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Cedric G. Lacey

Publications and source records attributed to Cedric G. Lacey.

At least 19 recordsLinked to original sources

The galaxy ultraviolet luminosity function from $z=7$ to $20$ 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 $z=7-20$ predicted by a set of new cosmological hydrodynamical 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 $7\lesssim z \lesssim 12$, but 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 several hundred from $z = 7$ to $z = 15$.

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Cosmological simulations of the high-redshift galaxy population adopting a variable stellar initial mass function

JWST surveys reveal a greater space density of high-redshift UV-bright galaxies than predicted by conventional galaxy formation models. We present results from a $L=100$ cMpc cosmological simulation evolved to $z=5$ with a variation of the COLIBRE galaxy formation model that adopts a density-dependent stellar initial mass function (IMF), such that stellar populations formed from dense gas are born with a top-heavy IMF. Crucially, heavy element and dust yields, and supernova feedback energetics, are self-consistently adjusted to the changing IMF. We model UV/optical emission (including nebular emission) from galaxies and its attenuation by dust. By allowing a significant fraction of high-redshift star formation to proceed with a top-heavy IMF, the rest-frame far-UV luminosities of early galaxies are elevated by up to a factor of $\simeq4$ with respect to the fiducial COLIBRE L100m6 simulation, which assumes a universal Chabrier IMF. This enables the formation of galaxies with observed brightness up to $M_{\rm UV} \simeq -20$ at $z=15$ (c.f. $M_{\rm UV} \simeq -18.5$ in the fiducial simulation), illustrating the potential of star formation with a top-heavy IMF to alleviate tensions with JWST data. Later, the boost in far-UV emission is partly offset by attenuation due to increased dust surface densities from i) additional dust grain ejection from core-collapse supernovae and ii) efficient grain growth promoted by more metal-rich interstellar gas. The simulation reproduces the $z=5$ galaxy stellar mass function and rest-frame optical luminosity function with comparable accuracy to the fiducial simulation, and both simulations exhibit UV continuum slopes that are consistent with JWST observations.

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The COLIBRE-SKIRT pipeline: Calibration-free dust radiative transfer postprocessing for cosmological simulations

Context. Three-dimensional dust radiative transfer provides a powerful framework to connect cosmological galaxy simulations to multiwavelength observations. Until recently, in large-volume simulations, the formation of a cold ISM phase was prevented and dust was not evolved self-consistently. This required calibration of dust-to-metal ratios and extra subgrid dust attenuation in birth clouds, thereby reducing the predictive power. Aims. We present the COLIBRE-SKIRT pipeline, a calibration-free dust radiative transfer framework for the novel COLIBRE suite of large-volume cosmological simulations, which include a live dust model and directly simulate the multiphase ISM. Our primary aim is to establish a reference pipeline for generating multiwavelength mock observables from these simulations. As a first application, we produce far-ultraviolet (FUV) to far-infrared (FIR) spatially integrated spectra and assess them by comparison with the observed low-redshift cosmic spectral energy distribution (CSED). Methods. We apply the SKIRT dust radiative transfer code to the COLIBRE simulations. Dust masses and species fractions are taken directly from the simulation, and no birth cloud model is added in postprocessing. We introduce a "split & scale" approach that maps the simulated two-size, multi-species dust distribution onto continuous grain size distributions without introducing free parameters. Results. We find that, for the first time, a large-volume cosmological simulation directly reproduces the local Universe CSED without calibrating the postprocessing routine a priori. Residual tensions in the mid-infrared (~0.2 dex) point towards insufficient heating of the hottest dust components and uncertainties in the modelling of the PAH-emission carriers. This framework can be readily applied at low and high redshift to create synthetic spectra and images from the FUV to the FIR.

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Cosmological Galaxy Formation Modelling in the Era of the Square Kilometre Array

Over the past decade, galaxy formation simulations have advanced dramatically, transforming our ability to model the interstellar medium (ISM) and predict galaxies' radio emission. Yet the challenge of bridging physical scales--from sub-parsec star formation to gigaparsec cosmic structure--remains. The Square Kilometre Array (SKA) will map the cold gas and radio continuum of galaxies across cosmic time, demanding models that couple physical realism with cosmological reach. This chapter reviews the state-of-the-art in cosmological galaxy formation modelling in preparation for the SKA. We outline progress in simulating atomic hydrogen (HI), molecular gas, and radio continuum emission from both star formation and active galactic nuclei, highlighting how cosmological hydrodynamical simulations and semi-analytic models now jointly reproduce many observed gas properties. We emphasise the need for a coordinated, ``wedding-cake'' strategy that unites simulations of different scales, for forward modelling of observables to ensure fair comparison with data, and for the integration of new technologies such as AI-driven emulators to accelerate progress. Together, these efforts will enable theoretical models to both interpret and guide SKA science, turning simulations from passive interpreters into active engines for discovery.

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The importance of super-Eddington black hole accretion for the emergence of massive quiescent galaxies at high redshift

Recent JWST observations indicate that massive quiescent galaxies (stellar mass $M_{*}\gtrsim 10^{10}~\mathrm{M_\odot}$) at high redshift ($z\gtrsim 6$) are more abundant than predicted by most existing galaxy formation simulations and semi-analytic models. Notably, the new COLIBRE simulations have succeeded in reconciling this tension, though the precise reason for their improved agreement with JWST data remains unclear. We demonstrate that the improved agreement is largely due to super-Eddington growth of supermassive black holes (BHs) at high redshift. We run a series of $(100~\mathrm{cMpc})^{3}$ simulations with the COLIBRE subgrid physics at m7 COLIBRE resolution (gas and dark matter particle masses $m_{\rm gas}\approx m_{\rm dm}\sim 10^7~\mathrm{M_\odot}$), varying the maximum allowed BH accretion rate in units of the Eddington rate. We show that only the fiducial COLIBRE model, which permits super-Eddington accretion, is consistent with the JWST constraints at $z \gtrsim 6$. Moreover, we find that in COLIBRE about $50$ per cent of BH mass growth at high redshift occurs in the super-Eddington regime, even though such events are extremely rare in time. Our work highlights the important role of super-Eddington accretion in simulations of galaxy formation for reproducing the observed early emergence of quenching of massive galaxies.

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Galaxy luminosity functions from far-UV to submillimetre at $z=0$ in the COLIBRE simulations

We present predictions from the recent COLIBRE cosmological hydrodynamical simulations of galaxy formation for the present-day galaxy luminosity functions (LFs) at wavelengths ranging from the far-ultraviolet (FUV) to the submillimetre. The simulations are post-processed with the radiative transfer code SKIRT, accounting for dust attenuation and emission using the distribution and properties of dust grains predicted directly by COLIBRE. Results from simulations varying in mass resolution by a factor of $\sim 10^2$ ($\sim 10^5 - 10^7\,\mathrm{M_{\odot}}$) show very good convergence over most luminosity ranges. The COLIBRE-SKIRT LFs match the data remarkably well from the FUV to the near-infrared ($3.4\,\mathrm{μm}$) and also in the far-infrared and submillimetre wavelength range ($70-850\,\mathrm{μm}$). In the mid-infrared (MIR; $8-24\,\mathrm{μm}$), COLIBRE-SKIRT matches the data well at low luminosities but significantly underpredicts the luminosities of MIR-bright galaxies, with the discrepancy increasing towards longer wavelengths. The total infrared LF, obtained by integrating the spectral energy distributions over $8-1000\,\mathrm{μm}$, also matches observations well at the faint end but underpredicts the number of very bright galaxies. The unprecedented agreement at all other wavelengths indicates that COLIBRE, coupled with this calibration-free SKIRT post-processing framework, successfully predicts the properties of stellar populations at the present day and the amount and distribution of interstellar dust.

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Modeling the Spectral Energy Distribution of Active Galactic Nuclei: Implications for Cosmological Simulations of Galaxy Formation

Modeling the spectral energy distribution (SED) of active galactic nuclei (AGN) plays a very important role in constraining modern cosmological simulations of galaxy formation. Here, we utilize an advanced supermassive black hole (SMBH) accretion disk model to compute the accretion flow structure and AGN SED across a wide range of black hole mass ($M_{\rm SMBH}$) and dimensionless accretion rates $\dot{m}(\equiv \dot{M}_{\rm acc}/\dot{M}_\mathrm{Edd})$, where $\dot{M}_{\rm acc}$ is the mass flow rate through the disk and $\dot{M}_\mathrm{Edd}$ is the Eddington mass accretion rate. We find that the radiative efficiency is mainly influenced by $\dot m$, while contributions of $M_{\rm SMBH}$ and $\dot{m}$ to the bolometric luminosity are comparably important. We have developed new scaling relationships that relate the bolometric luminosity of an AGN to its luminosities in the hard X-ray, soft X-ray, and optical bands. Our results align with existing literature at high luminosities but suggest lower luminosities in the hard and soft X-ray bands for AGNs with low bolometric luminosities than commonly reported values. Combining with the semi-analytical model of galaxy formation \textsc{L-Galaxies} and Millennium dark matter simulation for the distribution of ($M_{\rm SMBH}, \dot{m}$) at different redshift, we find the model predictions align well with observational data at redshifts below 1 but deviates for higher redshifts regarding AGN detection fraction and luminosity functions. This deviation may arise from improper treatment of SMBH growth at high redshifts in the model or bias from limited observational data. This AGN SED calculation can be readily applied in other cosmological simulations.

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Simulating AGN wind feedback with variable feedback efficiencies in idealised disc galaxies

Active Galactic Nucleus (AGN) feedback plays a critical role in galaxy formation and evolution. AGN-driven winds can significantly influence their host galaxies, although the details of their impact remain unclear. In this study, we investigate the feedback effects of AGN winds on idealized disc galaxies using the SWIFT hydrodynamical code with COLIBRE subgrid physics. We implement a new thermal AGN feedback model in which the energy injection coupling efficiency has a power-law dependence on the Eddington ratio of the black hole (BH) accretion rate, motivated by scaling relations for AGN winds from numerical models and observations. We simulate idealised Milky Way-mass galaxies, incorporating a BH, cold gas disc, stellar disc, and hot circumgalactic medium, within a static dark matter halo. We vary the BH mass and the slope and normalisation of the new coupling efficiency model. For a fixed BH mass, we find that while systematic trends with coupling efficiency exist, most galaxy and BH properties show only modest variations. This likely reflects BH self-regulation in the COLIBRE model, which modulates the effects of changes in the feedback efficiency, provided the BH mass is sufficiently high. Key exceptions are the BH accretion rate and mass growth history, and outflow behaviour, where lower coupling efficiencies lead to faster BH growth and weaker outflows, potentially helping to explain the presence of overmassive BHs at high redshifts. Varying the BH mass, however, has a much larger impact, confirming that BH mass remains the primary factor shaping galaxy and BH evolution in our simulations.

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COLIBRE: calibrating subgrid feedback in cosmological simulations that include a cold gas phase

We present the calibration of stellar and active galactic nucleus (AGN) feedback in the subgrid model for the new COLIBRE hydrodynamical simulations of galaxy formation. COLIBRE directly simulates the multi-phase interstellar medium and the evolution of dust grains, which is coupled to the chemistry. COLIBRE is calibrated at three resolutions: particle masses of $m_{\rm gas} \approx m_{\rm dm} \sim 10^7$ (m7), $10^6$ (m6), and $10^5~\mathrm{M_\odot}$ (m5). To calibrate the COLIBRE feedback at m7 resolution, we run Latin hypercubes of $\approx 200$ simulations that vary up to four subgrid parameters in cosmological volumes of ($50~\mathrm{cMpc}$)$^{3}$. We train Gaussian process emulators on these simulations to predict the $z=0$ galaxy stellar mass function (GSMF) and size - stellar mass relation (SSMR) as functions of the model parameters, which we then fit to observations. The trained emulators not only provide the best-fitting parameter values but also enable us to investigate how different aspects of the prescriptions for supernova and AGN feedback affect the predictions. In particular, we demonstrate that while the observed $z=0$ GSMF and SSMR can be matched individually with a relatively simple supernova feedback model, simultaneously reproducing both necessitates a more sophisticated prescription. We show that the calibrated m7 COLIBRE model not only reproduces the calibration target observables, but also matches various other galaxy properties to which the model was not calibrated. Finally, we apply the calibrated m7 model to the m6 and m5 resolutions and, after slight manual adjustments of the subgrid parameters, achieve a similar level of agreement with the observed $z=0$ GSMF and SSMR.

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The COLIBRE project: cosmological hydrodynamical simulations of galaxy formation and evolution

We present the COLIBRE galaxy formation model and the COLIBRE suite of cosmological hydrodynamical simulations. COLIBRE includes new models for radiative cooling, dust grains, star formation, stellar mass loss, turbulent diffusion, pre-supernova stellar feedback, supernova feedback, supermassive black holes and active galactic nucleus (AGN) feedback. The multiphase interstellar medium is explicitly modelled without a pressure floor. Hydrogen and helium are tracked in non-equilibrium, with their contributions to the free electron density included in metal-line cooling calculations. The chemical network is coupled to a dust model that tracks three grain species and two grain sizes. In addition to the fiducial thermally-driven AGN feedback, a subset of simulations uses black hole spin-dependent hybrid jet/thermal AGN feedback. To suppress spurious transfer of energy from dark matter to stars, dark matter is supersampled by a factor 4, yielding similar dark matter and baryonic particle masses. The subgrid feedback model is calibrated to match the observed $z \approx 0$ galaxy stellar mass function, galaxy sizes, and black hole masses in massive galaxies. The COLIBRE suite includes three resolutions, with particle masses of $\sim 10^5$, $10^6$, and $10^7\,\text{M}_\odot$ in cubic volumes of up to 100, 200, and 400 cMpc on a side, respectively. The largest runs use 136 billion ($5 \times 3008^3$) particles. We describe the model, assess its strengths and limitations, and present both visual impressions and quantitative results. Comparisons with various low-redshift galaxy observations generally show very good numerical convergence and excellent agreement with the data.

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A hybrid active galactic nucleus feedback model with spinning black holes, winds and jets

We present a hybrid active galactic nucleus (AGN) feedback model that features three accretion disc states (the thick, thin, and slim discs at low, moderate, and super-Eddington accretion rates, respectively), and two feedback modes: thermal isotropic and kinetic jets. The model includes black hole (BH) spin evolution due to gas accretion, BH mergers, jet spindown, and Lense-Thirring torques. The BH spin determines the jet directions and affects the feedback efficiencies. The model is implemented in the SWIFT code and coupled with the COLIBRE galaxy formation model. We present the first results from hybrid AGN feedback simulations run as part of the COLIBRE suite, focusing on the impact of new parameters and calibration efforts. Using the new hybrid AGN feedback model, we find that AGN feedback affects not just massive galaxies, but all galaxies down to $M_*\approx10^8$ $\mathrm{M}_\odot$. BH spins are predicted to be near-maximal for intermediate-mass BHs ($M_\mathrm{BH}\in[10^6,10^8]$ $\mathrm{M}_\odot$), and lower for other BH masses. These trends are in good agreement with observations. The intergalactic medium is hotter and impacted on larger scales in the hybrid AGN feedback simulations compared to those using purely thermal feedback. In the hybrid AGN simulations, we predict that half of the cumulative injected AGN energy is in thermal and the other half in jet form, broadly independent of BH mass and redshift. Jet feedback is important at all redshifts and dominates over thermal feedback at $z<0.5$ and $z>1.5$, but only mildly.

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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.

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A random walk model for the evolution of the halo spin vector

We follow the spin vector evolutions of well resolved dark matter haloes (containing more than 300 particles) in merger tree main branches from the Millennium and Millennium-II N-body simulations, from z about 3.3 to z = 0. We find that there seems to be a characteristic plane for the spin vector evolution along each main branch. In the direction perpendicular to it, spin vectors oscillate around the plane, while within the plane, spin vectors show a coherent direction change as well as a diffusion in direction (possibly corresponds to a Gaussian white noise). This plane may reflect the geometry of surrounding large-scale structures. We also construct a simple stochastic model in which halo spin vector evolution is assumed to be driven by accretion of halo mass and angular momentum. This model can reproduce major features of the results from N-body simulations.

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On the accuracy of dark matter halo merger trees and the consequences for semi-analytic models of galaxy formation

Galaxy formation and evolution models, such as semi-analytic models, are powerful theoretical tools for predicting how galaxies evolve across cosmic time. These models follow the evolution of galaxies based on the halo assembly histories inferred from large $N$-body cosmological simulations. This process requires codes to identify halos ("halo finder") and to track their time evolution ("tree builder"). While these codes generally perform well, they encounter numerical issues when handling dense environments. In this paper, we present how relevant these issues are in state-of-the-art cosmological simulations. We characterize two major numerical artefacts in halo assembly histories: (i) the non-physical swapping of large amounts of mass between subhalos, and (ii) the sudden formation of already massive subhalos at late cosmic times. We quantify these artefacts for different combinations of halo finder (SUBFIND, VELOCIRAPTOR, HBT-HERONS) and tree builder codes (D-TRESS+DHALO, TREEFROG, HBT-HERONS), finding that in general more than $50\%$ ($80\%$) of the more massive subhalos with $>10^{3}$ ($>10^{4}$) particles at $z=0$ inherit them in most cases. However, HBT-HERONS, which explicitly incorporates temporal information, effectively reduces the occurrence of these artefacts to $5\%$ ($10\%$). We then use the semi-analytic models SHARK and GALFORM to explore how these artefacts impact galaxy formation predictions. We demonstrate that the issues above lead to non-physical predictions in galaxies hosted by affected halos, particularly in SHARK where the modelling of baryons relies on subhalo information. Finally, we propose and implement fixes for the numerical artefacts at the semi-analytic model level, and use SHARK to show the improvements, especially at the high-mass end, after applying them.

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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.

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A comparison of pre-existing $Λ$CDM predictions with the abundance of {\it JWST} galaxies at high redshift

Observations with the {\it James Webb Space Telescope} have revealed a high abundance of bright galaxies at redshift, $z\gtrsim 12$, which has been widely interpreted as conflicting with the $Λ$CDM model. In Cowley et al. (2018) predictions were made -- prior to the {\it JWST} observations -- for the expected abundance of these galaxies using the Durham semi-analytic galaxy formation model, {\sc galform}, which is known to produce a realistic population of galaxies at lower redshifts including the present day. Key to this model is the assumption of a ``top-heavy" initial mass function of stars formed in bursts (required to explain the number counts and redshift distribution of sub-millimetre galaxies). Here, we compare the rest-frame ultraviolet luminosity functions derived from {\it JWST} observations with those predicted by the Cowley et al. model up to $z=14$ and make further predictions for $z=16$. We find that below $z\sim 10$, the Cowley et al. predictions agree very well with observations, while agreement at $z\gtrsim12$ requires extending the model to take into account the timescale for the growth of obscuring dust grains at these very early times and its dependence on gas metallicity. We trace the evolution of these galaxies from $z=14$ to $z=0$ and find that their descendants typically reside in halos with a median mass $2.5\times 10^{13}\,h^{-1}\,\mathrm{M_{\odot}}$. The stellar masses of the descendants range from $3.2\times 10^{6}\,h^{-1}\,\mathrm{M_{\odot}}$ to $3.2\times 10^{11}\,h^{-1}\,\mathrm{M_{\odot}}$. Although these galaxies were all central galaxies at $z=14$, over half of their descendants end up as satellites in massive halos.

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Winds versus jets: a comparison between black hole feedback modes in simulations of idealized galaxy groups and clusters

Using the SWIFT simulation code we study different forms of active galactic nuclei (AGN) feedback in idealized galaxy groups and clusters. We first present a physically motivated model of black hole (BH) spin evolution and a numerical implementation of thermal isotropic feedback (representing the effects of energy-driven winds) and collimated kinetic jets that they launch at different accretion rates. We find that kinetic jet feedback is more efficient at quenching star formation in the brightest cluster galaxies (BCGs) than thermal isotropic feedback, while simultaneously yielding cooler cores in the intracluster medium (ICM). A hybrid model with both types of AGN feedback yields moderate star formation rates, while having the coolest cores. We then consider a simplified implementation of AGN feedback by fixing the feedback efficiencies and the jet direction, finding that the same general conclusions hold. We vary the feedback energetics (the kick velocity and the heating temperature), the fixed efficiencies and the type of energy (kinetic versus thermal) in both the isotropic and the jet case. The isotropic case is largely insensitive to these variations. In particular, we highlight that kinetic isotropic feedback (used e.g. in IllustrisTNG) is similar in its effects to its thermal counterpart (used e.g. in EAGLE). On the other hand, jet feedback must be kinetic in order to be efficient at quenching. We also find that it is much more sensitive to the choice of energy per feedback event (the jet velocity), as well as the efficiency. The former indicates that jet velocities need to be carefully chosen in cosmological simulations, while the latter motivates the use of BH spin evolution models.

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FLAMINGO: Calibrating large cosmological hydrodynamical simulations with machine learning

To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller-volume simulations, we model how the galaxy stellar mass function and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the stellar mass function. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters.

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