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Changhyun Cho

Publications and source records attributed to Changhyun Cho.

6 recordsLinked to original sources

Globular cluster abundance patterns inherited from giant molecular clouds

Globular clusters exhibit large star-to-star variations and anticorrelations in their light element abundances that are commonly interpreted in terms of in-cluster self-enrichment, in which ejecta from early-forming cluster stars pollute the gas from which later stars form over millions of years. Yet proposed self-enrichment scenarios suffer from a severe mass-budget problem or invoke exotic stellar populations. Using cosmological radiation-hydrodynamic simulations with a standard chemical enrichment model, we identify a population of giant molecular clouds whose internal abundance patterns reproduce several key globular cluster signatures: large light-element abundance spreads and nitrogen-oxygen anticorrelations at nearly constant iron abundance. These clouds form at the restart of star-formation activity after an earlier starburst, where previously ejected oxygen-rich gas collides with nitrogen-rich galactic gas, and are sites of dense star-cluster formation. In this picture, the chemical abundance patterns of globular clusters need not require extended in-cluster star formation, but can be inherited at birth from chemically structured interstellar gas shaped by the baryon cycle. Globular clusters therefore provide a fossil record of chemical enrichment and gas flows in high-redshift galaxies.

astro-ph.GA

Danger Zone: Establishing Buffers for Enhanced Classification in BPT Diagrams

This study utilizes unsupervised machine learning, specifically the uniform manifold approximation and projection (UMAP) algorithm, to classify optical spectra originating from star-forming regions, Seyferts, and low-ionization (nuclear) emission-line regions (LI(N)ERs) based on their line ratios. Typically, the ionization source of a region is determined from intensity ratio of different combinations of pairs of spectral lines. However, using current boundary definitions, $\sim10$\% of spectra change classes between diagnostic diagrams. We apply the machine learning technique to $\sim$1.3 million optical spectra from 6,439 galaxies observed in the MaNGA survey. By training UMAP on consistently classified data, we can classify these ``ambiguous'' spectra, and delineate boundary zones where such ambiguities arise. Furthermore, we identify physically interesting subsets within the ambiguous spectra. Future work will incorporate additional parameters, such as alternative emission line ratios and velocity dispersions, to enhance classification accuracy.

astro-ph.GA

A closer look at the origin of LINER emission and its connection to evolved stars with a machine learning classification scheme

Identifying the dominant ionizing sources in galaxies is essential for understanding their formation and evolution. Traditionally, spectra are classified based on their dominant ionizing source using strong emission lines and Baldwin, Phillips, \& Terlevich (BPT) diagrams. The ionizing source is traditionally determined by the emission line ratios using the BPT diagrams. Low-Ionization Nuclear Emission-line Regions (LINERs) are a class of ionizing mechanisms that is observationally identified but with a poorly understood origin, unlike the case of star forming regions and active galactic nuclei (AGN). LINERs, typically found in early-type galaxies, are often associated with low-luminosity AGN activity but may also be powered by aging stellar populations, particularly post-Asymptotic Giant Branch (p-AGB) stars. In this study, we employ a machine-learning-based encoder, Spender, to analyze the full MaNGA IFU spectra and identify key spectral features of LINERs. By examining the continuum and line emission of these spaxels, our approach aims to uncover hidden patterns and better understand the dominant ionizing sources. We show in this work that the neural network-based encoder was able identify LINER sources from the stellar continuum alone. The characteristics of the stellar population underlying LINER regions are consistent with evolved low mass stars implying that the source driving LINER emission is probably p-AGB stars rather than AGN activity.

astro-ph.GA

Causal Discovery in Astrophysics: Unraveling Supermassive Black Hole and Galaxy Coevolution

Correlation does not imply causation, but patterns of statistical association between variables can be exploited to infer a causal structure (even with purely observational data) with the burgeoning field of causal discovery. As a purely observational science, astrophysics has much to gain by exploiting these new methods. The supermassive black hole (SMBH)--galaxy interaction has long been constrained by observed scaling relations, that is low-scatter correlations between variables such as SMBH mass and the central velocity dispersion of stars in a host galaxy's bulge. This study, using advanced causal discovery techniques and an up-to-date dataset, reveals a causal link between galaxy properties and dynamically-measured SMBH masses. We apply a score-based Bayesian framework to compute the exact conditional probabilities of every causal structure that could possibly describe our galaxy sample. With the exact posterior distribution, we determine the most likely causal structures and notice a probable causal reversal when separating galaxies by morphology. In elliptical galaxies, bulge properties (built from major mergers) tend to influence SMBH growth, while in spiral galaxies, SMBHs are seen to affect host galaxy properties, potentially through feedback in gas-rich environments. For spiral galaxies, SMBHs progressively quench star formation, whereas in elliptical galaxies, quenching is complete, and the causal connection has reversed. Our findings support theoretical models of hierarchical assembly of galaxies and active galactic nuclei feedback regulating galaxy evolution. Our study suggests the potentiality for further exploration of causal links in astrophysical and cosmological scaling relations, as well as any other observational science.

astro-ph.GA

The dark balance: quantifying the inner halo response to active galactic nuclei feedback in galaxies

This paper presents a study of the impact of supermassive black hole (SMBH) feedback on dark matter (DM) halos in numerical NIHAO simulations of galaxies. In particular, the amount of DM displaced via active galactic nuclei (AGN) feedback and the physical scale over which AGN feedback affects the DM halo are quantified by comparing NIHAO simulations with and without AGN feedback. NIHAO galaxies with $\log(M_*/M_{\rm \odot})\geq 10.0$ show a growing central DM suppression of 0.2 dex (~40%) from z = 1.5 to the present relative to noAGN feedback simulations. The growth of the DM suppression is related to the mass evolution of the SMBH and the gas mass in the central regions. For the most massive NIHAO galaxies with $\log(M_*/M_{\rm \odot}) > 10.5$, partially affected by numerical resolution, the central DM suppression peaks at z = 0.5, after which halo contraction overpowers AGN feedback due a shortage of gas and, thus, SMBH growth. The spatial scale, or ``sphere of influence,'' over which AGN feedback affects the DM distribution decreases as a function of time for MW-mass galaxies (from ~16 kpc at z = 1.5 to ~7.8 kpc at z = 0) as a result of halo contraction due to stellar growth. For the most massive NIHAO galaxies, the size of the sphere of influence remains constant (~16 kpc) for z > 0.5 owing to the balance between AGN feedback and halo contraction.

astro-ph.GA

HELLO project: High-$z$ Evolution of Large and Luminous Objects

We present the High-$z$ Evolution of Large and Luminous Objects (HELLO) project, a set of $\sim\!30$ high-resolution cosmological simulations aimed to study Milky Way analogues ($M_\star\sim10^{10-11}$\,\Msun) at high redshift ($z\sim [2-4]$). Based on the Numerical Investigation of a Hundred Astrophysical Objects (NIHAO), HELLO features an updated scheme for chemical enrichment and the addition of local photoionization feedback. Independently of redshift and mass, our galaxies exhibit a smooth progression along the star formation main sequence until $M_\star \sim\!10^{10.5}$, around which our sample at $z \sim 4$ remains mostly unperturbed while the most massive galaxies at $z \sim 2$ reach their peak star formation rate (SFR) and its subsequent decline, due to a mix of gas consumption and stellar feedback. While AGN feedback remains subdominant with respect to stellar feedback for energy deposition, its localised nature likely adds to the physical processes leading to declining SFRs. The phase in which a galaxy in our mass range can be found at a given redshift is set by its gas reservoir and assembly history. Finally, our galaxies are in excellent agreement with various scaling relations observed with the \textit{Hubble Space Telescope} and the \textit{James Webb Space Telescope}, and hence can be used to provide the theoretical framework to interpret current and future observations from these facilities and shed light on the transition from star-forming to quiescent galaxies.

astro-ph.GA