arXiv subjects

Huiyuan Wang

Publications and source records attributed to Huiyuan Wang.

At least 55 records · Page 3Linked to original sources

arXiv2025

Measuring Mass of Gas in Central Galaxies using weak lensing and satellite kinematics in MOND

In Milgrom's modified Newtonian dynamics (MOND) framework, the dynamical mass of a galaxy is fully determined by its baryonic matter distribution. We fit the distribution of cold and hot gas halos, focusing on hot gas, around SDSS central galaxies using weak lensing signals from the DECaLS survey in MOND. The central galaxies are classified into two samples, the total galaxies and star-forming galaxies. We find that hot gas halo densities nearly follow Plummer's profile for both samples across all mass bins. The rotation curves of the galaxy samples are also demonstrated. The efficiency of converting gas into stars, $M_*/(M_* + M_{\rm g})$, is between 0.3 and 0.8 in all mass bins of the star-forming sample, which is higher than in the total sample. We also calculate gas mass using the satellite kinematics method in MOND. A constant, mildly radial anisotropy or isotropy in satellite motion leads to good agreement between the satellite kinematics and weak lensing methods. Combining both methods, we observe a baryonic mass to line-of-sight velocity dispersion of satellites ($M_{\rm b}$-$σ_{\rm s}$) relation. In addition, we examine more sophisticated models in MOND, including external field effects and Osipkov-Merritt anisotropy profiles, and find them unnecessary. A simple, mildly radial constant anisotropic model or an isotropic model, even when isolated, already aligns with observations. The strong concordance between the two methods suggests that weak lensing signals reliably measure the dynamical mass of central galaxies and can constrain the distribution of missing baryons in galaxy clusters.

astro-ph.GA↗

arXiv2025

The Three Hundred: Gas Properties Outside of Galaxy Cluster with the WHIM Contribution and Detection

We investigate the physical properties and detectability of warm-hot intergalactic medium (WHIM) gas with temperatures in the range $10^5<T<10^7$K around galaxy clusters using simulated galaxy clusters from The Three Hundred project. In simulations with different input physics (GIZMO-SIMBA and Gadget-X), we consistently find that the median gas temperature decreases to the WHIM upper bound, $10^7$K, at $\sim 2 \times R_{200c}$, while the WHIM mass fraction increases with radius until $\sim 3\times R_{200c}$, where it plateaus at $\sim 70$ per cent.By simulating X-ray emission from all gas components, we find that the WHIM contribution to the soft X-ray band (0.2 - 2.3 keV) increases with radius but eventually plateaus at larger distances. The differences between the two simulations become more pronounced at higher redshifts and larger radii. Finally, after accounting for observational effects, primarily by removing (sub)halos, we predict that the signal-to-noise ratio of the X-ray signal obtained by stacking the eRASS1 galaxy cluster catalogue will be $\sim 7$ for GIZMO-SIMBA and $\sim 21$ for Gadget-X.

astro-ph.CO↗

arXiv2025

The large-scale structure supplies the formation of gas-star misaligned galaxies

Using the integral field unit data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, we build a sample of gas-star misaligned galaxies. The large-scale environment of misaligned galaxies is dominated by filaments and clusters, while is less dense relative to the gas-star aligned control galaxies. The direction of the large-scale structure (LSS) is defined by its minor axis ($\vec{e_{3}}$), which indicates the slowest collapsing direction. For the aligned controls, the gas and stellar spins are preferentially perpendicular to $\vec{e_{3}}$, since these galaxies reside in high-mass host haloes. For the misaligned galaxies, the gas spins also tend to be perpendicular to $\vec{e_{3}}$, suggesting that misaligned gas is recently accreted from the LSS. Meanwhile, there is no correlation between their stellar spins and $\vec{e_{3}}$. There are two possible explanations for this observational phenomenon: (1) the large-scale environments of misaligned galaxies evolve as they grow, with stellar angular momenta acquiring in different environments having different orientations; (2) the correlation between stellar spins and the LSS is smeared out since a relatively higher portion of misaligned galaxies in sheet environments are statistically analysed together with those in filament environments.

astro-ph.GA↗

arXiv2025

Central Velocity Dispersion being the Primary Driver of Abundance Patterns in Quenched Galaxies

The element abundances of galaxies provide crucial insights into their formation and evolution. Using high-resolution IFU data from the MaNGA survey, we analyze the central spectra (0-0.5 $R_{\rm e}$) of 1,185 quenched galaxies ($z = 0.012-0.15$) to study their element abundances and stellar populations. We employ the full-spectrum fitting code {\tt alf} to derive stellar ages and element abundances from synthetic spectra and empirical libraries. Our key findings are: (1) Central velocity dispersion ($σ_*$) is the most effective parameter correlating with (relative) element abundances, especially [Na/Fe], [Mg/Fe], [C/Fe], and [N/Fe], outperforming $M_\ast$ and $M_\ast/R_{\rm e}$. (2) When binned by $σ_*$, the relative abundances of Na, Mg, C, and N remain stable across different formation times ($T_{\rm form}$), suggesting these elements are primarily influenced by the burstiness of star formation (traced by $σ_*$) rather than prolonged evolutionary processes. (3) Fe and Ca show little variation with $σ_*$, indicating weaker sensitivity to $σ_*$-driven processes. However, $T_{\rm form}$ has a global influence on all elements, contributing to their overall chemical evolution, albeit secondary to $σ_*$ for most elements. These results support the primary role of $σ_*$ in shaping the abundance patterns, likely stemming from the connection between central massive black holes and possibly dark matter halos, which influences the burstiness of star formation histories.

astro-ph.GA↗

arXiv2025

The circumgalactic medium traced by Mg II absorption with DESI: dependence on galaxy stellar mass, star formation rate and azimuthal angle

Understanding the circumgalactic medium (CGM) distribution of galaxies is the key to revealing the dynamical exchange of materials between galaxies and their surroundings. In this work, we use DESI EDR dataset to investigate the cool CGM of galaxies ($0.3 10.0$, the EW(Mg II) at the minor axis is largely suppressed with respect to low mass galaxies. This suggests that the competing processes, such as stellar feedback and gravity, play a key role in shaping the distribution of outflowing gas.

astro-ph.GA↗

arXiv2024

Ultra Diffuse Dwarf Galaxies Hosting Pseudo-bulges

By analyzing data from DESI Legacy Imaging Survey of the dwarf galaxies in the Arecibo Legacy Fast Alfa Survey, we have identified five ultra-diffuse galaxies (UDGs) featuring central pseudo-bulges. These UDGs display blue pseudo-bulges with Sérsic indices $n<2.5$ and effective radii spanning 300-700 pc, along with bluer thin stellar disks exhibiting low surface brightness and expansive effective radii that align with the UDG definition. The rotation velocities of these UDGs, determined using HI line widths and optical inclinations, exceed those of most dwarf galaxies of similar mass, suggesting the high halo spins or substantial dark matter halos. We propose that these UDGs likely formed through mergers of dwarf galaxies lacking old stars in their progenitors, resulting in the development of central bulge-like structures during starbursts triggered by the mergers, while also enhancing their halo spin. Subsequent gas accretion facilitated the formation of extended stellar disks. It is also worth noting the possibility that these UDGs could alternatively represent ``failed $L^{\star}$ galaxies'' with massive dark matter halos but reduced star formation efficiencies. If future high-resolution HI observations confirm the presence of massive halos around these UDGs, they may have formed due to intense AGN feedback in the early universe, and may be the descendants of ``little red dots'' observed by the James Webb Space Telescope, which are characterized by heightened central black hole masses and intensified accretion and feedback processes in the early universe.

astro-ph.GA↗

arXiv2024

Size Growth on Short Timescales of Star-Forming Galaxies: Insights from Size Variation with Rest-Frame Wavelength with JADES

We investigate size variation with rest-frame wavelength for star-forming galaxies based on the second JWST Advanced Deep Extragalactic Survey data release. Star-forming galaxies are typically smaller at longer wavelength from UV-to-NIR at $z<3.5$, especially for more massive galaxies, indicating the inside-out assembly with in-situ star formation if ignoring dust attenuation. The size variation with wavelength shows strong dependence on stellar mass, and shows little or no dependence on redshift, specific star formation rate and galaxy environment. This suggests that the size growth of star-forming galaxies is a self-regulated process primarily governed by stellar mass. We model size as a function of both mass and redshift simultaneously, obtaining $R_{\rm e} \propto M_*^{0.23} (1+z)^{-1.04}$ at a wavelength of 0.45 ${μ\mathrm{m}}$, and $R_{\rm e} \propto M_*^{0.20} (1+z)^{-1.08}$ at 1.0 ${μ\mathrm{m}}$. Based on this size evolution and the star formation main sequence from the literature, we obtain the locus of typical size growth for individual galaxies of different masses on the mass-size plane. The moving trend of galaxies on the mass-size plane, which indicates the slopes of their locus, strongly correlates with the size ratio between 0.45 ${μ\mathrm{m}}$ and 1.0 ${μ\mathrm{m}}$, supporting the idea that the size variation with wavelength provides important information on size growth of galaxies on short timescales.

astro-ph.GA↗

arXiv2024

Investigating the Impact of Model Complexity in Large Language Models

Large Language Models (LLMs) based on the pre-trained fine-tuning paradigm have become pivotal in solving natural language processing tasks, consistently achieving state-of-the-art performance. Nevertheless, the theoretical understanding of how model complexity influences fine-tuning performance remains challenging and has not been well explored yet. In this paper, we focus on autoregressive LLMs and propose to employ Hidden Markov Models (HMMs) to model them. Based on the HMM modeling, we investigate the relationship between model complexity and the generalization capability in downstream tasks. Specifically, we consider a popular tuning paradigm for downstream tasks, head tuning, where all pre-trained parameters are frozen and only individual heads are trained atop pre-trained LLMs. Our theoretical analysis reveals that the risk initially increases and then decreases with rising model complexity, showcasing a "double descent" phenomenon. In this case, the initial "descent" is degenerate, signifying that the "sweet spot" where bias and variance are balanced occurs when the model size is zero. Obtaining the presented in this study conclusion confronts several challenges, primarily revolving around effectively modeling autoregressive LLMs and downstream tasks, as well as conducting a comprehensive risk analysis for multivariate regression. Our research is substantiated by experiments conducted on data generated from HMMs, which provided empirical support and alignment with our theoretical insights.

cs.LG↗

arXiv2024

A two-phase model of galaxy formation: I. The growth of galaxies and supermassive black holes

We develop a model for galaxy formation and the growth of supermassive black holes (SMBHs), based on the fact that cold dark matter (CDM) halos form their gravitational potential wells through a fast phase with rapid change in the potential, and that the high universal baryon fraction makes cooled gas in halos self-gravitating and turbulent before it can form rotation-supported disks. Gas fragmentation produces sub-clouds so dense that cloud-cloud collision and drag on clouds are not significant, producing a dynamically hot system of sub-clouds that form stars and move ballistically to feed the central SMBH. Active galactic nucleus (AGN) and supernova (SN) feedback is effective only in the fast phase, and the cumulative effects are to regulate star formation and SMBH growth, as well as to reduce the amount of cold gas in halos to allow the formation of globally stable disks. Using a set of halo assembly histories, we demonstrate that the model can reproduce a number of observations, including correlations among SMBH mass, stellar mass of galaxies and halo mass, the number densities of galaxies and SMBH, as well as their evolution over the cosmic time.

astro-ph.GA↗

arXiv2024

A two-phase model of galaxy formation: II. The size-mass relation of dynamically hot galaxies

In Paper-I we developed a two-phase model to connect dynamically hot galaxies (such as ellipticals and bulges) with the formation of self-gravitating gas clouds (SGCs) associated with the fast assembly of dark matter halos. Here we explore the implications of the model for the size-stellar mass relation of dynamically hot galaxies. Star-forming sub-clouds resulting from the fragmentation of the turbulent SGC inherit its spatial structure and dynamical hotness, producing a `homologous' relation, $r_{\rm f}\approx\, 100 r_{\rm bulge}$, between the size of a dynamically hot galaxy ($r_{\rm bulge}$) and that of its host halo assembled in the fast regime ($r_{\rm f}$), independent of redshift and halo mass. This relation is preserved by the `dry' expansion driven by dynamical heating when a galaxy becomes gas-poor due to inefficient cooling, and is frozen due to the stop of bulge growth during the slow assembly regime of the halo. The size-stellar mass relation is thus a simple combination of the galaxy-halo homology and the non-linear stellar mass-halo mass relation. Using a set of halo assembly histories we reproduce all properties in the observed size-mass relation of dynamically hot galaxies, including the flattening in the low-mass end and the upturn in the massive end. The prediction matches observational data currently available to $z \approx 4$, and can be tested in the future at higher $z$. Our results indicate that the sizes of dynamically hot galaxies are produced by the dissipation and collapse of gas in halos to establish SGCs in which stars form.

astro-ph.GA↗

arXiv2024

A Statistical Theory of Regularization-Based Continual Learning

We provide a statistical analysis of regularization-based continual learning on a sequence of linear regression tasks, with emphasis on how different regularization terms affect the model performance. We first derive the convergence rate for the oracle estimator obtained as if all data were available simultaneously. Next, we consider a family of generalized $\ell_2$-regularization algorithms indexed by matrix-valued hyperparameters, which includes the minimum norm estimator and continual ridge regression as special cases. As more tasks are introduced, we derive an iterative update formula for the estimation error of generalized $\ell_2$-regularized estimators, from which we determine the hyperparameters resulting in the optimal algorithm. Interestingly, the choice of hyperparameters can effectively balance the trade-off between forward and backward knowledge transfer and adjust for data heterogeneity. Moreover, the estimation error of the optimal algorithm is derived explicitly, which is of the same order as that of the oracle estimator. In contrast, our lower bounds for the minimum norm estimator and continual ridge regression show their suboptimality. A byproduct of our theoretical analysis is the equivalence between early stopping and generalized $\ell_2$-regularization in continual learning, which may be of independent interest. Finally, we conduct experiments to complement our theory.

cs.LG↗

arXiv2024

ELUCID VIII: Simulating the Coma Galaxy Cluster to Calibrate Model and Understand Feedback

We conducted an investigation of the Coma cluster of galaxies by running a series of constrained hydrodynamic simulations with GIZMO-SIMBA and GADGET-3, based on initial conditions reconstructed from the SDSS survey volume in the ELUCID project. We compared simulation predictions and observations for galaxies, ICM and IGM in and around the Coma cluster to constrain galaxy formation physics. Our results demonstrate that this type of constrained investigation allows us to probe in more detail the implemented physical processes, because the comparison between simulations and observations is free of cosmic variance and hence can be conducted in a ''one-to-one'' manner. We found that an increase in the earlier star formation rate and the supernova feedback of the original GIZMO-SIMBA model is needed to match observational data on stellar, ISM and ICM metallicity. The simulations without AGN feedback can well reproduce the observational ICM electron density, temperature, and entropy profiles, ICM substructures, and the IGM temperature-density relation, while the ones with AGN feedback usually fail. However, one requires something like AGN feedback to reproduce a sufficiently large population of quiescent galaxies, particularly in low-density regions. The constrained simulations of the Coma cluster thus provide a test bed to understand processes that drive galaxy formation and evolution.

astro-ph.GA↗

arXiv2024

CARE: Large Precision Matrix Estimation for Compositional Data

High-dimensional compositional data are prevalent in many applications. The simplex constraint poses intrinsic challenges to inferring the conditional dependence relationships among the components forming a composition, as encoded by a large precision matrix. We introduce a precise specification of the compositional precision matrix and relate it to its basis counterpart, which is shown to be asymptotically identifiable under suitable sparsity assumptions. By exploiting this connection, we propose a composition adaptive regularized estimation (CARE) method for estimating the sparse basis precision matrix. We derive rates of convergence for the estimator and provide theoretical guarantees on support recovery and data-driven parameter tuning. Our theory reveals an intriguing trade-off between identification and estimation, thereby highlighting the blessing of dimensionality in compositional data analysis. In particular, in sufficiently high dimensions, the CARE estimator achieves minimax optimality and performs as well as if the basis were observed. We further discuss how our framework can be extended to handle data containing zeros, including sampling zeros and structural zeros. The advantages of CARE over existing methods are illustrated by simulation studies and an application to inferring microbial ecological networks in the human gut.

stat.ME↗

arXiv2024

Black-Hole-to-Halo Mass Relation From UNIONS Weak Lensing

This letter presents, for the first time, direct constraints on the black-hole-to-halo-mass relation using weak gravitational lensing measurements. We construct type I and type II Active Galactic Nuclei (AGNs) samples from the Sloan Digital Sky Survey (SDSS), with a mean redshift of 0.4 0.1 for type I (type II) AGNs. This sample is cross-correlated with weak lensing shear from the Ultraviolet Near Infrared Northern Survey (UNIONS). We compute the excess surface mass density of the halos associated with $36,181$ AGNs from $94,308,561$ lensed galaxies and fit the halo mass in bins of black-hole mass. We find that more massive AGNs reside in more massive halos. We see no evidence of dependence on AGN type or redshift in the black-hole-to-halo-mass relationship when systematic errors in the measured black-hole masses are included. Our results are consistent with previous measurements for non-AGN galaxies. At a fixed black-hole mass, our weak-lensing halo masses are consistent with galaxy rotation curves, but significantly lower than galaxy clustering measurements. Finally, our results are broadly consistent with state-of-the-art hydro-dynamical cosmological simulations, providing a new constraint for black-hole masses in simulations.

astro-ph.GA↗

arXiv2024

Characterizing the assembly of dark matter halos with protohalo size histories: I. Redshift evolution, relation to descendant halos, and halo assembly bias

We propose a novel method to quantify the assembly histories of dark matter halos with the redshift evolution of the mass-weighted spatial variance of their progenitor halos, i.e. the protohalo size history. We find that the protohalo size history for each individual halo at z~0 can be described by a double power-law function. The amplitude of the fitting function strongly correlates to the central-to-total stellar mass ratios of descendant halos. The variation of the amplitude of the protohalo size history can induce a strong halo assembly bias effect for massive halos. This effect is detectable in observation using the central-to-total stellar mass ratio as a proxy of the protohalo size. The correlation to the descendant central-to-total stellar mass ratio and the halo assembly bias effect seen in the protohalo size are much stronger than that seen in the commonly adopted half-mass formation time derived from the mass accretion history. This indicates that the information loss caused by the compression of halo merger trees to mass accretion histories can be captured by the protohalo size history. Protohalo size thus provides a useful quantity to connect protoclusters across cosmic time and to link protoclusters with their descendant clusters in observations.

astro-ph.GA↗

arXiv2023

Coreset selection can accelerate quantum machine learning models with provable generalization

Quantum neural networks (QNNs) and quantum kernels stand as prominent figures in the realm of quantum machine learning, poised to leverage the nascent capabilities of near-term quantum computers to surmount classical machine learning challenges. Nonetheless, the training efficiency challenge poses a limitation on both QNNs and quantum kernels, curbing their efficacy when applied to extensive datasets. To confront this concern, we present a unified approach: coreset selection, aimed at expediting the training of QNNs and quantum kernels by distilling a judicious subset from the original training dataset. Furthermore, we analyze the generalization error bounds of QNNs and quantum kernels when trained on such coresets, unveiling the comparable performance with those training on the complete original dataset. Through systematic numerical simulations, we illuminate the potential of coreset selection in expediting tasks encompassing synthetic data classification, identification of quantum correlations, and quantum compiling. Our work offers a useful way to improve diverse quantum machine learning models with a theoretical guarantee while reducing the training cost.

quant-ph↗

arXiv2023

Halo mass-observable proxy scaling relations and their dependencies on galaxy and group properties

Based on the DECaLS shear catalog, we study the scaling relations between halo mass($M_{\rm h}$) and various proxies for SDSS central galaxies, including stellar mass($M_*$), stellar velocity dispersion($σ_*$), abundance matching halo mass($M_{\rm AM}$) and satellite velocity dispersion($σ_{\rm s}$), and their dependencies on galaxy and group properties. In general, these proxies all have strong positive correlations with $M_{\rm h}$, consistent with previous studies. We find that the $M_{\rm h}$-$M_*$ and $M_{\rm h}$-$σ_*$ relations depend strongly on group richness($N_{\rm sat}$), while the $M_{\rm h}$-$M_{\rm AM}$ and $M_{\rm h}$-$σ_{\rm s}$ relations are independent of it. Moreover, the dependence on star formation rate(SFR) is rather weak in the $M_{\rm h}$-$σ_*$ and $M_{\rm h}$-$σ_{\rm s}$ relations, but very prominent in the other two. $σ_{\rm s}$ is thus the best proxy among them, and its scaling relation is in good agreement with hydro-dynamical simulations. However, estimating $σ_{\rm s}$ accurately for individual groups/clusters is challenging because of interlopers and the requirement for sufficient satellites. We construct new proxies by combining $M_*$, $σ_*$, and $M_{\rm AM}$, and find the proxy with 30\% contribution from $M_{\rm AM}$ and 70\% from $σ_*$ can minimize the dependence on $N_{\rm sat}$ and SFR. We obtain the $M_{\rm h}$-supermassive black hole(SMBH) mass relation via the SMBH scaling relation and find indications for rapid and linear growth phases for SMBH. We also find that correlations among $M_{\rm h}$, $M_*$ and $σ_*$ change with $M_*$, indicating that different processes drive the growth of galaxies and SMBH at different stages.

astro-ph.GA↗

arXiv2023

A Conditional Abundance Matching Method of Extending Simulated Halo Merger Trees to Resolve Low-Mass Progenitors and Sub-halos

We present an algorithm to extend subhalo merger trees in a low-resolution dark-matter-only simulation by conditionally matching them to those in a high-resolution simulation. The algorithm is general and can be applied to simulation data with different resolutions using different target variables. We instantiate the algorithm by a case in which trees from ELUCID, a constrained simulation of $(500h^{-1}{\rm Mpc})^3$ volume of the local universe, are extended by matching trees from TNGDark, a simulation with much higher resolution. Our tests show that the extended trees are statistically equivalent to the high-resolution trees in the joint distribution of subhalo quantities and in important summary statistics relevant to modeling galaxy formation and evolution in halos. The extended trees preserve certain information of individual systems in the target simulation, including properties of resolved satellite subhalos, and shapes and orientations of their host halos. With the extension, subhalo merger trees in a cosmological scale simulation are extrapolated to a mass resolution comparable to that in a higher-resolution simulation carried out in a smaller volume, which can be used as the input for (sub)halo-based models of galaxy formation. The source code of the algorithm, and halo merger trees extended to a mass resolution of $\sim 2 \times 10^8 h^{-1}M_\odot$ in the entire ELUCID simulation, are available.

astro-ph.GA↗