness profile. We simulate \textit{James Webb Space Telescope (JWST)} Near Infrared Camera (NIRCam; rest-frame 1500 Å, $ \approx 0.031 ''$ resolution) and ALMA rest-frame 158 \um\ ($\approx$ $0.3''$ angular resolution) observations of the galaxies and then calculate the distance between the UV-FIR centres to analyse which physical processes drive the observed UV - FIR spatial offset. We find that $\sim16.23\%$ of galaxies exhibit spatial offsets of $\geq 2.5$ kpc between their UV and FIR emission peaks. We establish that the spatial offsets do not correlate with stellar mass, UV/FIR luminosity, and size. Offsets also do not correlate with AGN feedback or with large-scale environment or merger history. Galaxies with significant offsets preferentially have bluer UV slopes ($-2.5<β<-1.5$), consistent with recent star formation and dust-attenuated cores displacing the observed UV centroid. They show an accelerated star formation history, forming half their $z=5$ stellar mass $\sim$0.1 Gyr earlier than galaxies without offsets. These galaxies are enriched earlier than galaxies without an offset and show enhanced stellar metallicities, indicating a transition to an outward growth at higher redshifts ($z \geq 6$).

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arXiv2026

The LISA Astrophysics MBHcatalogues Project: A comparison of predictions of simulated massive black hole binaries

In the hierarchical paradigm of galaxy formation, central massive black holes (MBHs) are expected to coalesce after the merger of their host galaxies. One of the main goals of the Laser Interferometer Space Antenna (LISA) is to constrain the origin and growth of MBHs through their merger rates and mass distribution. Predicting MBH merger rates requires not only tracing their statistical population from large to small physical scales (kpc to sub-pc) but also modelling their formation, accretion, dynamics, mergers, and their galactic physical processes across cosmic time. This project is the result of a large collaborative effort undertaken by the LISA Astrophysics Working Group, bringing together its collective expertise on MBH formation, evolution, and modelling, to build a comprehensive understanding of MBH merger rates across cosmic time. The project compares various theoretical predictions of MBH merger rates, quantifies the spread, and evaluates the global astrophysical uncertainties of the LISA event rates. To build a unique and complete view, our work is based on about 20 semi-analytical models and cosmological simulations from the literature, all employing distinct approaches to modelling MBH and galaxy physics. To compute the merger rates, we also incorporate delays arising from the dynamical phase of MBH hardening to coalescence. We present the expected LISA merger rates given current galaxy formation models and discuss how the merger rate depends on model assumptions, such as the seeding model and the resolution of cosmological simulations.

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arXiv2026

Efficiently emulating distribution functions in gigaparsec volumes for varying cosmological parameters

We present a new method for emulating the halo mass function (HMF) and other distribution functions in large effective volumes, down to low halo masses, whilst simultaneously modifying large ranges of parameters, for a fraction of the cost of traditional periodic cosmological simulations. We demonstrate the method by selecting small regions, $V \sim (50 \,h^{-1}{\rm Mpc})^3$, with a range of overdensities from the Quijote suite, consisting of tens of thousands of $(1 \,h^{-1}{\rm Gpc})^3$ $N$-body simulation volumes run with varying $Λ$CDM parameters. We train a differentiable emulator, conditioned on the overdensity of the region and these global parameters, to reproduce the halo mass function in these regions. We then successfully recover the global distribution of halo masses of the entire box by integrating over the overdensity distribution. Our approach uses just $\sim\,$0.026% of the original simulation volume, and suggests that suites of targeted `zoom' simulations, extracted from low resolution parent volumes, can be used to emulate large volume simulations at a fraction of the computational cost, whilst simultaneously pushing the dynamic range to much lower masses than can be achieved in periodic simulations. We discuss emulation of other key dark matter and baryonic distribution functions, as well as higher order statistics, with implications for the interpretation of upcoming wide field surveys on observatories such as Euclid, Roman and Rubin.

astro-ph.CO↗

arXiv2026

Interpreting nebular emission lines in the high-redshift Universe

One of the most remarkable outcomes from \textit{JWST} has been the exquisite UV-optical spectroscopic data for galaxies in the high-redshift Universe ($z \geq 5$), enabling the use of various nebular emission lines to infer conditions of the interstellar medium. In this work, we assess the reliability of commonly used diagnostics for estimating the star formation rate (SFR), the ionising photon production efficiency ($ξ_{\rm ion}$), and the gas-phase oxygen abundance, focusing on dust corrections based on A$_{\rm V}$ (V-band attenuation) and the Balmer decrement. Using forward-modelled galaxy spectra from idealised toy models and the FLARES cosmological hydrodynamical simulations, we examine how variations in stellar populations and star-dust geometry affect these diagnostics. We find that the clumpy nature of \flares\ galaxies lead to strong internal variation in age, metallicity and dust attenuation, biasing the inferred quantities. In FLARES the SFRD at the bright-end of the SFR function can be underestimated by as much as $30\%$ compared to the true values. While the intrinsic $ξ_{\rm ion}$ in FLARES is nearly constant with stellar mass, estimates derived from H$α$ or H$β$ can be underestimated by more than 0.5 dex at high stellar masses ($>10^{9.5}$ M$_{\odot}$), introducing an artificial declining trend. Similarly, the dust-corrected mass-metallicity relation inferred from line ratios is significantly flatter than the intrinsic mass-weighted relation. These systematic offsets arise from the coupling between heterogeneous stellar populations and non-uniform star-dust geometry and depend on the diagnostic and the dust-correction method employed. No single dust-correction approach yields unbiased estimates of all quantities simultaneously, highlighting the need for forward modelling and comparisons in observed space for robust high-redshift inference.

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arXiv2025

First Light And Reionisation Epoch Simulations (FLARES) XX: Comparing semi-analytic models at high-redshift

We explore how the choice of galaxy formation model affects the predicted properties of high-redshift galaxies. Using the FLARES zoom resimulation strategy, we compare the EAGLE hydrodynamics model and the GALFORM, L-Galaxies, SC-SAM and SHARK semi-analytic models (SAMs) at $5\leq z \leq 12$. The first part of our analysis examines the stellar mass functions, stellar-to-halo mass relations, star formation rates, and supermassive black hole (SMBH) properties predicted by the different models. Comparisons are made with observations, where relevant. We find general agreement between the range of predicted and observed stellar mass functions. The model predictions differ considerably when it comes to SMBH properties, with GALFORM and SHARK predicting between 1.5-3 dex more massive SMBHs ($M_{\rm BH}>10^6\ {\rm M_\odot}$) than L-Galaxies and SC-SAM, depending on redshift. The second half of our analysis focuses on passive galaxies. We show that in L-Galaxies and SC-SAM, environmental quenching of satellites is the prevalent quenching mechanism, with active galactic nuclei (AGN) feedback having little effect at the redshifts probed. On the other hand, $\sim40\%$ of passive galaxies predicted by GALFORM and SHARK are quenched by AGN feedback at $z=5$. The SAMs are an interesting contrast to the EAGLE model, in which AGN feedback is essential for the formation of passive galaxies, in both satellites and centrals, even at high redshift.

astro-ph.GA↗

arXiv2025

Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer

We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible forward-modelling of galaxy SEDs and integrates the LtU-ILI package to ensure best practices in model training and validation. In this work we demonstrate Synference by training a neural posterior estimator on $10^6$ simulated galaxies, based on a flexible 8-parameter physical model, to infer galaxy properties from 14-band HST and JWST photometry. We validate this model, demonstrating excellent parameter recovery (e.g. R$^2>$0.99 for M$_\star$) and accurate posterior calibration against nested sampling results. We apply our trained model to 3,088 spectroscopically-confirmed galaxies in the JADES GOODS-South field. The amortized inference is exceptionally fast, having nearly fixed cost per posterior evaluation and processing the entire sample in $\sim$3 minutes on a single CPU (18 galaxies/CPU/sec), a $\sim$1700$\times$ speedup over traditional nested sampling or MCMC techniques. We demonstrate Synference's ability to simultaneously infer photometric redshifts and physical parameters, and highlight its utility for rapid Bayesian model comparison by demonstrating systematic stellar mass differences between two commonly used stellar population synthesis models. Synference is a powerful, scalable tool poised to maximise the scientific return of next-generation galaxy surveys.

astro-ph.GA↗

arXiv2025

Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours

We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation based inference approach. Using the Synthesizer code we simulate the dust attenuated ultraviolet-near infrared stellar emission from galaxies in thousands of cosmological hydrodynamic simulations from the CAMELS suite, including the Swift-EAGLE, IllustrisTNG, Simba & Astrid galaxy formation models. For each galaxy we calculate the rest-frame luminosity in a number of photometric bands, including the SDSS $\textit{ugriz}$ and GALEX FUV & NUV filters; this dataset represents the largest catalogue of synthetic photometry based on hydrodynamic galaxy formation simulations produced to date, totalling >200 million sources. From these we compile luminosity functions and colour distributions, and find clear dependencies on both cosmology and feedback. We then perform simulation based (likelihood-free) inference using these distributions to constrain $Ω_m$, $σ_8$, and four parameters controlling the strength of stellar and AGN feedback. Both colour distributions and luminosity functions provide complementary information on certain parameters when performing inference. We achieve constraints on the stellar feedback parameters, as well as $Ω_m$ and $σ_8$. The latter is attributable to the fact that the photometry encodes the star formation-metal enrichment history of each galaxy; galaxies in a universe with a higher $σ_8$ tend to form earlier and have higher metallicities, which leads to redder colours. We find that a model trained on one galaxy formation simulation generalises poorly when applied to another, and attribute this to differences in the subgrid prescriptions, and lack of flexibility in our emission modelling. The photometric catalogues are publicly available at: https://camels.readthedocs.io/

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arXiv2025

First Light And Reionization Epoch Simulations (FLARES) -- XIX: Supermassive black hole mergers in the early Universe and their environmental dependence

The upcoming space-based gravitational wave (GW) observatory, LISA, is expected to detect GW signals from supermassive black hole (SMBH) mergers occurring at high redshifts. However, understanding the origin and growth of SMBHs in the early Universe remains an open problem in astrophysics. In this work, we utilize the First Light And Reionization Epoch Simulations (FLARES), a suite of cosmological hydrodynamical zoom-in simulations, to study SMBH mergers at $5 \lesssim z \lesssim 10$ across a wide range of environments. Most mergers in FLARES involve secondary SMBHs near the seed mass ($m_{\rm seed} \approx 1.5 \times 10^{5}~{\rm M}_{\odot}$) while primary SMBHs span up to $10^{9}~{\rm M}_{\odot}$, resulting in mass ratios from $q \sim 10^{-4}$ to $1$, with a peak at $q \sim 1$. The number of mergers increases rapidly towards lower redshifts, and the comoving total number density scales with overdensity as $n_{\rm merger} = 10^{-3.81} (1 + δ)^{4.78}$. Denser regions host more massive mergers, with higher merger redshifts and lower mass ratios. Within the FLARES redshift range, LISA is expected to detect mergers with $10^{5} \lesssim M_{\rm tot}/{\rm M}_{\odot} \lesssim 10^{8}$ and $q \gtrsim 10^{-2}$, corresponding to a detection rate of $0.030~{\rm yr}^{-1}$ for events with signal-to-noise ratio ${\rm SNR} \geq 10$. Our study demonstrates the sensitivity of GW predictions at high redshifts to SMBH seed models and merger time delays, highlighting the need for improved modeling in future cosmological simulations to maximize LISA's scientific return.

astro-ph.GA↗

arXiv2025

Synthesizer: a Software Package for Synthetic Astronomical Observables

We present Synthesizer, a fast, flexible, modular and extensible platform for modelling synthetic astrophysical observables. Synthesizer can be used for a number of applications, but is predominantly designed for generating mock observables from analytical and numerical galaxy formation simulations. These use cases include (but are not limited to) analytical modelling of the star formation and metal enrichment histories of galaxies, the creation of mock images and integral field unit observations from particle based simulations, detailed photoionisation modelling of the central regions of active galactic nuclei, and spectro-photometric fitting. We provide a number of stellar population synthesis models, photoionisation code configurations, dust models, and imaging configurations that can be used 'out-of-the-box' interactively. The code can be used to quantitatively test the dependence of forward modelled observables on various model and parameter choices, and rapidly explore large parameter ranges for calibration and inference tasks. We invite and encourage the community to use, test and develop the code, and hope that the foundation developed will provide a flexible framework for a number of tasks in forward and inverse modelling of astrophysical observables. The code is publicly available at https://synthesizer-project.github.io/

astro-ph.IM↗

arXiv2025

First Light and Reionization Epoch Simulations (FLARES) -- XVIII: the ionising emissivities and hydrogen recombination line properties of early AGN

One of the most remarkable results from the \emph{James Webb Space Telescope} has been the discovery of a large population of compact sources exhibiting strong broad H$α$ emission, typically interpreted to be low-luminosity broad-line (Type 1) active galactic nuclei (BLAGN). An important question is whether these observations are in tension with galaxy formation models, and if so how? While comparisons have been made using physical properties (i.e.~black hole mass and accretion rate) inferred from observations, these require the use of SED modelling assumptions, or locally inferred scaling relations, which may be unjustified, at least in the distant high-redshift Universe. In this work we take an alternative approach and forward model predictions from the First Light And Reionisation Epoch Simulations (FLARES) suite of cosmological hydrodynamical zoom simulations to predict the observable properties of BLAGN. We achieve this by first coupling \flares\ with the \qsosed\ model to predict the ionising photon luminosities of high-redshift ($z>5$) AGN. To model the observed broad H$α$ emission we then assume a constant conversion factor and covering fraction, and the fraction of AGN that have observable broad-lines. With a reasonable choice of these parameters, \flares\ is able to reproduce observational constraints on the H$α$ luminosity function and equivalent width distribution at $z=5$.

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arXiv2025

First Light and Reionization Epoch Simulations (FLARES) -- XV: The physical properties of super-massive black holes and their impact on galaxies in the early universe

Understanding the co-evolution of super-massive black holes (SMBHs) and their host galaxies remains a key challenge of extragalactic astrophysics, particularly the earliest stages at high-redshift. However, studying SMBHs at high-redshift with cosmological simulations, is challenging due to the large volumes and high-resolution required. Through its innovative simulation strategy, the First Light And Reionisation Epoch Simulations (FLARES) suite of cosmological hydrodynamical zoom simulations allows us to simulate a much wider range of environments which contain SMBHs with masses extending to $M_{\bullet}>10^{9}\ M_{\odot}$ at $z=5$. In this paper, we use FLARES to study the physical properties of SMBHs and their hosts in the early Universe ($5\le\, z \le10$). FLARES predicts a sharply declining density with increasing redshift, decreasing by a factor of 100 over the range $z=5\to 10$. Comparison between our predicted bolometric luminosity function and pre-\emph{JWST} observations yield a good match. However, recent \emph{JWST} observations appear to suggest a larger contribution of SMBHs than previously observed, or predicted by FLARES. Finally, by using a re-simulation with AGN feedback disabled, we explore the impact of AGN feedback on their host galaxies. This reveals that AGN feedback results in a reduction of star formation activity, even at $z>5$, but only in the most massive galaxies. A deeper analysis reveals that AGN are also the cause of suppressed star formation in passive galaxies but that the presence of an AGN doesn't necessarily result in the suppression of star formation.

astro-ph.GA↗

arXiv2025

First Light And Reionisation Epoch Simulations (FLARES) XVI: Size Evolution of Massive Dusty Galaxies at Cosmic Dawn from UV to IR

We use the First Light And Reionisation Epoch Simulations (FLARES) to study the evolution of the rest-frame ultraviolet (UV) and far-infrared (FIR) sizes for a statistical sample of massive ($\gtrsim10^{9}$M$_{\odot}$) high redshift galaxies (z $\in$ [5,10]). Galaxies are post-processed using the SKIRT radiative transfer code, to self-consistently obtain the full spectral energy distribution and surface brightness distribution. We create mock observations of the galaxies for the Near Infrared Camera (NIRCam) to study the rest-frame UV 1500 $\unicode{xC5}$ morphology. We also generate mock rest-frame FIR (50 $μ$m) photometry and mock ALMA (158 $μ$m) (0.01"-0.03" and $\approx$0.3" angular resolution) observations to study the dust-continuum. We find the effect of dust on observed sizes reduces with increasing wavelength from the UV to optical ($\sim$0.6 times the UV at 0.4$μ$m), with no evolution in FIR sizes. Observed sizes vary within 0.4-1.2 times the intrinsic sizes at different signal to noise ratios (SNR = 5-20) across redshifts. The effect of PSF and noise makes bright structures prominent, whereas fainter regions blend with noise, leading to an underestimation (factor of 0.4-0.8) of sizes at SNR=5. At SNR=15-20, the underestimation reduces (factor of 0.6-0.9) at z=5-8 but due to PSF, at z=9-10, bright cores are dominant, resulting in an overestimation (factor of 1.0-1.2). For ALMA, low resolution sizes are effected by noise which acts as extended emission. The size evolution in UV broadly agrees with current observational samples and other simulations. This work is one of the first to analyse the panchromatic sizes of a statistically significant sample of simulated high-redshift galaxies, complementing a growing body of research highlighting the importance of conducting an equivalent comparison between observed galaxies and their simulated counterparts in the early Universe.

astro-ph.GA↗

arXiv2025

The effects of super-Eddington accretion and feedback on the growth of early supermassive black holes and galaxies

We present results of cosmological zoom-in simulations of a massive protocluster down to redshift $z\approx4$ (when the halo mass is $\approx10^{13}$ M$_\odot$) using the SWIFT code and the EAGLE galaxy formation model, focusing on supermassive black hole (BH) physics. The BH was seeded with a mass of $10^4$ M$_\odot$ at redshift $z\approx17$. We compare the base model that uses an Eddington limit on the BH accretion rate and thermal isotropic feedback by the AGN, with one where super-Eddington accretion is allowed, as well as two other models with BH spin and jets. In the base model, the BH grows at the Eddington limit from $z=9$ to $z=5.5$, when it becomes massive enough to halt its own and its host galaxy's growth through feedback. We find that allowing super-Eddington accretion leads to drastic differences, with the BH going through an intense but short super-Eddington growth burst around $z\approx7.5$, during which it increases its mass by orders of magnitude, before feedback stops further growth (of both the BH and the galaxy). By $z\approx4$ the galaxy is only half as massive in the super-Eddington cases, and an order of magnitude more extended, with the half-mass radius reaching values of a few physical kpc instead of a few hundred pc. The BH masses in our simulations are consistent with the intrinsic BH mass$-$stellar mass relation inferred from high-redshift observations by JWST. This shows that galaxy formation models using the $Λ$CDM cosmology are capable of reproducing the observed massive BHs at high redshift. Allowing jets, either at super- or sub-Eddington rates, has little impact on the host galaxy properties, but leads to lower BH masses as a consequence of higher feedback efficiencies.

astro-ph.GA↗

arXiv2024

First Light and Reionisation Epoch Simulations (FLARES) XVII: Learning the galaxy-halo connection at high redshifts

Understanding the galaxy-halo relationship is not only key for elucidating the interplay between baryonic and dark matter, it is essential for creating large mock galaxy catalogues from N-body simulations. High-resolution hydrodynamical simulations are limited to small volumes by their large computational demands, hindering their use for comparisons with wide-field observational surveys. We overcome this limitation by using the First Light and Reionisation Epoch Simulations (FLARES), a suite of high-resolution (M_gas = 1.8 x 10^6 M_Sun) zoom simulations drawn from a large, (3.2 cGpc)^3 box. We use an extremely randomised trees machine learning approach to model the relationship between galaxies and their subhaloes in a wide range of environments. This allows us to build mock catalogues with dynamic ranges that surpass those obtainable through periodic simulations. The low cost of the zoom simulations facilitates multiple runs of the same regions, differing only in the random number seed of the subgrid models; changing this seed introduces a butterfly effect, leading to random differences in the properties of matching galaxies. This randomness cannot be learnt by a deterministic machine learning model, but by sampling the noise and adding it post-facto to our predictions, we are able to recover the distributions of the galaxy properties we predict (stellar mass, star formation rate, metallicity, and size) remarkably well. We also explore the resolution-dependence of our models' performances and find minimal depreciation down to particle resolutions of order M_DM ~ 10^8 M_Sun, enabling the future application of our models to large dark matter-only boxes.

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