arXiv subjects

Yangyao Chen

Publications and source records attributed to Yangyao Chen.

43 records · Page 3Linked to original sources

arXiv2021

MAHGIC: A Model Adapter for the Halo-Galaxy Inter-Connection

We develop a model to establish the interconnection between galaxies and their dark matter halos. We use Principal Component Analysis (PCA) to reduce the dimensionality of both the mass assembly histories of halos/subhalos and the star formation histories of galaxies, and Gradient Boosted Decision Trees (GBDT) to transform halo/subhalo properties into galaxy properties. We use two sets of hydrodynamic simulations to motivate our model architecture and to train the transformation. We then apply the two sets of trained models to dark matter only (DMO) simulations to show that the transformation is reliable and statistically accurate. The model trained by a high-resolution hydrodynamic simulation, or by a set of such simulations implementing the same physics of galaxy formation, can thus be applied to large DMO simulations to make "mock" copies of the hydrodynamic simulation. The model is both flexible and interpretable, which paves the way for future applications in which we will constrain the model using observations at different redshifts simultaneously and explore how galaxies form and evolve in dark matter halos empirically.

astro-ph.GA↗

arXiv2021

Finding proto-clusters to trace galaxy evolution: I. The finder and its performance

We develop a method to identify proto-clusters based on dark matter halos represented by galaxy groups selected from surveys of galaxies at high redshift. We test the performance of this method on halos in N-body simulations, and find it can correctly identify more than 85% of the true proto-clusters with $\gtrsim$ 95% purity and with mass estimates typical within 0.25 dex from their true values. We show how the information provided by the proto-clusters can be used to link galaxies in present-day clusters of galaxies with their high redshift progenitors. Our tests show that the proto-clusters identified by our method can recover reliably the progenitor stellar mass distribution of galaxies, thereby providing an avenue to investigate the formation and evolution of present-day galaxy clusters and their member galaxies.

astro-ph.GA↗

arXiv2021

How to empirically model star formation in dark matter halos: I. Inferences about central galaxies from numerical simulations

We use TNG and EAGLE hydrodynamic simulations to investigate the central galaxy - dark matter halo relations that are needed for a halo-based empirical model of star formation in galaxies. Using a linear dimension reduction algorithm and a model ensemble method, we find that for both star-forming and quenched galaxies, the star formation history (SFH) is tightly related to the halo mass assembly history (MAH). The quenching of a low-mass galaxy is mainly due to the infall-ejection process related to a nearby massive halo, while the quenching of a high-mass galaxy is closely related to the formation of a massive progenitor in its host halo. The classification of star-forming and quenched populations based solely on halo properties contains contamination produced by sample imbalance and overlapping distributions of the two populations. Guided by the results from hydrodynamic simulations, we build an empirical model to predict the SFH of central galaxies based on the MAH of their host halos, and we model the star-forming and quenched populations separately. Our model is based on the idea of adopting star formation templates from hydrodynamic simulations to reduce model complexity. We use various tests to demonstrate that the model can recover star formation histories of individual galaxies, and can statistically reproduce the galaxy bimodal distribution, stellar mass - halo mass and star formation rate - halo mass relations from low to high redshift, and assembly bias. Our study provides a framework of using hydrodynamic simulations to discover, and to motivate the use of, key ingredients to model galaxy formation using halo properties.

astro-ph.GA↗

arXiv2020

The Breakdown Scale of HI Bias Linearity

The 21 cm intensity mapping experiments promise to obtain the large-scale distribution of HI gas at the post-reionization epoch. In order to reveal the underlying matter density fluctuations from the HI mapping, it is important to understand how HI gas traces the matter density distribution. Both nonlinear halo clustering and nonlinear effects modulating HI gas in halos may determine the scale below which the HI bias deviates from linearity. We employ three approaches to generate the mock HI density from a large-scale N-body simulation at low redshifts, and demonstrate that the assumption of HI linearity is valid at the scale corresponding to the first peak of baryon acoustic oscillations, but breaks down at $k \gtrsim 0.1\,h\, {\rm Mpc}^{-1}$. The nonlinear effects of halo clustering and HI content modulation counteract each other at small scales, and their competition results in a model-dependent "sweet-spot" redshift near $z$=1 where the HI bias is scale-independent down to small scales. We also find that the linear HI bias scales approximately linearly with redshift for $z\le 3$.

astro-ph.CO↗

arXiv2020

Identifying galaxy groups at high redshift from incomplete spectroscopic data: I. The group finder and application to zCOSMOS

Identifying galaxy groups from redshift surveys of galaxies plays an important role in connecting galaxies with the underlying dark matter distribution. Current and future high-$z$ spectroscopic surveys, usually incomplete in redshift sampling, present both opportunities and challenges to identifying groups in the high-$z$ Universe. We develop a group finder that is based on incomplete redshift samples combined with photometric data, using a machine learning method to assign halo masses to identified groups. Test using realistic mock catalogs shows that $\gtrsim 90\%$ of true groups with halo masses $\rm M_h \gtrsim 10^{12} M_{\odot}/h$ are successfully identified, and that the fraction of contaminants is smaller than $10\%$. The standard deviation in the halo mass estimation is smaller than 0.25 dex at all masses. We apply our group finder to zCOSMOS-bright and describe basic properties of the group catalog obtained.

astro-ph.GA↗

arXiv2020

Relating the structure of dark matter halos to their assembly and environment

We use a large $N$-body simulation to study the relation of the structural properties of dark matter halos to their assembly history and environment. The complexity of individual halo assembly histories can be well described by a small number of principal components (PCs), which, compared to formation times, provide a more complete description of halo assembly histories and have a stronger correlation with halo structural properties. Using decision trees built with the random ensemble method, we find that about $60\%$, $10\%$, and $20\%$ of the variances in halo concentration, axis ratio, and spin, respectively, can be explained by combining four dominating predictors: the first PC of the assembly history, halo mass, and two environment parameters. Halo concentration is dominated by halo assembly. The local environment is found to be important for the axis ratio and spin but is degenerate with halo assembly. The small percentages of the variance in the axis ratio and spin that are explained by known assembly and environmental factors suggest that the variance is produced by many nuanced factors and should be modeled as such. The relations between halo intrinsic properties and environment are weak compared to their variances, with the anisotropy of the local tidal field having the strongest correlation with halo properties. Our method of dimension reduction and regression can help simplify the characterization of the halo population and clarify the degeneracy among halo properties.

astro-ph.GA↗

arXiv2018

ELUCID. VI: Cosmic variance of galaxy distribution in the local Universe

Halo merger trees are constructed from ELUCID, a constrained $N$-body simulation in the Sloan Digital Sky Survey (SDSS) volume. These merger trees are used to populate dark matter halos with galaxies according to an empirical model of galaxy formation. Mock catalogs in the SDSS sky coverage are constructed, which can be used to study the spatial distribution of galaxies in the low-$z$ Universe. These mock catalogs are used to quantify the cosmic variance in the galaxy stellar mass function (GSMF) measured from the SDSS survey. The GSMF estimated from the SDSS magnitude-limited sample can be affected significantly by the presence of the under-dense region at $z<0.03$, so that the low-mass end of the function can be underestimated significantly. Several existing methods designed to deal with the effects of the cosmic variance in the estimate of GSMF are tested, and none is found to be able to fully account for the cosmic variance. We propose a method based on the conditional stellar mass functions in dark matter halos, which can provide an unbiased estimate of the global GSMF. The application of the method to the SDSS data shows that the GSMF has a significant upturn at $M_*< 10^{9.5} h^{-1}{\rm M}_\odot$, which has been missed in many earlier measurements of the local GSMF.

astro-ph.GA↗