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We present new results from the ASTRID simulation from $z=3$ to $z=0.5$, covering the epoch of cosmic noon. The galaxy stellar mass function, as well as the black hole mass and luminosity functions in ASTRID, exhibit good agreement with recent observational constraints. We study the $M_{\rm BH}$-$M_*$ scaling relation and its connections to AGN luminosity, galaxy color, and star formation rate, demonstrating that AGN feedback plays a crucial role in the quenching of massive galaxies ($M_*>10^{10.5} M_{\odot}$). Although AGN feedback suppresses star formation through quenching, AGN-host galaxies still exhibit statistically higher levels of star formation compared to inactive ones, due to the positive correlation between AGN activity and star formation, both fueled by a shared gas reservoir. The fraction of quiescent galaxies in ASTRID increases with both galaxy mass and redshift evolution, aligning well with observational trends. We find that different quenching mechanisms can leave distinct morphological imprints on quenched galaxies. Massive, compact quiescent galaxies typically experience shorter quenching timescales, have younger central regions, and host overmassive black holes. This is usually due to a compaction-like quenching mechanism that funnels gas into the galaxy center, leading to starbursts and triggering AGN kinetic feedback. In contrast, quiescent galaxies with more diffuse morphologies generally experience `inside-out' quenching, which is characterized by older central regions compared to the outskirts. These galaxies typically experience longer quenching timescales due to quenching processes operating on a larger halo scale, which gradually deplete the galactic star-forming gas. Data of the \astrid simulation down to $z=0.5$ is available at \url{https://astrid.psc.edu}., Comment: Summited to APJ, comments are welcome

Super-resolution (SR) models in cosmological simulations use deep learning (DL) to rapidly supplement low-resolution (LR) runs with statistically correct, fine details. The SR technique preserves large-scale structures by conditioning on a low-resolution (LR) version of the simulation. On smaller scales, the generative deep learning (DL) process is stochastic, resulting in numerous possible SR realizations, each with unique small-scale structures. Validation of SR then relies on making sure that a specific statistic of interest is accurately reproduced by comparing SR and high resolution (HR) runs. In this study, we develop an emulator designed to reproduce the individual small-scale structures of an HR simulation as closely as possible. We process an SR realization alongside a specific High-Resolution Initial Condition (HRIC), transforming the SR output to emulate the results of a full simulation with that HRIC. By comparing visualizations, individual halo measures and cross-correlating Fourier modes we show that the emulated SR runs closely align with the corresponding HR simulation, even on length scales an order of magnitude smaller than the LR run. Additionally, small halos are trained to match the HR simulation, and the subhalo mass function is more accurately reproduced. These results show the promise of this method for generating numerous fast and accurate simulations and mock observations for large galaxy surveys., Comment: 16 pages, 15 figures

Recent JWST observations have uncovered an unexpectedly large population of massive quiescent galaxies at $z>3$. Using the cosmological simulations IllustrisTNG and ASTRID, we identify analogous galaxies and investigate their abundance, formation, quenching mechanisms, and post-quenching evolution for stellar masses $9.5 < \log_{10}{(M_\star/{\rm M}_\odot)} < 12$. We apply three different quenching definitions and find that both simulations significantly underestimate the comoving number density of quenched massive galaxies at $z \gtrsim 3$ compared to JWST observations by up to $\sim 2$ dex. This fact highlights the necessity for improved physical models of AGN feedback in galaxy formation simulations. In both simulations, the high-$z$ quenched massive galaxies often host overmassive central black holes above the standard $M_{BH}-M_\star$ relation, implying that the AGN feedback plays a crucial role in quenching galaxies in the early Universe. The typical quenching timescales for these galaxies are $\sim 200-600$ Myr. IllustrisTNG primarily employs AGN kinetic feedback, while ASTRID relies on AGN thermal feedback, which is less effective and has a longer quenching timescale. We also study the post-quenching evolution of the high-$z$ massive quiescent galaxies and find that many experience subsequent reactivation of star formation, evolving into primary progenitors of $z=0$ brightest cluster galaxies., Comment: Submitted to The Astrophysical Journal. 13 pages, 12 figures

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between dark matter density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in the galaxy formation models, that remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct dark matter fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and sub-grid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying dark matter fields from the given stellar mass fields, while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes approximately 500 times larger than those it was trained on, and across different galaxy formation models. Code for reproducing these results can be found at https://github.com/victoriaono/variational-diffusion-cdm

We present mock JWST observations for more than 250,000 different galaxies from the Astrid simulation with $3 \leq z \leq 6$. The mock observations are made using the BPASS stellar SED model, and a simple dust model. They are then viewed through NIRCam filters, convolved with a PSF, have noise added, and are drizzled together to emulate the Cosmic Evolution Early Release Science (CEERS) survey. We analyse this dataset by computing a number of morphological measures and find our catalog to have comparable statistics to similar mock catalogs, and the first release of CEERS data. We find that most of the Sersic indices of galaxies in our redshift range are lower than observed, with most having n less than one. Additionally, we observe the sizes of galaxies of all masses to increase from redshift z=6 to redshift z=3 consistent with other results. The number of galaxies in our catalog allows us to examine how relationships like the mass-size relation evolve with redshift, and compare the accuracy of a variety of traditional galaxy classification techniques (Sersic fit, Asymmetry-Concentration, and Gini-$M_{20}$) within our redshift range. We find the mass-size relation to be nearly flat at redshift z=6, and consistently increases as redshift decreases, and find the galaxy classification methods have minimal correlation with each other in our redshift range. We also investigate the impact that different stages of our imaging pipeline have on these morphological measures to determine how robust mock catalogs are to different choices at each step. Finally, we test the addition of incorporating light from AGNs into our pipeline and find that while the population of galaxies that have significant AGN luminosity is low, those galaxies do tend to have higher Sersic indices once the AGN luminosity is added, rectifying some of the systematic bias towards lower Sersic indices present in our dataset., Comment: 17 pages, 14 figures

The hosts of two low-luminosity high-z quasars, J2255+0251 and J2236+0032, were recently detected using JWST's NIRCam instrument. These represent the first high-z quasar host galaxy stellar detections and open a new window into studying high-z quasars. We examine the implications of the measured properties of J2255+0251 and J2236+0032 within the context of the hydrodynamic simulation BlueTides at z = 6.5. We find that these observed quasars fall on the BlueTides stellar to black hole mass relation and have similar luminosities to the brightest simulated quasars. We predict their star formation rates, estimating approximately $10^{2-3}$ $M_{\odot}/ \rm yr$ for both quasar hosts. J2255+0251 and J2236+0032's host galaxy radii also fall within estimates of the radii of the simulated host galaxies of similar luminosity quasars. We generate mock JWST NIRCam images of analogs to the observed quasars within BlueTides and perform a point source removal to illustrate both a qualitative and quantitative comparison of the measured and simulated radii and magnitudes. The quasar subtraction works well for similar luminosity quasars, and the recovered host images are consistent with what was observed for J2255+0251 and J2236+0032, further supporting the success of those observations. We also use our mock imaging pipeline to make predictions for the detection of J2255+0251 and J2236+0032's hosts in upcoming JWST observations. We anticipate that the simulation analogs of future high-z quasar host discoveries will allow us to make accurate predictions of their properties beyond the capabilities of JWST., Comment: Accepted to MNRAS. 15 pages, 11 figures

We study dual AGN host galaxy morphologies at $z=2$ using the ASTRID simulation, selecting black hole (BH) pairs with small separation ($\Delta r<30\rm{kpc}$), high mass ($M_{\text{BH,12}}>10^7M_\odot$), and luminosity ($L_{\text{bol,12}}>10^{43}\rm{erg/s}$). We kinematically decompose (using MORDOR) $\sim1000$ dual AGN hosts into standard components - a `disk' (thin and thick disk, pseudo-bulge) and 'bulge' (bulge and halo) and define disk-dominated galaxies by the disk-to-total $D/T\geq0.5$. In ASTRID, $60.9\pm2.1\%$ of dual AGN hosts (independent of separation) are disk-dominated, with the $D/T$ distribution peaking at $\sim0.7$. Notably, hosts of BH pairs have similar morphologies (most either both disk or bulge-dominated). In dual-AGN hosts, the $D/T$ increases from $\sim17\% $ at $M_{\rm *}\sim 10^{9} M_{\odot}$ to $ 64\% $ for $M_{\rm *} \sim 10^{11.5} M_{\odot}$, and the pseudo-bulge is the dominant component of the disk fraction at the high mass end. Moreover, dual AGN hosts exhibit a higher fraction of disk/large pseudo-bulge than single-AGN hosts. The Disk-to-Total ratio is approximately constant with BH mass or AGN luminosity. We also create mock images of dual AGN host galaxies, employing morphological fitting software Statmorph to calculate morphological parameters and compare them with our kinematic decomposition results. Around $83.3\pm2.4\%$ of galaxies display disk-like profiles, of which $\sim60.7\pm2.2\%$ are kinematically confirmed as disks. Se\'rsic indices and half-mass radii of dual AGN host galaxies align with observational measurements from HST at $z\sim2$. Around $34\%$ are identified as mergers from the $\text{Gini}-M_{20}$ relation. We find two dual AGN hosted by galaxies that exhibit disk-like se\'rsic index $n_{12}<1$ and $(D/T)_{12}>0.5$, which are in remarkable agreement with properties of recently discovered dual quasars in disk galaxies at $z\sim 2$., Comment: 15 pages, 12 figures, submitted to the Open Journal of Astrophysics

The elusive massive black hole (MBH) seeds stand to be revealed by the Laser Space Antenna Interferometer through mergers. As an aftermath of galaxy mergers, MBH coalescence is a vastly multi-scale process connected to galaxy formation. We introduce the "Massive black hole Assembly in Galaxies Informed by Cosmological Simulations" (MAGICS) suite, with galaxy/MBH properties and orbits recovered from large-volume cosmological simulation ASTRID. The simulations include subgrid star formation, supernovae feedback, and MBH accretion/feedback. In this first suite, we extract fifteen representative galaxy mergers with seed MBHs to examine their dynamics at an improved mass and spatial resolution (by $\sim2000$ and $\sim20$) and follow MBH orbits down to $\sim10\,\text{pc}$. We find that the seed MBH energy loss and orbital decay are largely governed by global torques induced by the galaxy merger process on scales resolvable by cosmological simulations. Specifically, pairs sink quickly if their orbits shrink rapidly below $1\,\text{kpc}$ during the first $\sim200\,\text{Myr}$ of pairing due to effective energy loss in major galaxy mergers, whereas MBHs gaining energy in minor galaxy mergers with head-on collisions are likely to stall. High initial eccentricities ($e_\text{init}>0.5$) and high stellar densities at kpc scales ($\rho_\text{star}>0.05\,M_\odot/\text{pc}^3$) also lead to most efficient decays. $\sim50\%$ high-redshift seed MBH pairs experience consecutive galaxy mergers and are more likely to stall at $\sim1\,\text{kpc}$. For a subset of systems, we carry out N-Body re-simulations until binary formation and find that some stalled systems merge at high-z when embedded in sufficient nuclear star clusters., Comment: 21 pages, 20 Figures. Submitted to The Open Journal of Astrophysics. Comments welcome!

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter components that cannot be directly observed. The relationship between dark matter density fields and galaxy distributions can be sensitive to assumptions in cosmology and astrophysical processes embedded in the galaxy formation models, that remain uncertain in many aspects. Based on state-of-the-art galaxy formation simulation suites with varied cosmological parameters and sub-grid astrophysics, we develop a diffusion generative model to predict the unbiased posterior distribution of the underlying dark matter fields from the given stellar mass fields, while being able to marginalize over the uncertainties in cosmology and galaxy formation.

This white paper explores the detectability of intermediate-mass black holes (IMBHs) wandering in the Milky Way (MW) and massive local galaxies, with a particular emphasis on the role of AXIS. IMBHs, ranging within $10^{3-6} \, M_\odot$, are commonly found at the centers of dwarf galaxies and may exist, yet undiscovered, in the MW. By using model spectra for advection-dominated accretion flows (ADAFs), we calculated the expected fluxes emitted by a population of wandering IMBHs with a mass of $10^5 \, M_\odot$ in various MW environments and extrapolated our results to massive local galaxies. Around $40\%$ of the potential population of wandering IMBHs in the MW can be detected in an AXIS deep field. We proposed criteria to aid in selecting IMBH candidates using already available optical surveys. We also showed that IMBHs wandering in $>200$ galaxies within $10$ Mpc can be easily detected with AXIS when passing within dense galactic environments (e.g., molecular clouds and cold neutral medium). In summary, we highlighted the potential X-ray detectability of wandering IMBHs in local galaxies and provided insights for guiding future surveys. Detecting wandering IMBHs is crucial for understanding their demographics, evolution, and the merging history of galaxies., Comment: This White Paper is part of a series commissioned for the AXIS Probe Concept Mission; additional AXIS White Papers can be found at the AXIS website: http://axis.astro.umd.edu/ with a mission overview here: arXiv:2311.00780. Review article, 7 pages, 3 figures

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. (2023) developed models that could accurately infer the value of $\Omega_{\rm m}$ from catalogs that only contain the positions and radial velocities of galaxies that are robust to uncertainties in astrophysics and subgrid models. However, observations are affected by many effects, including 1) masking, 2) uncertainties in peculiar velocities and radial distances, and 3) different galaxy selections. Moreover, observations only allow us to measure redshift, intertwining galaxies' radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that, although the presence of these effects degrades the precision and accuracy of the models, and increases the fraction of catalogs where the model breaks down, the fraction of galaxy catalogs where the model performs well is over 90 %, demonstrating the potential of these models to constrain cosmological parameters even when applied to real data., Comment: 39 pages, 25 figures. For the reference in the abstract (de Santi et al. 2023) see arXiv:2302.14101

Recent works have discovered a relatively tight correlation between $\Omega_{\rm m}$ and properties of individual simulated galaxies. Because of this, it has been shown that constraints on $\Omega_{\rm m}$ can be placed using the properties of individual galaxies while accounting for uncertainties on astrophysical processes such as feedback from supernova and active galactic nuclei. In this work, we quantify whether using the properties of multiple galaxies simultaneously can tighten those constraints. For this, we train neural networks to perform likelihood-free inference on the value of two cosmological parameters ($\Omega_{\rm m}$ and $\sigma_8$) and four astrophysical parameters using the properties of several galaxies from thousands of hydrodynamic simulations of the CAMELS project. We find that using properties of more than one galaxy increases the precision of the $\Omega_{\rm m}$ inference. Furthermore, using multiple galaxies enables the inference of other parameters that were poorly constrained with one single galaxy. We show that the same subset of galaxy properties are responsible for the constraints on $\Omega_{\rm m}$ from one and multiple galaxies. Finally, we quantify the robustness of the model and find that without identifying the model range of validity, the model does not perform well when tested on galaxies from other galaxy formation models., Comment: 13 pages, 7 figures

We study quasar proximity zones in a simulation that includes a self-consistent quasar formation model and realistic IGM environments. The quasar host halo is $10^{13}\ M_{\mathrm{\odot}}$ at $z=6$, more massive than typical halos studied in previous work. Between $6

A recent study found dynamical evidence of a supermassive black hole of $\sim 3 \times 10^{6} \, \rm M_\odot$ at the center of Leo I, the most distant dwarf spheroidal galaxy of the Milky Way. This black hole, comparable in mass to the Milky Way's Sgr A*, places the system $>2$ orders of magnitude above the standard $M_\bullet-M_{\star}$ relation. We investigate the possibility, from a dynamical standpoint, that Leo I's stellar system was originally much more massive and, thus, closer to the relation. Extreme tidal disruption from one or two close passages within the Milky Way's virial radius could have removed most of its stellar mass. A simple analytical model suggests that the progenitor of Leo I could have experienced a mass loss in the range of $32\% - 57\%$ from a single pericenter passage, depending on the stellar velocity dispersion estimate. This mass loss percentage increases to the range $66\% - 78\%$ if the pericenter occurs at the minimum distance allowed by current orbital reconstructions. Detailed N-body simulations show that the mass loss could reach $\sim 90\%$ with up to two passages, again with pericenter distances compatible with the minimum value allowed by Gaia data. Despite very significant uncertainties in the properties of Leo I, we reproduce its current position and velocity dispersion, as well as the final stellar mass enclosed in $1$ kpc ($\sim 5\times 10^6 \, \rm M_\odot$) within a factor $< 2$. The most recent tidal stream is directed along our line of sight toward Leo I, making it difficult to detect. Evidence from this extreme tidal disruption event could be present in current Gaia data in the form of extended tidal streams., Comment: Accepted for publication in The Astrophysical Journal Letters. 9 pages, 4 figures. A video of the N-body simulation can be viewed here: https://www.fabiopacucci.com/resources/simulations/

We quantify the cosmological spread of baryons relative to their initial neighboring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighboring distribution owing to chaotic gravitational dynamics on spatial scales comparable to their host dark matter halo. In contrast, gas in hydrodynamic simulations spreads much further from the initial neighboring dark matter owing to feedback from supernovae (SNe) and Active Galactic Nuclei (AGN). We show that large-scale baryon spread is very sensitive to model implementation details, with the fiducial \textsc{SIMBA} model spreading $\sim$40\% of baryons $>$1\,Mpc away compared to $\sim$10\% for the IllustrisTNG and \textsc{ASTRID} models. Increasing the efficiency of AGN-driven outflows greatly increases baryon spread while increasing the strength of SNe-driven winds can decrease spreading due to non-linear coupling of stellar and AGN feedback. We compare total matter power spectra between hydrodynamic and paired $N$-body simulations and demonstrate that the baryonic spread metric broadly captures the global impact of feedback on matter clustering over variations of cosmological and astrophysical parameters, initial conditions, and galaxy formation models. Using symbolic regression, we find a function that reproduces the suppression of power by feedback as a function of wave number ($k$) and baryonic spread up to $k \sim 10\,h$\,Mpc$^{-1}$ while highlighting the challenge of developing models robust to variations in galaxy formation physics implementation., Comment: 17 pages, 15 figures

We look for simulated star-forming linear wakes such as the one recently discovered by van Dokkum et al. (2023) in the cosmological hydrodynamical simulation ASTRID. Amongst the runaway black holes in ASTRID, none are able to produce clear star-forming wakes. Meanwhile, fly-by encounters, typically involving a compact galaxy (with a central black hole) and a star-forming galaxy (with a duo of black holes) reproduce remarkably well many of the key properties (its length and linearity; recent star formation, etc.) of the observed star-forming linear feature. We predict the feature to persist for approximately 100 Myr in such a system and hence constitute a rare event. The feature contains a partly stripped galaxy (with $M_{\rm gal}=10^9 \sim 10^{10}M_\odot$) and a dual BH system ($M_{\rm BH}=10^5 \sim 10^7\,M_\odot$) in its brightest knot. X-ray emission from AGN in the knot should be detectable in such systems. After $100\sim 200\,{\rm Myrs}$ from the first fly-by, the galaxies merge leaving behind a triple black hole system in a (still) actively star-forming early-type remnant of mass $\sim 5\times 10^{10}\,M_\odot$. Follow-up JWST observations may be key for revealing the nature of these linear features by potentially detecting the older stellar populations constituting the bright knot. Confirmation of such detections may therefore help discriminate a fly-by encounter from a massive BH wake to reveal the origin of such features., Comment: 8 pages, 5 figures, comments welcome

Accuracy in the topology and statistics of a simulated Epoch of Reionization (EoR) are vital to draw connections between observations and physical processes. While full radiative transfer models produce the most accurate reionization models, they are highly computationally expensive, and are infeasible for the largest cosmological simulations. Instead, large simulations often include EoR models that are pre-computed via the initial density field, or post-processed where feedback effects are ignored. We introduce Astrid-ES, a resimulation of the Astrid epoch of reionisation $20 > z > 5.5$ which includes an on-the-fly excursion-set reionization algorithm. Astrid-ES produces more accurate reionization histories without significantly impacting the computational time. This model directly utilises the star particles produced in the simulation to calculate the EoR history and includes a UV background which heats the gas particles after their reionization. We contrast the reionization topology and statistics in Astrid-ES with the previously employed parametric reionisation model, finding that in Astrid-ES, ionised regions are more correlated with galaxies, and the 21cm power-spectrum shows an increase in large scale power. We calculate the relation between the size of HII regions and the UV luminosity of the brightest galaxy within them. Prior to the overlap phase, we find a power-law fit of $\mathrm{log} (R) = -0.314 M_\mathrm{UV} - 2.550 \mathrm{log}(1+z) + 7.408$ with a standard deviation $\sigma_R < 0.15 \mathrm{dex}$ across all mass bins. We also examine the properties of halos throughout reionization, finding that while the properties of halos in the simulation are correlated with the redshift of reionisation, they are not greatly affected by reionisation itself., Comment: 12 pages, 11 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Society

We present the PRIYA suite of cosmological simulations, based on the code and hydrodynamic model of the ASTRID simulation, and designed for cosmological analyses of the Lyman-$\alpha$ forest. Our simulation suite spans a $9$-dimensional parameter space, including $4$ cosmological parameters and $5$ astrophysical/thermal parameters. We have run $48$ low fidelity simulations with $1536^3$ particles in a $120$ Mpc/h box and $3$ high fidelity simulations with $3072^3$ particles in a $120$ Mpc/h box. All our simulations include a full physics model for galaxy formation, including supernova and AGN feedback, and thus also contain a realistic population of DLAs. We advance on earlier simulations suites by larger particle loads, by incorporating new physical models for patchy hydrogen and helium reionization, and by self-consistently incorporating a model for AGN feedback. We show that patchy helium reionization imprints an excess in the 1D flux power spectrum on large scales, which may allow future measurements of helium reionization bubble sizes. Simulation parameters are chosen based on a Latin hypercube design and a Gaussian process is used to interpolate to arbitrary parameter combinations. We build a multi-fidelity emulator for the 1D flux power spectrum and the mean IGM temperature. We show that our final interpolation error is $< 1\%$ and that our simulations produce a flux power spectrum converged at the percent level for $z=5.4$ - $2.2$. Our simulation suite will be used to interpret Lyman-$\alpha$ forest 1D flux power spectra from SDSS and future DESI data releases., Comment: 25 pages, 11 figures, matches version published in JCAP

In this work, we extend our recently developed super-resolution (SR) model for cosmological simulations to produce fully time consistent evolving representations of the particle phase-space distribution. We employ a style-based constrained generative adversarial network (Style-GAN) where the changing cosmic time is an input style parameter to the network. The matter power spectrum and halo mass function agree well with results from high-resolution N-body simulations over the full trained redshift range ($10 \le z \le 0$). Furthermore, we assess the temporal consistency of our SR model by constructing halo merger trees. We examine progenitors, descendants and mass growth along the tree branches. All statistical indicators demonstrate the ability of our SR model to generate satisfactory high-resolution simulations based on low-resolution inputs., Comment: 12 pages, 11 figures, code and movie available in https://github.com/sagasv5-xw/map2map on styled srsgan branch

Recent work has pointed out the potential existence of a tight relation between the cosmological parameter $\Omega_{\rm m}$, at fixed $\Omega_{\rm b}$, and the properties of individual galaxies in state-of-the-art cosmological hydrodynamic simulations. In this paper, we investigate whether such a relation also holds for galaxies from simulations run with a different code that made use of a distinct subgrid physics: Astrid. We find that also in this case, neural networks are able to infer the value of $\Omega_{\rm m}$ with a $\sim10\%$ precision from the properties of individual galaxies while accounting for astrophysics uncertainties as modeled in CAMELS. This tight relationship is present at all considered redshifts, $z\leq3$, and the stellar mass, the stellar metallicity, and the maximum circular velocity are among the most important galaxy properties behind the relation. In order to use this method with real galaxies, one needs to quantify its robustness: the accuracy of the model when tested on galaxies generated by codes different from the one used for training. We quantify the robustness of the models by testing them on galaxies from four different codes: IllustrisTNG, SIMBA, Astrid, and Magneticum. We show that the models perform well on a large fraction of the galaxies, but fail dramatically on a small fraction of them. Removing these outliers significantly improves the accuracy of the models across simulation codes., Comment: 16 pages, 12 figures

We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies. CAMELS-ASTRID employs the galaxy formation model following the ASTRID simulation and contains 2,124 hydrodynamic simulation runs that vary 3 cosmological parameters ($\Omega_m$, $\sigma_8$, $\Omega_b$) and 4 parameters controlling stellar and AGN feedback. Compared to the existing TNG and SIMBA simulation suites in CAMELS, the fiducial model of ASTRID features the mildest AGN feedback and predicts the least baryonic effect on the matter power spectrum. The training set of ASTRID covers a broader variation in the galaxy populations and the baryonic impact on the matter power spectrum compared to its TNG and SIMBA counterparts, which can make machine-learning models trained on the ASTRID suite exhibit better extrapolation performance when tested on other hydrodynamic simulation sets. We also introduce extension simulation sets in CAMELS that widely explore 28 parameters in the TNG and SIMBA models, demonstrating the enormity of the overall galaxy formation model parameter space and the complex non-linear interplay between cosmology and astrophysical processes. With the new simulation suites, we show that building robust machine-learning models favors training and testing on the largest possible diversity of galaxy formation models. We also demonstrate that it is possible to train accurate neural networks to infer cosmological parameters using the high-dimensional TNG-SB28 simulation set.

We forecast the prospects for cross-correlating future line intensity mapping (LIM) surveys with the current and future Ly-$\alpha$ forest data. We use large cosmological hydrodynamic simulations to model the expected emission signal for the CO rotational transition in the COMAP LIM experiment at the 5-year benchmark and the Ly-$\alpha$ forest absorption signal for various surveys, including eBOSS, DESI, and PFS. We show that CO$\times$Ly-$\alpha$ forest can significantly enhance the detection signal-to-noise ratio of CO, with a $200$ to $300 \%$ improvement when cross-correlated with the forest observed in the Prime Focus Spectrograph (PFS) survey and a $50$ to $75\%$ enhancement for the currently available eBOSS or the upcoming DESI observations. We compare to the signal-to-noise improvements expected for a galaxy survey and show that CO$\times$Ly-$\alpha$ is competitive with even a spectroscopic galaxy survey in raw signal-to-noise. Furthermore, our study suggests that the clustering of CO emission is tightly constrained by CO$\times$Ly-$\alpha$ forest, due to the increased signal-to-noise ratio and the simplicity of Ly-$\alpha$ absorption power spectrum modeling. Any foreground contamination or systematics are expected not to be shared between LIM surveys and Ly-$\alpha$ forest observations; this provides an unbiased inference. Our findings highlight the potential benefits of utilizing the Ly-$\alpha$ forest to aid in the initial detection of signals in line intensity experiments. For example, we also estimate that [CII]$\times$Ly-$\alpha$ forest measurements from EXCLAIM and DESI/eBOSS, respectively, should have a larger signal-to-noise ratio than planned [CII]$\times$quasar observations by about an order of magnitude. Our results can be readily applied to actual data thanks to the observed quasar spectra in eBOSS Stripe 82, which overlaps with several LIM surveys., Comment: Codes and the produced data are available at https://github.com/qezlou/lali

We use the ASTRID cosmological hydrodynamic simulation to investigate the properties and evolution of triple and quadruple Massive Black Hole (MBH) systems at $z = 2-3$. Only a handful of MBH tuple systems have been detected to date. In ASTRID, we find $4\%$ of the $M_{\rm BH}>10^7\,M_\odot$ are in tuples with $\Delta r_{\rm max} < 200\,{\rm kpc}$. The tuple systems span a range of separations with the majority of the observable AGN systems at $\Delta r \sim 50-100$ kpc. They include some of the most massive BHs (up to $10^{10} \,M_\odot$) but with at least one of the components of $M_{\rm BH} \sim 10^7 \,M_\odot$. Tuples' host galaxies are typically massive with $M_* \sim 10^{10-11} \,M_\odot$. We find that $>10\%$ massive halos with $M_{\rm halo} > 10^{13} M_\odot$ host MBH tuples. Following the subsequent interactions between MBHs in tuples, we found that in $\sim 5\%$ of the triplets all three MBHs merge within a Gyr, and $15\%$ go through one merger. As a by-product of the complex multi-galaxy interaction of these systems, we also find that up to $\sim 5\%$ of tuples lead to runaway MBHs. In ASTRID, virtually all of the ultramassive black holes ($>10^{10} \,M_\odot $) have undergone a triple quasar phase while for BHs with $M_{\rm BH} \sim 10^9 \,M_\odot$ this fraction drops to $50\%$., Comment: 10 pages, 9 figures; comments welcome

We discover analytic equations that can infer the value of $\Omega_{\rm m}$ from the positions and velocity moduli of halo and galaxy catalogues. The equations are derived by combining a tailored graph neural network (GNN) architecture with symbolic regression. We first train the GNN on dark matter halos from Gadget N-body simulations to perform field-level likelihood-free inference, and show that our model can infer $\Omega_{\rm m}$ with $\sim6\%$ accuracy from halo catalogues of thousands of N-body simulations run with six different codes: Abacus, CUBEP$^3$M, Gadget, Enzo, PKDGrav3, and Ramses. By applying symbolic regression to the different parts comprising the GNN, we derive equations that can predict $\Omega_{\rm m}$ from halo catalogues of simulations run with all of the above codes with accuracies similar to those of the GNN. We show that by tuning a single free parameter, our equations can also infer the value of $\Omega_{\rm m}$ from galaxy catalogues of thousands of state-of-the-art hydrodynamic simulations of the CAMELS project, each with a different astrophysics model, run with five distinct codes that employ different subgrid physics: IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE. Furthermore, the equations also perform well when tested on galaxy catalogues from simulations covering a vast region in parameter space that samples variations in 5 cosmological and 23 astrophysical parameters. We speculate that the equations may reflect the existence of a fundamental physics relation between the phase-space distribution of generic tracers and $\Omega_{\rm m}$, one that is not affected by galaxy formation physics down to scales as small as $10~h^{-1}{\rm kpc}$., Comment: 32 pages, 13 figures, summary video: https://youtu.be/STZHvDHkVgo

We train graph neural networks to perform field-level likelihood-free inference using galaxy catalogs from state-of-the-art hydrodynamic simulations of the CAMELS project. Our models are rotational, translational, and permutation invariant and do not impose any cut on scale. From galaxy catalogs that only contain $3$D positions and radial velocities of $\sim 1, 000$ galaxies in tiny $(25~h^{-1}{\rm Mpc})^3$ volumes our models can infer the value of $\Omega_{\rm m}$ with approximately $12$ % precision. More importantly, by testing the models on galaxy catalogs from thousands of hydrodynamic simulations, each having a different efficiency of supernova and AGN feedback, run with five different codes and subgrid models - IllustrisTNG, SIMBA, Astrid, Magneticum, SWIFT-EAGLE -, we find that our models are robust to changes in astrophysics, subgrid physics, and subhalo/galaxy finder. Furthermore, we test our models on $1,024$ simulations that cover a vast region in parameter space - variations in $5$ cosmological and $23$ astrophysical parameters - finding that the model extrapolates really well. Our results indicate that the key to building a robust model is the use of both galaxy positions and velocities, suggesting that the network have likely learned an underlying physical relation that does not depend on galaxy formation and is valid on scales larger than $\sim10~h^{-1}{\rm kpc}$., Comment: 34 pages, 12 figures. For a video summarizing the results, see https://youtu.be/b59ep7cyPOs

In the near future, projects like LISA and Pulsar Timing Arrays are expected to detect gravitational waves from mergers between supermassive black holes, and it is crucial to precisely model the underlying merger populations now to maximize what we can learn from this new data. Here we characterize expected high-redshift (z > 2) black hole mergers using the very large volume Astrid cosmological simulation, which uses a range of seed masses to probe down to low-mass BHs, and directly incorporates dynamical friction so as to accurately model the dynamical processes which bring black holes to the galaxy center where binary formation and coalescence will occur. The black hole populations in Astrid include black holes down to 10$^{4.5}$ M$_\odot$, and remain broadly consistent with the TNG simulations at scales > 10$^6$ M$_\odot$ (the seed mass used in TNG). By resolving lower-mass black holes, the overall merger rate is ~5x higher than in TNG. However, incorporating dynamical friction delays mergers compared to a recentering scheme, reducing the high-z merger rate mass-matched mergers by a factor of ~2x. We also calculate the expected LISA Signal-to-Noise values, and show that the distribution peaks at high SNR (>100), emphasizing the importance of implementing a seed mass well below LISA's peak sensitivity (10$^6$ M$_\odot$) to resolve the majority of LISA's GW detections., Comment: 11 pages, 10 figures, submitted to MNRAS

Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraints on cosmology. We investigate how the observable properties of group-scale halos can constrain feedback's impact on the matter distribution using Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). Extending the results of previous work to smaller halo masses and higher wavenumber, $k$, we find that the baryon fraction in halos contains significant information about the impact of feedback on the matter power spectrum. We explore how the thermal Sunyaev Zel'dovich (tSZ) signal from group-scale halos contains similar information. Using recent Dark Energy Survey (DES) weak lensing and Atacama Cosmology Telescope (ACT) tSZ cross-correlation measurements and models trained on CAMELS, we obtain $10\%$ constraints on feedback effects on the power spectrum at $k \sim 5\, h/{\rm Mpc}$. We show that with future surveys, it will be possible to constrain baryonic effects on the power spectrum to $\mathcal{O}(<1\%)$ at $k = 1\, h/{\rm Mpc}$ and $\mathcal{O}(3\%)$ at $k = 5\, h/{\rm Mpc}$ using the methods that we introduce here. Finally, we investigate the impact of feedback on the matter bispectrum, finding that tSZ observables are highly informative in this case., Comment: 18 pages, 15 figures. Comments are welcome

Intermediate-Mass Black Holes (IMBHs) of $10^3-10^6 \, M_\odot$ are commonly found at the center of dwarf galaxies. Simulations and observations convincingly show that a sizable population of IMBHs could wander off-center in galaxies. We use the cosmological simulation ASTRID to study the orbital and radiative properties of wandering IMBHs in massive galaxies at $z\sim3$. We find that this population of black holes has large orbital inclinations ($60^\circ\pm22^\circ$) with respect to the principal plane of the host. The eccentricity of their orbits is also significant ($0.6\pm0.2$) and decreases with time. Wandering IMBHs undergo spikes of accretion activity around the pericenter of their orbits, with rates $10^{-3}-10^{-5}$ times the Eddington rate and a median accretion duty cycle of $\sim 12\%$. Their typical spectral energy distribution peaks in the infrared at $\sim 11 \, \mu \rm m$ rest-frame. Assuming a standard value of $10\%$ for the matter-to-energy radiative efficiency, IMBHs reach $2-10$ keV X-ray luminosities $>10^{37} \, \mathrm{erg\,s^{-1}}$ for $\sim10\%$ of the time. This luminosity corresponds to fluxes $>10^{-15} \, \mathrm{erg \, s^{-1} \, cm^{-2}}$ within $10$ Mpc. They could be challenging to detect because of competing emissions from X-ray binaries and the interstellar medium. X-ray luminosities $> 10^{41} \, \mathrm{erg \, s^{-1}}$, in the hyper-luminous X-ray sources (HLXs) regime, are reached by $\sim 7\%$ of the IMBHs. These findings suggest that HLXs are a small subset of the wandering IMBH population, which is characterized by luminosities $10^3-10^4$ times fainter. Dedicated surveys are needed to assess the demographics of this missing population of black holes., Comment: Accepted for publication in MNRAS. This is the final version of the manuscript. 9 pages, 7 figures

Massive black holes in the centers of galaxies today must have grown by several orders of magnitude from seed black holes formed at early times. Detecting a population of intermediate mass black holes (IMBHs) can provide constraints on these elusive BH seeds. Here we use the large volume, cosmological hydrodynamical simulation Astrid, which includes IMBH seeds and dynamical friction to investigate the population of IMBH seeds. Dynamical friction is largely inefficient at sinking and merging seed IMBHs at high-z. This leads to an extensive population (several hundred per galaxy) of wandering IMBHs in large halos at z~2. A small fraction of these IMBHs are detectable as HLXs, Hyper Luminous X-ray sources. Importantly, at z ~ 2, IMBHs mergers produce the peak of GW events. We find close to a million GW events in Astrid between z=2-3 involving seed IMBH mergers. These GW events (almost all detectable by LISA) at cosmic noon should provide strong constraints on IMBH seed models and their formation mechanisms. At the center of massive galaxies, where the number of IMBHs can be as high as 10-100, SMBH-IMBH pairs can form. These Intermediate mass ratio inspirals (IMRIs) and extreme mass ratio inspirals (EMRIs), will require the next generation of milli-muHz space-based GW interferometers to be detected. Large populations of IMBHs around massive black holes will probe their environments and MBH causal structure.

AI super-resolution, combining deep learning and N-body simulations has been shown to successfully reproduce the large scale structure and halo abundances in the Lambda Cold Dark Matter cosmological model. Here, we extend its use to models with a different dark matter content, in this case Fuzzy Dark Matter (FDM), in the approximation that the difference is encoded in the initial power spectrum. We focus on redshift z = 2, with simulations that model smaller scales and lower masses, the latter by two orders of magnitude, than has been done in previous AI super-resolution work. We find that the super-resolution technique can reproduce the power spectrum and halo mass function to within a few percent of full high resolution calculations. We also find that halo artifacts, caused by spurious numerical fragmentation of filaments, are equally present in the super-resolution outputs. Although we have not trained the super-resolution algorithm using full quantum pressure FDM simulations, the fact that it performs well at the relevant length and mass scales means that it has promise as technique which could avoid the very high computational cost of the latter, in some contexts. We conclude that AI super-resolution can become a useful tool to extend the range of dark matter models covered in mock catalogs., Comment: 7 pages, 4 figures

We train graph neural networks on halo catalogues from Gadget N-body simulations to perform field-level likelihood-free inference of cosmological parameters. The catalogues contain $\lesssim$5,000 halos with masses $\gtrsim 10^{10}~h^{-1}M_\odot$ in a periodic volume of $(25~h^{-1}{\rm Mpc})^3$; every halo in the catalogue is characterized by several properties such as position, mass, velocity, concentration, and maximum circular velocity. Our models, built to be permutationally, translationally, and rotationally invariant, do not impose a minimum scale on which to extract information and are able to infer the values of $\Omega_{\rm m}$ and $\sigma_8$ with a mean relative error of $\sim6\%$, when using positions plus velocities and positions plus masses, respectively. More importantly, we find that our models are very robust: they can infer the value of $\Omega_{\rm m}$ and $\sigma_8$ when tested using halo catalogues from thousands of N-body simulations run with five different N-body codes: Abacus, CUBEP$^3$M, Enzo, PKDGrav3, and Ramses. Surprisingly, the model trained to infer $\Omega_{\rm m}$ also works when tested on thousands of state-of-the-art CAMELS hydrodynamic simulations run with four different codes and subgrid physics implementations. Using halo properties such as concentration and maximum circular velocity allow our models to extract more information, at the expense of breaking the robustness of the models. This may happen because the different N-body codes are not converged on the relevant scales corresponding to these parameters., Comment: 25 pages, 11 figures, summary video: https://youtu.be/qkw92Z6owJU

The origin of rare and elusive ultramassive black holes (UMBH, with MBH > 1e10 Msun) is an open question. Using the large volume cosmological hydrodynamic simulation ASTRID, we report on the formation of an extremely massive UMBH with MBH ~ 1e11 Msun at z~2. The UMBH is assembled as a result of two successive mergers of massive galaxies each with stellar mass M* > 3e11 Msun that also produces a bright, rare triple quasar system powered by three ~10^9 Msun black holes. The second merger of supermassive black holes (SMBHs) follows the first after 150 Myrs. The merger events lead to sustained Eddington accretion onto the central SMBH, forming an UMBH in the center of a massive compact stellar core with M* > 2e12 Msun. The strong feedback of the UMBH quenches the surrounding star formation to < 10 Msun/yr in the inner 50 kpc/h region. There are two more UMBHs with MBH > 5e10 Msun at z>2 in ASTRID which are also produced by major mergers of galaxies, and their progenitors can be observed as quasar triplets of lower luminosity. The rarely observed quasar multiples can be the cradle of UMBHs at high redshift, and likely end up in the center of the most massive clusters., Comment: 7 pages, 4 figures, comments welcome

The statistics of galactic-scale quasar pairs can elucidate our understanding of the dynamical evolution of supermassive black hole (SMBH) pairs, the duty cycles of quasar activity in mergers, or even the nature of dark matter, but have been challenging to measure at cosmic noon, the prime epoch of massive galaxy and SMBH formation. Here we measure a double quasar fraction of $\sim 6.2\pm0.5\times 10^{-4}$ integrated over $\sim 0.3-3$ arcsec separations (projected physical separations of $\sim 3-30\,{\rm kpc}$ at $z\sim 2$) in luminous ($L_{\rm bol}>10^{45.8}\,{\rm erg\,s^{-1}}$) unobscured quasars at $1.5

We examine the dual (both BHs active) and offset (one BH active) AGN population (comprising $\sim$ 2000 pairs at $0.5\,\text{kpc}\lesssim\Delta r<30\,\text{kpc}$) at $z=2\sim3$ in the ASTRID simulation covering (360 cMpc)${^3}$. The dual (offset) AGN make up $3.0(2.2)\%$ of all AGN at $z=2$. The dual fraction is roughly constant while the offset fraction increases by a factor of ten from $z=4\sim2$. Compared with the full AGN population, duals are characterized by a low $M_\text{BH}/M_*$ ratio, a high specific star-formation rate (sSFR) of $\sim 1\,\text{Gyr}^{-1}$, and a high Eddington ratio ($\sim 0.05$, double that of single AGN). The dual AGN are formed in major galaxy mergers (typically involving $M_\text{halo}<10^{13}\,M_\odot$), with BHs that have similar masses. At small separations (when their host galaxies are in the late phase of the merger) duals become $2\sim8$ times brighter (albeit more obscured) than at larger separations. $80\%$ of these bright, close duals merge in the simulation within $\sim500\,\text{Myrs}$. Notably, the initially less-massive BH in duals frequently becomes the brighter AGN during the galaxy merger. In offset AGN, the active BH is typically $\gtrsim 10$ times more massive than its non-active counterpart and than most BHs in duals. Offsets are predominantly formed in minor galaxy mergers with the active BH residing in the center of massive halos ($ M_\text{ halo}\sim 10^{13-14}\,M_\odot$). In these deep potentials, gas stripping is common and the secondary quickly deactivates. The stripping also leads to inefficient orbital decay amongst offsets, which stall at $\Delta r\sim5\,\text{kpc}$ for a few hundred Myrs., Comment: 17 Pages, 18 Figures; comments welcome!

We present a mock image catalogue of ~100,000 MUV=-22.5 to -19.6 mag galaxies at z=7-12 from the BlueTides cosmological simulation. We create mock images of each galaxy with the James Webb (JWST), Hubble, Roman, and Euclid Space Telescopes, as well as Subaru, and VISTA, with a range of near- and mid-infrared filters. We perform photometry on the mock images to estimate the success of these instruments for detecting high-z galaxies. We predict that JWST will have unprecedented power in detecting high-z galaxies, with a 95% completeness limit at least 2.5 magnitudes fainter than VISTA and Subaru, 1.1 magnitudes fainter than Hubble, and 0.9 magnitudes fainter than Roman, for the same wavelength and exposure time. Focusing on JWST, we consider a range of exposure times and filters, and find that the NIRCam F356W and F277W filters will detect the faintest galaxies, with 95% completeness at m=27.4 mag in 10ks exposures. We also predict the number of high-z galaxies that will be discovered by upcoming JWST imaging surveys. We predict that the COSMOS-Web survey will detect ~1000 MUV<-20.1 mag galaxies at 6.5

We explore implications of a range of black hole (BH) seeding prescriptions on the formation of the brightest $z\gtrsim6$ quasars in cosmological hydrodynamic simulations. The underlying galaxy formation model is the same as in IllustrisTNG. Using constrained initial conditions, we study the growth of BHs in rare overdense regions (forming $\gtrsim10^{12}M_{\odot}/h$ halos by $z=7$) using a $(9~\mathrm{Mpc}/h)^3$ simulated volume. BH growth is maximal within halos that are compact and have a low tidal field. For these halos, we consider an array of gas-based seeding prescriptions wherein $M_{\mathrm{seed}}=10^4-10^6~M_{\odot}/h$ seeds are inserted in halos above critical thresholds for halo mass and dense, metal-poor gas mass (defined as $\tilde{M}_{\mathrm{h}}$ and $\tilde{M}_{\mathrm{sf,mp}}$, respectively, in units of $M_{\mathrm{seed}}$). We find that a seed model with $\tilde{M}_{\mathrm{sf,mp}}=5$ and $\tilde{M}_{\mathrm{h}}=3000$ successfully produces a $z\sim6$ quasar with $\sim10^9~M_{\odot}$ mass and $\sim10^{47}~\mathrm{ergs~s^ {-1}}$ luminosity. BH mergers play a crucial role at $z\gtrsim9$, causing an early boost in BH mass at a time when accretion-driven BH growth is negligible. When more stringent seeding conditions are applied (for e.g., $\tilde{M}_{\mathrm{sf,mp}}=1000$), the relative paucity of BH seeds results in a much lower merger rate. In this case, $z\gtrsim6$ quasars can only be formed if we enhance the maximum allowed BH accretion rates (by factors $\gtrsim10$) compared to the accretion model used in IllustrisTNG. This can be achieved either by allowing for super-Eddington accretion, or by reducing the radiative efficiency. Our results show that progenitors of $z\sim6$ quasars have distinct BH merger histories for different seeding models, which will be distinguishable with LISA observations., Comment: 21 pages, 15 figures

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project was developed to combine cosmology with astrophysics through thousands of cosmological hydrodynamic simulations and machine learning. CAMELS contains 4,233 cosmological simulations, 2,049 N-body and 2,184 state-of-the-art hydrodynamic simulations that sample a vast volume in parameter space. In this paper we present the CAMELS public data release, describing the characteristics of the CAMELS simulations and a variety of data products generated from them, including halo, subhalo, galaxy, and void catalogues, power spectra, bispectra, Lyman-$\alpha$ spectra, probability distribution functions, halo radial profiles, and X-rays photon lists. We also release over one thousand catalogues that contain billions of galaxies from CAMELS-SAM: a large collection of N-body simulations that have been combined with the Santa Cruz Semi-Analytic Model. We release all the data, comprising more than 350 terabytes and containing 143,922 snapshots, millions of halos, galaxies and summary statistics. We provide further technical details on how to access, download, read, and process the data at \url{https://camels.readthedocs.io}., Comment: 18 pages, 3 figures. More than 350 Tb of data from thousands of simulations publicly available at https://www.camel-simulations.org

We examine massive black hole (MBH) mergers and their associated gravitational wave signals from the large-volume cosmological simulation Astrid. Astrid includes galaxy formation and black hole models recently updated with a MBH seed population between $3\times 10^4M_{\odot}/h$ and $3\times 10^5M_{\odot}/h$ and a sub-grid dynamical friction (DF) model to follow the MBH dynamics down to $1.5\;\text{ckpc}/h$. We calculate initial eccentricities of MBH orbits directly from the simulation at kpc-scales, and find orbital eccentricities above $0.7$ for most MBH pairs before the numerical merger. After approximating unresolved evolution on scales below ${\sim 200\,\text{pc}}$, we find that the in-simulation DF on large scales accounts for more than half of the total orbital decay time ($\sim 500\,\text{Myrs}$) due to DF. The binary hardening time is an order of magnitude longer than the DF time, especially for the seed-mass binaries ($M_\text{BH}<2M_\text{seed}$). As a result, only $\lesssim20\%$ of seed MBH pairs merge at $z>3$ after considering both unresolved DF evolution and binary hardening. These $z>3$ seed-mass mergers are hosted in a biased population of galaxies with the highest stellar masses of $>10^9\,M_\odot$. With the higher initial eccentricity prediction from Astrid, we estimate an expected merger rate of $0.3-0.7$ per year from the $z>3$ MBH population. This is a factor of $\sim 7$ higher than the prediction using the circular orbit assumption. The LISA events are expected at a similar rate, and comprise $\gtrsim 60\%$ seed-seed mergers, $\sim 30\%$ involving only one seed-mass MBH, and $\sim 10\%$ mergers of non-seed MBHs., Comment: 17 pages, 13 Figures; comments are welcome

We introduce the ASTRID simulation, a large-scale cosmological hydrodynamic simulation in a $250$ Mpc/h box with $2\times 5500^3$ particles. ASTRID contains a large number of high redshift galaxies, which can be compared to future survey data, and resolves galaxies in halos more massive than $2\times 10^9 M_\odot$. ASTRID has been run from $z=99$ to $z=3$. As a particular focus is modelling the high redshift Universe, it contains models for inhomogeneous hydrogen and helium reionization, baryon relative velocities and massive neutrinos, as well as supernova and AGN feedback. The black hole model includes mergers driven by dynamical friction rather than repositioning. We briefly summarise the implemented models, and the technical choices we took when developing the simulation code. We validate the model, showing good agreement with observed UV luminosity functions, galaxy stellar mass functions and specific star formation rates. We show that the redshift at which a given galaxy underwent hydrogen reionization has a large effect on the halo gas fraction. Finally, at $z=6$, halos with $M \sim 2\times 10^9 M_\odot$ which have been reionized have a star formation rate $1.5$ times greater than those which have not yet been reionized., Comment: 15 pages, 12 figures. Accepted by MNRAS, added star formation rate density

We present the evolution of black holes (BHs) and their relationship with their host galaxies in Astrid, a large-volume cosmological hydrodynamical simulation with box size 250 $h^{-1} \rm Mpc$ containing $2\times5500^3$ particles evolved to z=3. Astrid statistically models BH gas accretion and AGN feedback to their environments, applies a power-law distribution for BH seed mass $M_{\rm sd}$, uses a dynamical friction model for BH dynamics and executes a physical treatment of BH mergers. The BH population is broadly consistent with empirical constraints on the BH mass function, the bright end of the luminosity functions, and the time evolution of BH mass and accretion rate density. The BH mass and accretion exhibit a tight correlation with host stellar mass and star formation rate. We trace BHs seeded before z>10 down to z=3, finding that BHs carry virtually no imprint of the initial $M_{\rm sd}$ except those with the smallest $M_{\rm sd}$, where less than 50\% of them have doubled in mass. Gas accretion is the dominant channel for BH growth compared to BH mergers. With dynamical friction, Astrid predicts a significant delay for BH mergers after the first encounter of a BH pair, with a typical elapse time of about 200 Myrs. There are in total $4.5 \times 10^5$ BH mergers in Astrid at z>3, $\sim 10^3$ of which have X-ray detectable EM counterparts: a bright kpc scale dual AGN with $L_X>10^{43}$ erg/s. BHs with $M_{\rm BH} \sim 10^{7-8} M_{\odot}$ experience the most frequent mergers. Galaxies that host BH mergers are unbiased tracers of the overall $M_{\rm BH} - M_{*}$ relation. Massive ($>10^{11} M_{\odot}$) galaxies have a high occupation number (>10) of BHs, and hence host the majority of BH mergers., Comment: Match the published version

We study the sizes of galaxies in the Epoch of Reionization using a sample of ~100,000 galaxies from the BlueTides cosmological hydrodynamical simulation from z=7 to 11. We measure the galaxy sizes from stellar mass and luminosity maps, defining the effective radius as the minimum radius which could enclose the pixels containing 50% of the total mass/light in the image. We find an inverse relationship between stellar mass and effective half-mass radius, suggesting that the most massive galaxies are more compact and dense than lower mass galaxies, which have flatter mass distributions. We find a mildly negative relation between intrinsic far-ultraviolet luminosity and size, while we find a positive size-luminosity relation when measured from dust-attenuated images. This suggests that dust is the predominant cause of the observed positive size-luminosity relation, with dust preferentially attenuating bright sight lines resulting in a flatter emission profile and thus larger measured effective radii. We study the size-luminosity relation across the rest-frame ultraviolet and optical, and find that the slope decreases at longer wavelengths; this is a consequence of the relation being caused by dust, which produces less attenuation at longer wavelengths. We find that the far-ultraviolet size-luminosity relation shows mild evolution from z=7 to 11, and galaxy size evolves with redshift as $R\propto(1+z)^{-m}$, where $m=0.662\pm0.009$. Finally, we investigate the sizes of z=7 quasar host galaxies, and find that while the intrinsic sizes of quasar hosts are small relative to the overall galaxy sample, they have comparable sizes when measured from dust-attenuated images., Comment: 12 pages, 10 figures. Accepted for publication in MNRAS

Significant clustering around the rarest luminous quasars is a feature predicted by dark matter theory combined with number density matching arguments. However, this expectation is not reflected by observations of quasars residing in a diverse range of environments. Here, we assess the tension in the diverse clustering of visible $i$-band dropout galaxies around luminous $z\sim6$ quasars. Our approach uses a simple empirical method to derive the median luminosity to halo mass relation, $L_{c}(M_{h})$ for both quasars and galaxies under the assumption of log-normal luminosity scatter, $\Sigma_{Q}$ and $\Sigma_{G}$. We show that higher $\Sigma_{Q}$ reduces the average halo mass hosting a quasar of a given luminosity, thus introducing at least a partial reversion to the mean in the number count distribution of nearby Lyman-Break galaxies. We generate a large sample of mock Hubble Space Telescope fields-of-view centred across rare $z\sim6$ quasars by resampling pencil beams traced through the dark matter component of the BlueTides cosmological simulation. We find that diverse quasar environments are expected for $\Sigma_{Q}>0.4$, consistent with numerous observations and theoretical studies. However, we note that the average number of galaxies around the central quasar is primarily driven by galaxy evolutionary processes in neighbouring halos, as embodied by our parameter $\Sigma_{G}$, instead of a difference in the large scale structure around the central quasar host, embodied by $\Sigma_{Q}$. We conclude that models with $\Sigma_{G}>0.3$ are consistent with current observational constraints on high-z quasars, and that such a value is comparable to the scatter estimated from hydrodynamical simulations of galaxy formation., Comment: 19 pages, 8 figures; accepted for publication in ApJ

In this work, we expand and test the capabilities of our recently developed super-resolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity, from computationally cheap low-resolution (LR) cosmological N-body simulations. The SR model enhances the simulation resolution by generating 512 times more tracer particles, extending into the deeply non-linear regime where complex structure formation processes take place. We validate the SR model by deploying the model in 10 test simulations of box size 100 Mpc/h, and examine the matter power spectra, bispectra and 2D power spectra in redshift space. We find the generated SR field matches the true HR result at percent level down to scales of k ~ 10 h/Mpc. We also identify and inspect dark matter halos and their substructures. Our SR model generate visually authentic small-scale structures, that cannot be resolved by the LR input, and are in good statistical agreement with the real HR results. The SR model performs satisfactorily on the halo occupation distribution, halo correlations in both real and redshift space, and the pairwise velocity distribution, matching the HR results with comparable scatter, thus demonstrating its potential in making mock halo catalogs. The SR technique can be a powerful and promising tool for modelling small-scale galaxy formation physics in large cosmological volumes., Comment: 13 pages, 11 figures, published version

In this work we establish and test methods for implementing dynamical friction for massive black hole pairs that form in large volume cosmological hydrodynamical simulations which include galaxy formation and black hole growth. We verify our models and parameters both for individual black hole dynamics and for the black hole population in cosmological volumes. Using our model of dynamical friction (DF) from collisionless particles, black holes can effectively sink close to the galaxy center, provided that the black hole's dynamical mass is at least twice that of the lowest mass resolution particles in the simulation. Gas drag also plays a role in assisting the black holes' orbital decay, but it is typically less effective than that from collisionless particles, especially after the first billion years of the black hole's evolution. DF from gas becomes less than $1\%$ of DF from collisionless particles for BH masses $> 10^{7}$ M$_{\odot}$. Using our best DF model, we calculate the merger rate down to $z=1.1$ using an $L_{\rm box}=35$ Mpc$/h$ simulation box. We predict $\sim 2$ mergers per year for $z>1.1$ peaking at $z\sim 2$. These merger rates are within the range obtained in previous work using similar-resolution hydro-dynamical simulations. We show that the rate is enhanced by factor of $\sim 2$ when DF is taken into account in the simulations compared to the no-DF run. This is due to $>40\%$ more black holes reaching the center of their host halo when DF is added., Comment: 17 pages, 12 figures; Comments welcome!

The bright emission from high-redshift quasars completely conceals their host galaxies in the rest-frame ultraviolet/optical, with detection of the hosts in these wavelengths eluding even the Hubble Space Telescope (HST) using detailed point spread function (PSF) modelling techniques. In this study we produce mock images of a sample of z=7 quasars extracted from the BlueTides simulation, and apply Markov Chain Monte Carlo-based PSF modelling to determine the detectability of their host galaxies with the James Webb Space Telescope (JWST). While no statistically significant detections are made with HST, we predict that at the same wavelengths and exposure times JWST NIRCam imaging will detect ~50% of quasar host galaxies. We investigate various observational strategies, and find that NIRCam wide-band imaging in the long-wavelength filters results in the highest fraction of successful quasar host detections, detecting >80% of the hosts of bright quasars in exposure times of 5 ks. Exposure times of ~5 ks are required to detect the majority of host galaxies in the NIRCam wide-band filters, however even 10 ks exposures with MIRI result in <30% successful host detections. We find no significant trends between galaxy properties and their detectability. The PSF modelling can accurately recover the host magnitudes, radii, and spatial distribution of the larger-scale emission, when accounting for the central core being contaminated by residual quasar flux. Care should be made when interpreting the host properties measured using PSF modelling., Comment: 21 pages, 14 figures. Resubmitted to MNRAS following referee feedback, with most notable improvements in Section 5

In this work, we use the constrained Gaussian realization technique to study the early growth of supermassive black holes (SMBHs) in cosmological hydrodynamic simulations, exploring its relationship with features of the initial density peaks on large scales, ~1 Mpc/h. Our constrained simulations of volume (20 Mpc/h)^3 successfully reconstruct the large-scale structure as well as the black hole growth for the hosts of the rare 10^9 Msun SMBHs found in the BlueTides simulation at z~7. We run a set of simulations with constrained initial conditions by imposing a 5 \sigma_0(R_G) peak on scale of R_G = 1 Mpc/h varying different peak features, such as the shape and compactness as well as the tidal field surrounding the peak. We find that initial density peaks with high compactness and low tidal field induce the most rapid BH growth at early epochs. This is because compact density peaks with a more spherical large scale matter distribution lead to the formation of high density gas clumps in the centers of halos, and thus boost early BH accretion. Moreover, such initially compact density peaks in low tidal field regions also lead to a more compact BH host galaxy morphology. This can explain the tight correlation between BH growth and host galaxy compactness seen in observations., Comment: matches MNRAS accepted version

Cosmological simulations of galaxy formation are limited by finite computational resources. We draw from the ongoing rapid advances in Artificial Intelligence (specifically Deep Learning) to address this problem. Neural networks have been developed to learn from high-resolution (HR) image data, and then make accurate super-resolution (SR) versions of different low-resolution (LR) images. We apply such techniques to LR cosmological N-body simulations, generating SR versions. Specifically, we are able to enhance the simulation resolution by generating 512 times more particles and predicting their displacements from the initial positions. Therefore our results can be viewed as new simulation realizations themselves rather than projections, e.g., to their density fields. Furthermore, the generation process is stochastic, enabling us to sample the small-scale modes conditioning on the large-scale environment. Our model learns from only 16 pairs of small-volume LR-HR simulations, and is then able to generate SR simulations that successfully reproduce the HR matter power spectrum to percent level up to $16\,h^{-1}\mathrm{Mpc}$, and the HR halo mass function to within $10 \%$ down to $10^{11} \, M_\odot$. We successfully deploy the model in a box 1000 times larger than the training simulation box, showing that high-resolution mock surveys can be generated rapidly. We conclude that AI assistance has the potential to revolutionize modeling of small-scale galaxy formation physics in large cosmological volumes., Comment: 10 pages, 8 figures, matches PNAS accepted version

High-$z$ AGNs hosted in gas rich galaxies are expected to grow through significantly obscured accretion phases. This may limit or bias their observability. In this work, we use \textsc{BlueTides}, a large volume cosmological simulation of galaxy formation to examine quasar obscuration for the highest-redshift ($z \geq 7$) supermassive black holes residing in the center of galaxies. We find that for the bright quasars, most of the high column density gas ($>90\%$) resides in the innermost regions of the host galaxy, (typically within $< 10$ ckpc), while the gas in the outskirts is a minor contributor to the $N_\mathrm H$. The brightest quasars can have large angular variations in galactic obscuration, over 2 orders of magnitude, where the lines of sight with the lowest obscuration are those formed via strong gas outflows driven by AGN feedback. We find that for the overall AGN population, the mean $N_\mathrm H$ is generally larger for high luminosity and BH mass, while the $N_\mathrm H$ distribution is significantly broadened, developing a low $N_\mathrm H $ wing due to the angular variations driven by the AGN outflows/feedback. The obscured fraction P($N_{\rm H} > 10^{23} {\rm cm}^{-2}$) typically range from 0.6 to 1.0 for increasing $L_{X}$ (with $L_X > 10^{43} \rm{ergs/s}$), with no clear trend of redshift evolution. With respect to the galaxy host property, we find a linear relation between $N_{\rm H}$, $M_*$ and $M_{\rm H_2}$ with $\log N_{\rm H} = (0.24 \pm 0.03) \log M_{*} + (20.7 \pm 0.3)$ and $\log N_{\rm H} = (0.47 \pm 0.03) \log M_{\rm H_2} + (18.4 \pm 0.3)$. The dust optical depth in the UV band $\tau_{\mathrm UV}$ has tight positive correlation with $N_{\rm H}$. Our dust extincted UVLF is about 1.5 dex lower than the intrinsic UVLF, implying that more than 99\% of the $z \sim 7$ AGNs are heavily dust extincted and therefore would be missed by the UV band observation.

We examine the properties of the host galaxies of $z=7$ quasars using the large volume, cosmological hydrodynamical simulation BlueTides. We find that the 10 most massive black holes and the 191 quasars in the simulation (with $M_{\textrm{UV,AGN}}10^{6.5}M_\odot$ black hole, indicating that minor mergers play at least some role in growing black holes in the early Universe., Comment: 19 pages, 20 figures. Accepted for publication in MNRAS