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Ji-hoon Kim

Publications and source records attributed to Ji-hoon Kim.

At least 37 records · Page 2Linked to original sources

Growth of A Massive Black Hole Via Tidal Disruption Accretion

Stars that are tidally disrupted by the massive black hole (MBH) may contribute significantly to the growth of the MBH, especially in dense nuclear star clusters (NSCs). Yet, this tidal disruption accretion (TDA) of stars onto the MBH has largely been overlooked compared to the gas accretion (GA) channel in most numerical experiments until now. In this work, we implement a black hole growth channel via TDA in the high-resolution adaptive mesh refinement code Enzo to investigate its influence on a MBH seed's early evolution. We find that a MBH seed grows rapidly from $10^3\,\mathrm{M}_\odot$ to $\gtrsim 10^6\,\mathrm{M}_\odot$ in 200\,Myrs in some of the tested simulations. Compared to a MBH seed that grows only via GA, TDA can enhance the MBH's growth rate by up to more than an order of magnitude. However, as predicted, TDA mainly helps the early growth of the MBH (from $10^{3-4}\,\mathrm{M}_\odot$ to $\lesssim10^{5}\,\mathrm{M}_\odot$) while the later evolution is generally dominated by GA. We also observe that the star formation near the MBH is suppressed when TDA is most active, sometimes with a visible cavity in gas (of size $\sim$ a few pc) created in the vicinity of the MBH. It is because the MBH may grow expeditiously with both GA and TDA, and the massive MBH could consume its neighboring gas faster than being replenished by gas inflows. Our study demonstrates the need to consider different channels of black hole accretion that may provide clues for the existence of supermassive black holes at high redshifts.

astro-ph.GA↗

Calibrating cosmological simulations with implicit likelihood inference using galaxy growth observables

In a novel approach employing implicit likelihood inference (ILI), also known as likelihood-free inference, we calibrate the parameters of cosmological hydrodynamic simulations against observations, which has previously been unfeasible due to the high computational cost of these simulations. For computational efficiency, we train neural networks as emulators on ~1000 cosmological simulations from the CAMELS project to estimate simulated observables, taking as input the cosmological and astrophysical parameters, and use these emulators as surrogates to the cosmological simulations. Using the cosmic star formation rate density (SFRD) and, separately, stellar mass functions (SMFs) at different redshifts, we perform ILI on selected cosmological and astrophysical parameters (Omega_m, sigma_8, stellar wind feedback, and kinetic black hole feedback) and obtain full 6-dimensional posterior distributions. In the performance test, the ILI from the emulated SFRD (SMFs) can recover the target observables with a relative error of 0.17% (0.4%). We find that degeneracies exist between the parameters inferred from the emulated SFRD, confirmed with new full cosmological simulations. We also find that the SMFs can break the degeneracy in the SFRD, which indicates that the SMFs provide complementary constraints for the parameters. Further, we find that the parameter combination inferred from an observationally-inferred SFRD reproduces the target observed SFRD very well, whereas, in the case of the SMFs, the inferred and observed SMFs show significant discrepancies that indicate potential limitations of the current galaxy formation modeling and calibration framework, and/or systematic differences and inconsistencies between observations of the stellar mass function.

astro-ph.CO↗

Star Formation Variability as a Probe for the Baryon Cycle within Galaxies

We investigate the connection of the regulation of star formation and the cycling of baryons within and in and out of galaxies. We use idealized numerical simulations of Milky Way-mass galaxies, in which we systemically vary the galaxy morphology (bulge-to-total mass ratio) and stellar feedback strength (total eight setups with 80 simulations). By following individual gas parcels through the disk, spiral arms, and massive star-forming clumps, we quantify how gas moves and oscillates through the different phases of the interstellar medium (ISM) and forms stars. We show that the residence time of gas in the dense ISM phase ($τ_{\rm SF}$), the nature of spiral arms (strength, number), and the clump properties (number, mass function, and young star fraction) depend on both the galaxy morphology and stellar feedback. Based on these results, we quantify signatures of the baryon cycle within galaxies using the temporal and spatial power spectrum density (PSD) of the star formation history (SFH). Stronger stellar feedback leads to more bursty star formation while the correlation timescale of the SFH is longer, because stronger feedback dissolves the dense, star-forming ISM phase, leading to a more homogeneous ISM and a decrease in $τ_{\rm SF}$. The bulge strength has a similar effect: the deep gravitational potential in a bulge-dominant galaxy imposes a strong shear force that effectively breaks apart gas clumps in the ISM; this subsequently inhibits the fragmentation of cool gas and therefore the star formation in the disk, leading to a decrease in the spatial power on scales of $\sim$ 1 kpc. We conclude that measurements of the temporal and spatial PSD of the SFH can provide constraints on the baryon cycle and the star formation process.

astro-ph.GA↗

Machine-guided Exploration and Calibration of Astrophysical Simulations

We apply a novel method with machine learning to calibrate sub-grid models within numerical simulation codes to achieve convergence with observations and between different codes. It utilizes active learning and neural density estimators. The hyper parameters of the machine are calibrated with a well-defined projectile motion problem. Then, using a set of 22 cosmological zoom simulations, we tune the parameters of a popular star formation and feedback model within Enzo to match simulations. The parameters that are adjusted include the star formation efficiency, coupling of thermal energy from stellar feedback, and volume into which the energy is deposited. This number translates to a factor of more than three improvements over manual calibration. Despite using fewer simulations, we obtain a better agreement to the observed baryon makeup of a Milky-Way (MW) sized halo. Switching to a different strategy, we improve the consistency of the recommended parameters from the machine. Given the success of the calibration, we then apply the technique to reconcile metal transport between grid-based and particle-based simulation codes using an isolated galaxy. It is an improvement over manual exploration while hinting at a less known relation between the diffusion coefficient and the metal mass in the halo region. The exploration and calibration of the parameters of the sub-grid models with a machine learning approach is concluded to be versatile and directly applicable to different problems.

astro-ph.GA↗

Dark Matter Deficient Galaxies And Their Member Star Clusters Form Simultaneously During High-velocity Galaxy Collisions In 1.25 pc Resolution Simulations

How diffuse dwarf galaxies that are deficient in dark matter -- such as NGC1052-DF2 and NGC1052-DF4 -- formed remains a mystery. Along with their luminous member globular clusters (GCs), the so-called dark matter deficient galaxies (DMDGs) have challenged observers and theorists alike. Here we report a suite of galaxy collision simulations using the adaptive mesh refinement code ENZO with 1.25 pc resolution, which demonstrates that high-velocity galaxy collisions induce the formation of DMDGs and their star clusters (SCs) simultaneously. With a numerical resolution significantly better than our previous study (Shin et al. 2020), we resolve the dynamical structure of the produced DMDGs and the detailed formation history of their SCs which are possible progenitors of the DMDG's member GCs. In particular, we show that a galaxy collision with a high relative velocity of $\sim 300\;{\rm km\;s}^{-1}$, invoking severe shock compression, spawns multiple massive SCs ($\gtrsim 10^{6}\;{\rm M}_{\odot}$) within 150 Myr after the collision. At the end of our ~ 800 Myr fiducial run, the resulting DMDG of $M_{\star} \simeq 3.5\times 10^{8}\;{M}_{\odot}$ hosts 10 luminous ($M_{\rm V} \lesssim -8.5\;{\rm mag}$), gravitational bound SCs with a line-of-sight velocity dispersion $11.2\;{\rm km\;s}^{-1}$. Our study suggests that DMDGs and their luminous member SCs could form simultaneously in high-velocity galaxy collisions while being in line with the key observed properties of NGC1052-DF2 and NGC1052-DF4.

astro-ph.GA↗

The AGORA High-resolution Galaxy Simulations Comparison Project. III: Cosmological zoom-in simulation of a Milky Way-mass halo

We present a suite of high-resolution cosmological zoom-in simulations to $z=4$ of a $10^{12}\,{\rm M}_{\odot}$ halo at $z=0$, obtained using seven contemporary astrophysical simulation codes widely used in the numerical galaxy formation community. Physics prescriptions for gas cooling, heating, and star formation, are similar to the ones used in our previous {\it AGORA} disk comparison but now account for the effects of cosmological processes. In this work, we introduce the most careful comparison yet of galaxy formation simulations run by different code groups, together with a series of four calibration steps each of which is designed to reduce the number of tunable simulation parameters adopted in the final run. After all the participating code groups successfully completed the calibration steps, we reach a suite of cosmological simulations with similar mass assembly histories down to $z=4$. With numerical accuracy that resolves the internal structure of a target halo, we find that the codes overall agree well with one another in e.g., gas and stellar properties, but also show differences in e.g., circumgalactic medium properties. We argue that, if adequately tested in accordance with our proposed calibration steps and common parameters, the results of high-resolution cosmological zoom-in simulations can be robust and reproducible. New code groups are invited to join this comparison by generating equivalent models by adopting the common initial conditions, the common easy-to-implement physics package, and the proposed calibration steps. Further analyses of the simulations presented here will be in forthcoming reports from our Collaboration.

astro-ph.GA↗

How Metals Are Transported In And Out Of A Galactic Disk: Dependence On The Hydrodynamic Schemes In Numerical Simulations

Metallicity is a fundamental probe for understanding the baryon physics in a galaxy. Since metals are intricately associated with radiative cooling, star formation, and feedback, reproducing the observed metal distribution through numerical experiments will provide a prominent way to examine our understandings of galactic baryon physics. In this study, we analyze the dependence of the galactic metal distribution on the numerical schemes and quantify the differences in the metal mixing among modern galaxy simulation codes (the mesh-based code Enzo and the particle-based codes Gadget-2 and Gizmo-PSPH). In particular, we examine different stellar feedback strengths and an explicit metal diffusion scheme in particle-based codes, as a way to alleviate the well-known discrepancy in metal transport between mesh-based and particle-based simulations. We demonstrate that a sufficient number of gas particles are needed in the gas halo to properly investigate the metal distribution therein. Including an explicit metal diffusion scheme does not significantly affect the metal distribution in the galactic disk but does change the amount of low-metallicity gas in the hot-diffuse halo. We also find that the spatial distribution of metals depends strongly on how the stellar feedback is modeled. We demonstrate that the previously reported discrepancy in metals between mesh-based and particle-based simulations can be mitigated with our proposed prescription, enabling these simulations to be reliably utilized in the study of metals in galactic halos and the circumgalactic medium.

astro-ph.GA↗

Dark Matter Deficient Galaxies Produced Via High-velocity Galaxy Collisions In High-resolution Numerical Simulations

The recent discovery of diffuse dwarf galaxies that are deficient in dark matter appears to challenge the current paradigm of structure formation in our Universe. We describe the numerical experiments to determine if the so-called dark matter deficient galaxies (DMDGs) could be produced when two gas-rich, dwarf-sized galaxies collide with a high relative velocity of $\sim 300\,{\rm kms^{-1}}$. Using idealized high-resolution simulations with both mesh-based and particle-based gravito-hydrodynamics codes, we find that DMDGs can form as high-velocity galaxy collisions separate dark matter from the warm disk gas which subsequently is compressed by shock and tidal interaction to form stars. Then using a large simulated universe IllustrisTNG, we discover a number of high-velocity galaxy collision events in which DMDGs are expected to form. However, we did not find evidence that these types of collisions actually produced DMDGs in the TNG100-1 run. We argue that the resolution of the numerical experiment is critical to realize the "collision-induced" DMDG formation scenario. Our results demonstrate one of many routes in which galaxies could form with unconventional dark matter fractions.

astro-ph.GA↗

Self-consistent proto-globular cluster formation in cosmological simulations of high-redshift galaxies

We report the formation of bound star clusters in a sample of high-resolution cosmological zoom-in simulations of z>5 galaxies from the FIRE project. We find that bound clusters preferentially form in high-pressure clouds with gas surface densities over 10^4 Msun pc^-2, where the cloud-scale star formation efficiency is near unity and young stars born in these regions are gravitationally bound at birth. These high-pressure clouds are compressed by feedback-driven winds and/or collisions of smaller clouds/gas streams in highly gas-rich, turbulent environments. The newly formed clusters follow a power-law mass function of dN/dM~M^-2. The cluster formation efficiency is similar across galaxies with stellar masses of ~10^7-10^10 Msun at z>5. The age spread of cluster stars is typically a few Myrs and increases with cluster mass. The metallicity dispersion of cluster members is ~0.08 dex in [Z/H] and does not depend on cluster mass significantly. Our findings support the scenario that present-day old globular clusters (GCs) were formed during relatively normal star formation in high-redshift galaxies. Simulations with a stricter/looser star formation model form a factor of a few more/fewer bound clusters per stellar mass formed, while the shape of the mass function is unchanged. Simulations with a lower local star formation efficiency form more stars in bound clusters. The simulated clusters are larger than observed GCs due to finite resolution. Our simulations are among the first cosmological simulations that form bound clusters self-consistently in a wide range of high-redshift galaxies.

astro-ph.GA↗

The AGORA high-resolution galaxy simulations comparison project: Public data release

As part of the AGORA High-resolution Galaxy Simulations Comparison Project (Kim et al. 2014, 2016) we have generated a suite of isolated Milky Way-mass galaxy simulations using 9 state-of-the-art gravito-hydrodynamics codes widely used in the numerical galaxy formation community. In these simulations we adopted identical galactic disk initial conditions, and common physics models (e.g., radiative cooling and ultraviolet background by a standardized package). Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production were carefully constrained. Here we release the simulation data to be freely used by the community. In this release we include the disk snapshots at 0 and 500Myr of evolution per each code as used in Kim et al. (2016), from simulations with and without star formation and feedback. We encourage any member of the numerical galaxy formation community to make use of these resources for their research - for example, compare their own simulations with the AGORA galaxies, with the common analysis yt scripts used to obtain the plots shown in our papers, also available in this release.

astro-ph.GA↗

High-redshift Galaxy Formation with Self-consistently Modeled Stars and Massive Black Holes: Stellar Feedback and Quasar Growth

As computational resolution of modern cosmological simulations reach ever so close to resolving individual star-forming clumps in a galaxy, a need for "resolution-appropriate" physics for a galaxy-scale simulation has never been greater. To this end, we introduce a self-consistent numerical framework that includes explicit treatments of feedback from star-forming molecular clouds (SFMCs) and massive black holes (MBHs). In addition to the thermal supernovae feedback from SFMC particles, photoionizing radiation from both SFMCs and MBHs is tracked through full 3-dimensional ray tracing. A mechanical feedback channel from MBHs is also considered. Using our framework, we perform a state-of-the-art cosmological simulation of a quasar-host galaxy at z~7.5 for ~25 Myrs with all relevant galactic components such as dark matter, gas, SFMCs, and an embedded MBH seed of ~> 1e6 Ms. We find that feedback from SFMCs and an accreting MBH suppresses runaway star formation locally in the galactic core region. Newly included radiation feedback from SFMCs, combined with feedback from the MBH, helps the MBH grow faster by retaining gas that eventually accretes on to the MBH. Our experiment demonstrates that previously undiscussed types of interplay between gas, SFMCs, and a MBH may hold important clues about the growth and feedback of quasars and their host galaxies in the high-redshift Universe.

astro-ph.GA↗

Machine-assisted Semi-Simulation Model (MSSM): Estimating Galactic Baryonic Properties from their Dark Matter using a Machine Trained on Hydrodynamic Simulations

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a $(75 \,\,h^{-1}{\rm Mpc})^3$ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large $(1 \,\,h^{-1}{\rm Gpc})^3$ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

astro-ph.GA↗

Galaxy Mergers with Adaptive Mesh Refinement: Star Formation and Hot Gas Outflow

In hierarchical structure formation, merging of galaxies is frequent and known to dramatically affect their properties. To comprehend these interactions high-resolution simulations are indispensable because of the nonlinear coupling between pc and Mpc scales. To this end, we present the first adaptive mesh refinement (AMR) simulation of two merging, low mass, initially gas-rich galaxies (1.8e10 Ms each), including star formation and feedback. With galaxies resolved by ~2e7 total computational elements, we achieve unprecedented resolution of the multiphase interstellar medium, finding a widespread starburst in the merging galaxies via shock-induced star formation. The high dynamic range of AMR also allows us to follow the interplay between the galaxies and their embedding medium depicting how galactic outflows and a hot metal-rich halo form. These results demonstrate that AMR provides a powerful tool in understanding interacting galaxies.

astro-ph.GA↗

Galaxy Formation with Self-consistently Modeled Stars and Massive Black Holes. I: Feedback-regulated Star Formation and Black Hole Growth

There is mounting evidence for the coevolution of galaxies and their embedded massive black holes (MBHs) in a hierarchical structure formation paradigm. To tackle the nonlinear processes of galaxy-MBH interaction, we describe a self-consistent numerical framework which incorporates both galaxies and MBHs. The high-resolution adaptive mesh refinement (AMR) code Enzo is modified to model the formation and feedback of molecular clouds at their characteristic scale of 15.2 pc and the accretion of gas onto a MBH. Two major channels of MBH feedback, radiative feedback (X-ray photons followed through full 3D adaptive ray tracing) and mechanical feedback (bipolar jets resolved in high-resolution AMR), are employed. We investigate the coevolution of a 9.2e11 Msun galactic halo and its 1e5 Msun embedded MBH at redshift 3 in a cosmological LCDM simulation. The MBH feedback heats the surrounding ISM up to 1e6 K through photoionization and Compton heating and locally suppresses star formation in the galactic inner core. The feedback considerably changes the stellar distribution there. This new channel of feedback from a slowly growing MBH is particularly interesting because it is only locally dominant, and does not require the heating of gas globally on the disk. The MBH also self-regulates its growth by keeping the surrounding ISM hot for an extended period of time.

astro-ph.GA↗

Dwarf Galaxies with Ionizing Radiation Feedback. I: Escape of Ionizing Photons

We describe a new method for simulating ionizing radiation and supernova feedback in the analogues of low-redshift galactic disks. In this method, which we call star-forming molecular cloud (SFMC) particles, we use a ray-tracing technique to solve the radiative transfer equation for ultraviolet photons emitted by thousands of distinct particles on the fly. Joined with high numerical resolution of 3.8 pc, the realistic description of stellar feedback helps to self-regulate star formation. This new feedback scheme also enables us to study the escape of ionizing photons from star-forming clumps and from a galaxy, and to examine the evolving environment of star-forming gas clumps. By simulating a galactic disk in a halo of 2.3e11 Msun, we find that the average escape fraction from all radiating sources on the spiral arms (excluding the central 2.5 kpc) fluctuates between 0.08% and 5.9% during a ~20 Myr period with a mean value of 1.1%. The flux of escaped photons from these sources is not strongly beamed, but manifests a large opening angle of more than 60 degree from the galactic pole. Further, we investigate the escape fraction per SFMC particle, f_esc(i), and how it evolves as the particle ages. We discover that the average escape fraction f_esc is dominated by a small number of SFMC particles with high f_esc(i). On average, the escape fraction from a SFMC particle rises from 0.27% at its birth to 2.1% at the end of a particle lifetime, 6 Myrs. This is because SFMC particles drift away from the dense gas clumps in which they were born, and because the gas around the star-forming clumps is dispersed by ionizing radiation and supernova feedback. The framework established in this study brings deeper insight into the physics of photon escape fraction from an individual star-forming clump, and from a galactic disk.

astro-ph.GA↗

Dwarf Galaxies with Ionizing Radiation Feedback. II: Spatially-resolved Star Formation Relation

We investigate the spatially-resolved star formation relation using a galactic disk formed in a comprehensive high-resolution (3.8 pc) simulation. Our new implementation of stellar feedback includes ionizing radiation as well as supernova explosions, and we handle ionizing radiation by solving the radiative transfer equation rather than by a subgrid model. Photoheating by stellar radiation stabilizes gas against Jeans fragmentation, reducing the star formation rate. Because we have self-consistently calculated the location of ionized gas, we are able to make spatially-resolved mock observations of star formation tracers, such as H-alpha emission. We can also observe how stellar feedback manifests itself in the correlation between ionized and molecular gas. Applying our techniques to the disk in a galactic halo of 2.3e11 Msun, we find that the correlation between star formation rate density (estimated from mock H-alpha emission) and molecular hydrogen density shows large scatter, especially at high resolutions of <~ 75 pc that are comparable to the size of giant molecular clouds (GMCs). This is because an aperture of GMC size captures only particular stages of GMC evolution, and because H-alpha traces hot gas around star-forming regions and is displaced from the molecular hydrogen peaks themselves. By examining the evolving environment around star clusters, we speculate that the breakdown of the traditional star formation laws of the Kennicutt-Schmidt type at small scales is further aided by a combination of stars drifting from their birthplaces, and molecular clouds being dispersed via stellar feedback.

astro-ph.GA↗

Formation of Globular Cluster Candidates in Merging Proto-galaxies at High Redshift: A View from the FIRE Cosmological Simulations

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypothesis of present-day metal-poor globular clusters. We find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ~> 1e5-6 Msun collectively to high density, at which point it rapidly turns into stars before stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical timescale, t_ff <~ 3 Myr, shorter than most stellar feedback timescales. Our simulation then allows us to trace how clusters could become virialized and tightly-bound to survive for up to ~420 Myr till the end of the simulation. Because the cluster's tightly-bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.

astro-ph.GA↗

The AGORA High-Resolution Galaxy Simulations Comparison Project. II: Isolated Disk Test

Using an isolated Milky Way-mass galaxy simulation, we compare results from 9 state-of-the-art gravito-hydrodynamics codes widely used in the numerical community. We utilize the infrastructure we have built for the AGORA High-resolution Galaxy Simulations Comparison Project. This includes the common disk initial conditions, common physics models (e.g., radiative cooling and UV background by the standardized package Grackle) and common analysis toolkit yt, all of which are publicly available. Subgrid physics models such as Jeans pressure floor, star formation, supernova feedback energy, and metal production are carefully constrained across code platforms. With numerical accuracy that resolves the disk scale height, we find that the codes overall agree well with one another in many dimensions including: gas and stellar surface densities, rotation curves, velocity dispersions, density and temperature distribution functions, disk vertical heights, stellar clumps, star formation rates, and Kennicutt-Schmidt relations. Quantities such as velocity dispersions are very robust (agreement within a few tens of percent at all radii) while measures like newly-formed stellar clump mass functions show more significant variation (difference by up to a factor of ~3). Systematic differences exist, for example, between mesh-based and particle-based codes in the low density region, and between more diffusive and less diffusive schemes in the high density tail of the density distribution. Yet intrinsic code differences are generally small compared to the variations in numerical implementations of the common subgrid physics such as supernova feedback. Our experiment reassures that, if adequately designed in accordance with our proposed common parameters, results of a modern high-resolution galaxy formation simulation are more sensitive to input physics than to intrinsic differences in numerical schemes.

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