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Boon Kiat Oh

Publications and source records attributed to Boon Kiat Oh.

At least 19 recordsLinked to original sources

The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 1: Effects of a Major Galaxy Merger on Star Formation of a Milky Way-mass Galaxy Progenitor

Given their highly nonlinear dynamics and sensitivity to initial conditions, galaxy mergers are a compelling area to conduct a simulation code comparison. We perform a comparative study of a major galaxy merger at $z \approx 4.5$ in cosmological zoom-in hydrodynamic simulations of a Milky Way-mass galaxy progenitor. The comparison employs the AGORA CosmoRun suite of nine well-calibrated, state-of-the-art numerical codes, each adopting a different stellar feedback scheme. We find that the evolution of the star formation rate (SFR) during the interaction is strongly shaped by the stellar feedback type. Using kinetic feedback in the feedback model drives a pronounced merger-induced starburst that starts to subside before coalescence; using thermal feedback without kinetic feedback yields prolonged SFR growth even after coalescence; and using delayed cooling or radiation pressure results in highly fluctuating SFR. Tracking gas particles in particle-based codes reveals that kinetic feedback facilitates gas inflow from the secondary galaxy onto the primary galaxy between the first periapsis and apoapsis, thus producing an earlier and more prominent starburst. In contrast, thermal feedback, augmented by superbubble or delayed-cooling feedback, suppresses gas cooling, creates a more extended gas distribution, and hinders strong starbursts during the merger. We also observe an inverse correlation between burst fraction and pre-merger gas fraction that is independent of feedback models. Overall, these results highlight the sensitivity of simulated galaxy mergers' star formation response to stellar feedback prescriptions. This study indicates that galaxy mergers may serve as a good testbed for stellar feedback processes in cosmological simulations.

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The AGORA High-resolution Galaxy Simulations Comparison Project. IX - Part 2: Effects of a Major Galaxy Merger on the Stellar Morphology of a Milky Way-mass Galaxy Progenitor

Galaxy mergers, with their high sensitivity to initial conditions, provide a valuable setting for comparative studies of galaxy simulation codes. Following our first paper focusing on merger-driven star formation, we present a code comparison examining the morphological transformation impact of a major galaxy merger at $z \approx 4.5$ on a Milky Way-mass galaxy progenitor. Our analysis employs nine state-of-the-art codes from the AGORA CosmoRun cosmological zoom-in simulation suite. For this merger, we show that the adopted stellar feedback type influences the galaxy's compaction and stellar disc formation. Codes with purely thermal feedback produce a merger remnant that forms a disc and becomes compact primarily during and after coalescence; codes that include kinetic feedback begin disc formation and compaction around the first periapsis; and codes with strong delayed cooling or superbubble feedback suppress disc formation and produce a more extended remnant. In contrast, the orientation of the remnant disc is code-independent. In all codes, the rotational angular momentum of the remnant disc aligns with the interaction's orbital angular momentum rather than the pre-merger rotational axis, implying that the infalling gas preserves its orbital angular momentum to form a new disc. Comparisons with the Santa Cruz semi-analytic model show reasonable agreement in stellar mass and half-mass radius, yet the model underpredicts (overpredicts) the dark matter fraction and velocity dispersion for codes exhibiting strong compaction (expansion). The systematic dependence of our remnants' morphology on feedback schemes demonstrates that merger remnant morphology may serve as a powerful probe of stellar feedback processes.

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Investigating black hole accretion and feedback self-regulation in Seyfert galaxies using the FIRE-3 cosmological hydrodynamic simulations

Recent observations of local Seyfert galaxies show an intriguing connection between Active Galactic Nuclei (AGN) luminosity and a deficit of molecular gas on ~50pc scales compared to 200pc, the plausible imprint of AGN feedback. Motivated by these findings, we investigate the interplay between supermassive black hole (BH) accretion, AGN feedback, and nuclear gas reservoirs using high-resolution cosmological hydrodynamic simulations implementing FIRE-3 multi-phase interstellar medium (ISM) physics and multi-component BH accretion and feedback models. Focusing on the late-time evolution of four Milky Way-mass galaxies, we find recurrent cycles of increased gas inflow toward the accretion disc, enhanced BH accretion, feedback self-regulation, and suppressed gas inflow rate until the next fueling event. AGN winds interact with the ISM and escape preferentially through low-density polar channels after opening central cavities on ~10-500pc scales, regulating BH growth and producing episodic behaviour on ~10-100Myr timescales. The simulations reproduce the observed diversity of nuclear morphologies, gas concentrations, and AGN luminosities in late-type Seyfert galaxies, but do not exhibit a clear anti-correlation between gas concentration and AGN luminosity. Higher-luminosity AGN ($L_X$~$10^{41.5-43}$ erg s$^{-1}$) powered by the accretion disc reservoir can coexist with feedback-driven cavities, consistent with observations, but they are more common in simulated galaxies with centrally-peaked gas distributions. Although differences in sample selection, tracer choice, spatial resolution, and stochasticity in AGN fueling may impact underlying concentration-luminosity trends, the apparent tension between simulations and observations points to the timing between gas inflow, accretion-disc depletion, and feedback-driven clearing on ~50-200pc scales as a key constraint on AGN self-regulation models.

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Little Red Dots on FIRE: Exploring the formation and observational signatures of ultra-compact early galaxies

Little Red Dots (LRDs) are compact sources with broad Balmer lines, Balmer breaks, anomalous UV emission, rising red continuum, and uncertain origin. We use FIRE cosmological simulations, 3D dust radiative transfer, and synthetic emission-line data cubes to test whether ultra-compact early galaxies can reproduce LRD-like observables without invoking AGN. In progenitors of present-day group halos ($M_{\rm halo} > 10^{13.5} M_{\odot}$), we identify transient phases at $z \approx 4-8$ lasting $\sim 150-400$ Myr in which strong dissipative inflows build massive ($M_{\star} \sim 10^{8.5}-10^{10.5} M_{\odot}$), UV-bright ($-23 \lesssim M_{\rm UV} \lesssim -20$), ultra-compact ($R_{\rm eff} < 300$ pc) stellar cores with extreme circular velocity ($V_{\rm circ} > 500$ km s$^{-1}$) and consistent with several LRD properties: strong Balmer breaks ($F_ν(4200{\rm Å})/F_ν(3500{\rm Å}) \sim 2$); blue UV beta slopes ($β_{\rm UV} \approx -1.25$); dust masses; ALMA non-detections; and Balmer-line widths up to $\sim 1500$ km s$^{-1}$ broadened by galaxy-scale dynamics. However, stellar emission and host-galaxy kinematics alone do not reproduce the red rest-optical continuum, more extreme Balmer breaks ($\gtrsim 2.5$) and line widths ($\gtrsim 2000$ km s$^{-1}$), or the broad-Balmer/narrow-forbidden-line signature of broad-line AGN. The same ultra-compact conditions efficiently fuel central BHs, suggesting a hybrid stellar+AGN scenario in which compact stars explain the UV continuum, Balmer break, and intermediate line widths while AGN supply the red optical continuum and more extreme line properties. With halo masses $M_{\rm halo} \sim 10^{11-12.5} M_\odot$ and comoving abundance $\sim 2 \times 10^{-5} {\rm cMpc}^{-3}$ (for $\sim 20\%$ duty-cycle at $z \approx 4-8$), ultra-compact galaxies can contribute to the massive, bright LRD population.

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Learning the Universe at High Redshifts: Impact of Accretion Modeling on Early Black Hole Growth

JWST discoveries of the earliest ($z \gtrsim 9$) supermassive black holes (BHs, $M_\bullet \gtrsim 10^6\,\rm{M}_\odot$) challenge the BH seeding and accretion models of most cosmological simulations. In this work, we compare early BH growth arising from three different accretion prescriptions characterized by distinct scalings between the accretion rate ($\dot{M}_{\rm \bullet}$) and the BH mass ($M_{\rm \bullet}$): the commonly used Bondi-Hoyle model ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^2$), and two free-fall models with shallower scalings ($\dot{M}_{\rm \bullet}\propto M_{\rm \bullet}^{1/2}$ and $M_{\rm \bullet}$). Bondi accretion tends to produce stronger runaway growth than the free-fall models when using heavy ($\sim10^5\,\rm{M}_\odot$) seeds in extreme environments owing to the steeper $M_\bullet$ scaling, but its sensitivity to the local gas sound speed makes it more susceptible to suppression from temperature increases due to AGN and stellar feedback. The free-fall models tend to produce stronger growth for lower-mass seeds ($\sim10^{3-4}\,\rm{M}_\odot$) in moderate environments as they are less dependent on the BH's mass to accrete effectively, however in this regime BH growth remains negligible for all accretion models in the presence of fiducial stellar feedback. Enhancing early BH growth via many BH-BH mergers disproportionately enhances subsequent accretion-driven growth for Bondi due to the steeper $M_{\rm \bullet}$ dependence. Our simulations can thus assemble BHs with masses of $\sim10^6-10^7~M_{\odot}$ at $z\gtrsim9$, as inferred by JWST, under two circumstances: 1) abundant heavy-seed formation that drives BH-BH mergers, or 2) Bondi accretion with weak feedback.

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Learning the Universe with the 2nd Generation of CAMELS: Varying 35 parameters of the IllustrisTNG model in (50Mpc/h)^3 boxes

We present a new set of 1,192 cosmological simulations as part of the CAMELS project, in which a space of 35 cosmological, astrophysical, and numerical parameters is explored around the fiducial IllustrisTNG model. The volume of each of these simulations is (50Mpc/h)^3, eight times larger than that of previous CAMELS simulations. This provides lower sample variance as well as access to more massive halos and more diverse environments. We focus this work on exploring the advantages these differences provide for parameter inference powered by neural networks. We generate training sets based on the matter power spectra, projected maps of the volumes, graphs representing galaxy spatial distributions, and thermodynamical properties of massive halos. We employ multilayer perceptrons, convolutional neural networks, graph neural networks, and Gaussian processes, respectively, to extract information on the simulation parameters from these inputs while comparing systematically to analogous results from our previous generation of (25Mpc/h)^3 simulations. We generally find that the new, larger volumes produce tighter marginal constraints on the parameters, to degrees that vary between the different inputs. The improvements, however, scale more weakly than with the square root of the increase in the amount of data (i.e., physical volume). We interpret this as originating either from information loss due to mode coupling or from complex degeneracies in parameter space. We also discuss the effects on statistics of the intergalactic medium temperature from four new parameters that are varied in these simulations, which control the amplitude and timing of the ionizing background radiation. We publicly release the simulation outputs and ancillary data at https://camels.readthedocs.io.

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The AGORA High-resolution Galaxy Simulations Comparison Project. XI: Solving the Non-Spherical Morphology and Evolution of Dark Matter Halos with Haskap Pie

We introduce a halo solving and tracking procedure that intrinsically treats dark matter halos as non-spherical objects by leveraging the bound particle searching techniques used in Haskap Pie. The AGORA Collaboration's hydrodynamic simulation CosmoRun}project provides a useful laboratory to explore trends in dark matter halo morphology that are revealed by our new procedure in the context of any dispersions or similarities between the codes. We find that several morphological and shape measures were very responsive to high mass ratio mergers. The greatest difference in these measures between the simulation codes were related to timing discrepancies and the dynamical state of the halos prior to the mergers. Most other quantities were similar across codes, including several secular and redshift-dependent trends in various dynamical quantities that showed a departure from Virial Theorem (e.g., overdensity and halo mass). We find that halo spin and the ratio between the semi-major and the semi-minor axis peaked at 4>z>2 before declining at low redshift. Also, halo overdensity is both mass-dependent and redshift-dependent, diverging for low mass halos at low redshift. Our method contributes a new perspective on these trends that have not been fully replicated in other works due to our emphasis on fundamentally non-spherical halos and measures of morphology that correspondingly do not assume spherical symmetry.

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AGN jet evolution simulation with GADGET4-OSAKA

Active galactic nuclei (AGN) jets are powerful drivers of galaxy evolution, depositing energy and momentum into the circumgalactic and intracluster medium (CGM/ICM) and regulating gas cooling and star formation. We investigate the dynamics of jet evolution in the self-similar regime using the smoothed particle hydrodynamics (SPH) code GADGET4-Osaka, systematically vary jet-launching schemes, artificial-viscosity prescriptions, mass resolution, and jet lifetimes and compare the results with grid-based simulation. Our analysis combines quantitative diagnostics of jet size and energetics with detailed morphological and thermodynamic characterizations from slice maps and phase diagrams. We find that jet lobe growth follows analytic self-similar scaling relations and converges with resolution, but is highly sensitive to the choice of artificial viscosity. While the overall jet size tracks self-similar predictions, the partitioning of thermal and kinetic energy departs significantly from the idealized picture, reflecting enhanced dissipation and mixing, which is consistent with the jet propagation in grid-based simulations. These results establish robust benchmarks for SPH-based jet modeling, provide insight into the physical and numerical factors shaping jet--medium interactions, and lay the groundwork for future studies of AGN feedback in realistic galactic and cluster environments.

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The AGORA High-resolution Galaxy Simulations Comparison Project. X: Formation and Evolution of Galaxies at the High-redshift Frontier

Recent observations from JWST have revealed unexpectedly luminous galaxies, exhibiting stellar masses and luminosities significantly higher than predicted by theoretical models at Cosmic Dawn. In this study, we present a suite of cosmological zoom-in simulations targeting high-redshift ($z \geq 10$) galaxies with dark matter halo masses in the range $10^{10} - 10^{11}\ {\rm M}_{\odot}$ at $z=10$, using state-of-the-art galaxy formation simulation codes (Enzo, Ramses, Changa, Gadget-3, Gadget-4, and Gizmo). This study aims to evaluate the convergence of the participating codes and their reproducibility of high-redshift galaxies with the galaxy formation model calibrated at relatively low redshift, without additional physics for high-redshift environments. The subgrid physics follows the AGORA CosmoRun framework, with adjustments to resolution and initial conditions to emulate similar physical environments in the early universe. The participating codes show consistent results for key galaxy properties (e.g., stellar mass), but also reveal notable differences (e.g., metallicity), indicating that galaxy properties at high redshifts are highly sensitive to the feedback implementation of the simulation. Massive halos (${\rm M}_{\rm halo}\geq5\times10^{10}\,{\rm M}_{\odot}$ at $z=10$) succeed in reproducing observed stellar masses, metallicities, and UV luminosities at $10\leq z\leq12$ without requiring additional subgrid physics, but tend to underpredict those properties at higher redshift. We also find that varying the dust-to-metal ratio modestly affects UV luminosity of simulated galaxies, whereas the absence of dust significantly enhances it. In future work, higher-resolution simulations will be conducted to better understand the formation and evolution of galaxies at Cosmic Dawn.

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Cosmological back-reaction of baryons on dark matter in the CAMELS simulations

Baryonic processes such as radiative cooling and feedback from massive stars and active galactic nuclei (AGN) directly redistribute baryons in the Universe but also indirectly redistribute dark matter due to changes in the gravitational potential. In this work, we investigate this "back-reaction" of baryons on dark matter using thousands of cosmological hydrodynamic simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, including parameter variations in the SIMBA, IllustrisTNG, ASTRID, and Swift-EAGLE galaxy formation models. Matching haloes to corresponding N-body (dark matter-only) simulations, we find that virial masses decrease owing to the ejection of baryons by feedback. Relative to N-body simulations, halo profiles show an increased dark matter density in the center (due to radiative cooling) and a decrease in density farther out (due to feedback), with both effects being strongest in SIMBA (> 450% increase at r < 0.01 Rvir). The clustering of dark matter strongly responds to changes in baryonic physics, with dark matter power spectra in some simulations from each model showing as much as 20% suppression or increase in power at k ~ 10 h/Mpc relative to N-body simulations. We find that the dark matter back-reaction depends intrinsically on cosmology (Omega_m and sigma_8) at fixed baryonic physics, and varies strongly with the details of the feedback implementation. These results emphasize the need for marginalizing over uncertainties in baryonic physics to extract cosmological information from weak lensing surveys as well as their potential to constrain feedback models in galaxy evolution.

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The role of galactic winds fueling central starbursts and quasars in the FIRE cosmological simulations

Central starbursts and Active Galactic Nuclei (AGN) are thought to be fueled by either galaxy interactions or secular processes in gravitationally unstable discs. We employ cosmological hydrodynamic simulations from the Feedback in Realistic Environments (FIRE) project to propose a new nuclear fueling scenario based on the transition that galaxies undergo from bursty to smooth star formation and from prominent global galactic winds to inefficient stellar feedback as they grow above $M_{\star}\sim 10^{10-10.5}\,{\rm M}_{\odot}$: the last major galactic wind event shuts down star formation, evacuates gas from the galaxy, and slows down gas accretion from the circumgalactic medium (CGM), creating a $\sim$$10^{10}\,{\rm M}_{\odot}$ pileup of gas in the inner CGM which later accretes coherently onto the galaxy, achieving a tenfold increase in inflow rate over pre-outflow conditions. We explicitly track the accumulation of gas along the outflow pathway owing to hydrodynamic interactions and show that $\sim$50% of gas fueling the central $\sim$10-100$\,{\rm pc}$ over the subsequent $\sim$15$\,{\rm Myr}$ can be traced back to pileup gas having experienced $>$50% change in infall velocity owing to the wind interaction. This galactic wind pileup effect may thus represent a significant fueling mode for compact starbursts and luminous AGN. Galactic winds at earlier times or AGN-driven outflows can have qualitatively similar effects, but the pileup of gas driven by the last major galactic wind event refuels the galaxy precisely when the deepening stellar potential prevents further gas evacuation by stellar feedback, providing the ideal conditions for quasar fueling at the time when AGN feedback is most needed to regulate central star formation in massive galaxies at their peak of activity.

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The AGORA High-resolution Galaxy Simulations Comparison Project. VIII: Disk Formation and Evolution of Simulated Milky Way Mass Galaxy Progenitors at $1<z<5$

We investigate how differences in the stellar feedback produce disks with different morphologies in Milky Way-like progenitors over 1 $\leq z \leq 5$, using eight state-of-the-art cosmological hydrodynamics simulation codes in the \textit{AGORA} project. In three of the participating codes, a distinct, rotation-dominated inner core emerges with a formation timescale of $\lesssim 300$ Myr, largely driven by a major merger event, while two other codes exhibit similar signs of wet compaction -- gaseous shrinkage into a compact starburst phase -- at earlier epochs. The remaining three codes show only weak evidence of wet compaction. Consequently, we divide the simulated galaxies into two groups: those with strong compaction signatures and those with weaker ones. Galaxies in these two groups differ in size, stellar age gradients, and disk-to-total mass ratios. Specifically, codes with strong wet compaction build their outer disks in an inside-out fashion, leading to negative age gradients, whereas codes with weaker compaction feature flat or positive age gradients caused primarily by outward stellar migration. Although the stellar half-mass radii of these two groups diverge at $z \sim 3$, the inclusion of dust extinction brings their sizes and shapes in mock observations closer to each other and to observed galaxies. We attribute the observed morphological differences primarily to variations in the stellar feedback implementations -- such as delayed cooling timescales, and feedback strengths -- that regulate both the onset and duration of compaction. Overall, our results suggest that disk assembly at high redshifts is highly sensitive to the details of the stellar feedback prescriptions in simulations.

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How does feedback affect the star formation histories of galaxies?

Star formation in galaxies is regulated by the interplay of a range of processes that shape the multiphase gas in the interstellar and circumgalactic media. Using the CAMELS suite of cosmological simulations, we study the effects of varying feedback and cosmology on the average star formation histories (SFHs) of galaxies at $z\sim0$ across the IllustrisTNG, SIMBA and ASTRID galaxy formation models. We find that galaxy SFHs in all three models are sensitive to changes in stellar feedback, which affects the efficiency of baryon cycling and the rates at which central black holes grow, while effects of varying AGN feedback depend on model-dependent implementations of black hole seeding, accretion and feedback. We also find strong interaction terms that couple stellar and AGN feedback, usually by regulating the amount of gas available for the central black hole to accrete. Using a double power-law to describe the average SFHs, we derive a general set of equations relating the shape of the SFHs to physical quantities like baryon fraction and black hole mass across all three models. We find that a single set of equations (albeit with different coefficients) can describe the SFHs across all three CAMELS models, with cosmology dominating the SFH at early times, followed by halo accretion, and feedback and baryon cycling at late times. Galaxy SFHs provide a novel, complementary probe to constrain cosmology and feedback, and can connect the observational constraints from current and upcoming galaxy surveys with the physical mechanisms responsible for regulating galaxy growth and quenching.

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The AGORA High-Resolution Galaxy Simulations Comparison Project VII: Satellite quenching in zoom-in simulation of a Milky Way-mass halo

Context: Satellite galaxies experience multiple physical processes when interacting with their host halos, often leading to the quenching of star formation. In the Local Group (LG), satellite quenching has been shown to be highly efficient, affecting nearly all satellites except the most massive ones. While recent surveys are studying Milky Way (MW) analogs to assess how representative our LG is, the dominant physical mechanisms behind satellite quenching in MW-mass halos remain under debate. Aims: We analyze satellite quenching within the same MW-mass halo, simulated using various widely-used astrophysical codes, each using different hydrodynamic methods and implementing different supernovae feedback recipes. The goal is to determine whether quenched fractions, quenching timescales and the dominant quenching mechanisms are consistent across codes or if they show sensitivity to the specific hydrodynamic method and supernovae (SNe) feedback physics employed. Methods: We use a subset of high-resolution cosmological zoom-in simulations of a MW-mass halo from the multiple-code AGORA CosmoRun suite. Results: We find that the quenched fraction is consistent with the latest SAGA survey results within its 1$σ$ host-to-host scatter across all the models. Regarding quenching timescales, all the models reproduce the trend observed in the ELVES survey, LG observations, and previous simulations: the less massive the satellite, the shorter its quenching timescale. All our models converge on the dominant quenching mechanisms: strangulation halts cold gas accretion and ram pressure stripping is the predominant mechanism for gas removal, particularly effective in satellites with $M_* < 10^8\, M_\odot$. Nevertheless, the efficiency of the stripping mechanisms differs among the codes, showing a strong sensitivity to the different SNe feedback implementations and/or hydrodynamic methods employed.

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Inferring Cosmological Parameters on SDSS via Domain-Generalized Neural Networks and Lightcone Simulations

We present a proof-of-concept simulation-based inference on $Ω_{\rm m}$ and $σ_{8}$ from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid lightcone simulations, ${\rm L{\scriptsize -PICOLA}}$, mock galaxy catalogs are produced that fully incorporate the observational effects. The collection of galaxies is fed as input to a point cloud-based network, ${\texttt{Minkowski-PointNet}}$. We also add relatively more accurate ${\rm G{\scriptsize ADGET}}$ mocks to obtain robust and generalizable neural networks. By explicitly learning the representations which reduces the discrepancies between the two different datasets via the semantic alignment loss term, we show that the latent space configuration aligns into a single plane in which the two cosmological parameters form clear axes. Consequently, during inference, the SDSS BOSS LOWZ NGC catalog maps onto the plane, demonstrating effective generalization and improving prediction accuracy compared to non-generalized models. Results from the ensemble of 25 independently trained machines find $Ω_{\rm m}=0.339 \pm 0.056$ and $σ_{8}=0.801 \pm 0.061$, inferred only from the distribution of galaxies in the lightcone slices without relying on any indirect summary statistics. A single machine that best adapts to the ${\rm G{\scriptsize ADGET}}$ mocks yields a tighter prediction of $Ω_{\rm m}=0.282 \pm 0.014$ and $σ_{8}=0.786 \pm 0.036$. We emphasize that adaptation across multiple domains can enhance the robustness of the neural networks in observational data.

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Dense stellar clump formation driven by strong quasar winds in the FIRE cosmological hydrodynamic simulations

We investigate the formation of dense stellar clumps in a suite of high-resolution cosmological zoom-in simulations of a massive, star forming galaxy at $z \sim 2$ under the presence of strong quasar winds. Our simulations include multi-phase ISM physics from the Feedback In Realistic Environments (FIRE) project and a novel implementation of hyper-refined accretion disk winds. We show that powerful quasar winds can have a global negative impact on galaxy growth while in the strongest cases triggering the formation of an off-center clump with stellar mass ${\rm M}_{\star}\sim 10^{7}\,{\rm M}_{\odot}$, effective radius ${\rm R}_{\rm 1/2\,\rm Clump}\sim 20\,{\rm pc}$, and surface density $Σ_{\star} \sim 10^{4}\,{\rm M}_{\odot}\,{\rm pc}^{-2}$. The clump progenitor gas cloud is originally not star-forming, but strong ram pressure gradients driven by the quasar winds (orders of magnitude stronger than experienced in the absence of winds) lead to rapid compression and subsequent conversion of gas into stars at densities much higher than the average density of star-forming gas. The AGN-triggered star-forming clump reaches ${\rm SFR} \sim 50\,{\rm M}_{\odot}\,{\rm yr}^{-1}$ and $Σ_{\rm SFR} \sim 10^{4}\,{\rm M}_{\odot}\,{\rm yr}^{-1}\,{\rm kpc}^{-2}$, converting most of the progenitor gas cloud into stars in $\sim$2\,Myr, significantly faster than its initial free-fall time and with stellar feedback unable to stop star formation. In contrast, the same gas cloud in the absence of quasar winds forms stars over a much longer period of time ($\sim$35\,Myr), at lower densities, and losing spatial coherency. The presence of young, ultra-dense, gravitationally bound stellar clumps in recently quenched galaxies could thus indicate local positive feedback acting alongside the strong negative impact of powerful quasar winds, providing a plausible formation scenario for globular clusters.

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Merger Tree-based Galaxy Matching: A Comparative Study Across Different Resolutions

We introduce a novel halo/galaxy matching technique between two cosmological simulations with different resolutions, which utilizes the positions and masses of halos along their subhalo merger tree. With this tool, we conduct a study of resolution biases through the {\it galaxy-by-galaxy} inspection of a pair of simulations that have the same simulation configuration but different mass resolutions, utilizing a suite of {\sc IllustrisTNG} simulations to assess the impact on galaxy properties. We find that, with the subgrid physics model calibrated for TNG100-1, subhalos in TNG100-1 (high resolution) have $\lesssim0.5$ dex higher stellar masses than their counterparts in the TNG100-2 (low-resolution). It is also discovered that the subhalos with $M_{\mathrm{gas}}\sim10^{8.5}\,{\rm M}_\odot$ in TNG100-1 have $\sim0.5$ dex higher gas mass than those in TNG100-2. The mass profiles of the subhalos reveal that the dark matter masses of subhalos in TNG100-2 converge well with those from TNG100-1, except within 4 kpc of the resolution limit. The differences in stellar mass and hot gas mass are most pronounced in the central region. We exploit machine learning to build a correction mapping for the physical quantities of subhalos from low- to high-resolution simulations (TNG300-1 and TNG100-1), which enables us to find an efficient way to compile a high-resolution galaxy catalog even from a low-resolution simulation. Our tools can easily be applied to other large cosmological simulations, testing and mitigating the resolution biases of their numerical codes and subgrid physics models.

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The AGORA High-resolution Galaxy Simulations Comparison Project IV: Halo and Galaxy Mass Assembly in a Cosmological Zoom-in Simulation at $z\le2$

In this fourth paper from the AGORA Collaboration, we study the evolution down to redshift $z=2$ and below of a set of cosmological zoom-in simulations of a Milky Way mass galaxy by eight of the leading hydrodynamic simulation codes. We also compare this CosmoRun suite of simulations with dark matter-only simulations by the same eight codes. We analyze general properties of the halo and galaxy at $z=4$ and 3, and before the last major merger, focusing on the formation of well-defined rotationally-supported disks, the mass-metallicity relation, the specific star formation rate, the gas metallicity gradients, and the non-axisymmetric structures in the stellar disks. Codes generally converge well to the stellar-to-halo mass ratios predicted by semi-analytic models at $z\sim$2. We see that almost all the hydro codes develop rotationally-supported structures at low redshifts. Most agree within 0.5 dex with the observed MZR at high and intermediate redshifts, and reproduce the gas metallicity gradients obtained from analytical models and low-redshift observations. We confirm that the inter-code differences in the halo assembly history reported in the first paper of the collaboration also exist in CosmoRun, making the code-to-code comparison more difficult. We show that such differences are mainly due to variations in code-dependent parameters that control the time-stepping strategy of the gravity solver. We find that variations in the early stellar feedback can also result in differences in the timing of the low-redshift mergers. All the simulation data down to $z=2$ and the auxiliary data will be made publicly available.

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