arXiv subjects

Huiyuan Wang

Publications and source records attributed to Huiyuan Wang.

At least 37 records · Page 2Linked to original sources

arXiv2026

Updated Metallicity Diagnostics for Precision Oxygen Abundance Measurements in High-redshift Galaxies with JWST

Recent work has demonstrated that widely used strong-line oxygen abundance indicators, such as O3N2, $\rm R23$, and $\widehat{\rm R}$, suffer from large uncertainties when applied to high-redshift galaxies. We show that this loss of precision primarily arises because, at fixed \Oabund, galaxies span a wide dynamic range in ionization parameter and nitrogen enrichment. Here we develop updated indicators that explicitly incorporate both effects via the proxies O32 and N2O2. We define ${\rm R}_{\rm u}\equiv \rm R23+α_1 O32+α_2 N2O2$, $\widehat{\rm R}_{\rm u}\equiv \rm \widehat{R}+β_1 O32+β_2 N2O2$, and ${\rm O}_{\rm u}\equiv \rm O3N2+γ_1 O32+γ_2 N2O2$, and calibrate \Oabund~as low-order polynomials in each composite indicator. Applied to a JWST sample with $T_{\rm e}$-method abundances, the updated indicators substantially tighten the correlations with \Oabund, boosting adjusted coefficients of determination from $\mathbb{R}^2\lesssim 0$ (classical indicators) to $\mathbb{R}^2\gtrsim 0.5$ for the full sample and to $\sim 0.7$ at $z>2$. The residuals reveal a redshift evolution in the mapping between \Oabund, strong lines, ionization, and nitrogen enrichment, with a pivotal turning point near the cosmic noon ($z\sim 2$). Our calibrations provide a practical, physically grounded path to precise metallicity measurements in the JWST era and a firmer basis for quantifying early chemical enrichment and feedback.

astro-ph.GA↗

arXiv2026

Radio AGN feedback sustains quiescence only in a minority of massive galaxies

Radio active galactic nuclei (AGNs) eject a huge amount of energy into the surrounding medium and are thought to potentially prevent gas cooling and maintain the quiescence of massive galaxies. The short-lived, sporadic, and anisotropic nature of radio activities, coupled with the detection of abundant cold gas around some massive quiescent galaxies, raise questions about the efficiency of radio feedback in massive galaxies. Here we present an innovative method rooted in artificial intelligence to separate galaxies in which radio feedback is effective (RFE), regardless of current radio emission, from those in which radio feedback is ineffective (RFI), according to their optical images. Galaxies categorized as RFE are all dynamically hot, whereas quiescent RFI (RFI-Q) galaxies usually have extended cold-disk components. At given stellar mass, dark matter halos hosting RFE galaxies are between four to ten times more massive than those of RFI-Q galaxies. We find, for the first time, that almost all RFE galaxies have scant cold gas, irrespective of AGN activity. In contrast, many RFI-Q galaxies are surrounded by substantial amounts of condensed atomic gas, indicating a different evolutionary path from RFE galaxies. Our finding provides direct and compelling evidence that a radio AGN has gone through about 300 on-off cycles and that radio feedback can prevent gas cooling over a timescale much longer than that of radio activity. Contrary to general belief, our analysis shows that only a small fraction of massive galaxies are influenced by strong radio AGNs, suggesting that current galaxy formation models need serious revision.

astro-ph.GA↗

arXiv2025

Surrogate-Powered Inference: Regularization and Adaptivity

High-quality labeled data are essential for reliable statistical inference, but are often limited by validation costs. While surrogate labels provide cost-effective alternatives, their noise can introduce non-negligible bias. To address this challenge, we propose the surrogate-powered inference (SPI) toolbox, a unified framework that leverages both the validity of high-quality labels and the abundance of surrogates to enable reliable statistical inference. SPI comprises three progressively enhanced versions. Base-SPI integrates validated labels and surrogates through augmentation to improve estimation efficiency. SPI+ incorporates regularized regression to safely handle multiple surrogates, preventing performance degradation due to error accumulation. SPI++ further optimizes efficiency under limited validation budgets through an adaptive, multiwave labeling procedure that prioritizes informative subjects for labeling. Compared to traditional methods, SPI substantially reduces the estimation error and increases the power in risk factor identification. These results demonstrate the value of SPI in improving the reproducibility. Theoretical guarantees and extensive simulation studies further illustrate the properties of our approach.

stat.ME↗

arXiv2025

Warped Disk Galaxies: Statistical Properties from DESI Legacy Imaging Surveys DR8

Warped structures are often observed in disk galaxies, yet their physical origin is still under investigation. We present a systematic study of warped edge-on disk galaxies based on imaging data from the DESI Legacy Imaging Surveys DR8, with the expectation that this large sample size, enabled by wide-area surveys, will offer new perspectives on the formation of disk warps. Using a deep learning approach, we trained an EfficientNet-B3 convolutional neural network to classify the morphology of edge-on-disk galaxies into warped and non-warped categories. Our model was trained on a curated and visually verified set of labeled galaxy images and applied to a large dataset of over 595,651 edge-on disk galaxies selected from the Galaxy Zoo DESI catalog. Our results provide the largest warp catalog to date, consisting of 23996 warped edge-on disk galaxies, and reveal statistical trends between warp occurrence and galaxy properties. Compared to their non-warped counterparts, these warped disk galaxies tend to have bluer colors, lower stellar masses, higher gas fractions and star-formation rates, smaller Sérsic indices and larger disk sizes. In addition, warped disk galaxies show higher projected number densities of neighboring galaxies than their non-warped counterparts, particularly within $ R_{\mathrm{proj}} \lesssim 50~\mathrm{kpc} $, where the local number density is roughly twice as high.

astro-ph.GA↗

arXiv2025

Obtaining Accurate Ground-State Properties on Near-term Quantum Devices

Accurate ground-state calculations on noisy quantum computers are fundamentally limited by restricted ansatz expressivity and unavoidable hardware errors. We introduce a hybrid-quantum classical framework that simultaneously addresses these challenges. Our method systematically purifies noisy two electron reduced density matrices from quantum devices by enforcing N-representability conditions through efficient semidefinite programming, guided by a norm-based distance constraint to the experimental data. To implement this constraint, we develop a hardware efficient calibration protocol based on Clifford circuits. We demonstrate near full configuration interaction accuracy for ground-state energies of H2, LiH, and H4, and compute precise scattering intensities for C6H8 on noisy hardware. This approach surpasses conventional methods by simultaneously overcoming both ansatz limitations and hardware noise, establishing a scalable route to quantum advantage and marking a critical step toward reliable simulations of complex molecularnsystems on noisy devices.

quant-ph↗

arXiv2025

The Bigfoot: A footprint of a Coma cluster progenitor at z=3.98

Protoclusters, galaxy clusters' high redshift progenitors, hold the keys to understanding the formation and evolution of clusters and their member galaxies. However, their cosmological distances and spatial extensions (tens of Mpc) have inhibited complete mapping of their structure and constituent galaxies, which is key to robustly linking protoclusters to their descendants. Here we report the discovery of the Bigfoot, a tridimensional structure at $z = 3.98$ including 11 subgroups traced by 55 (700) spectroscopic (photometric) redshifts with JWST, extending over $15\times 37$ $\times 49{\rm{cMpc^3}}$ in the PRIMER-UDS field. Bigfoot's large-scale and mass function of member galaxies closely match constrained simulations' predictions for the progenitors of today's most massive clusters (${M_0} > 10^{15} {M_{_ \odot }}$). All subgroups with ${M_{\rm{h}}} > {10^{12.5}}{M_{_ \odot }}$ exhibit enhanced fractions of massive galaxies ($>{10^{10.0} {M_{_ \odot }}}$) compared to lower-mass halos and the field, demonstrating the accelerated formation of massive galaxies in massive halos. The presence of this massive protocluster with a large central halo (${10^{13.0} {M_{_ \odot }}}$) in a JWST deep field bears important cosmological implication that favors high ${σ_8}$ of PLANCK cosmology over low-redshift probes.

astro-ph.GA↗

arXiv2025

Collaborative Indirect Treatment Comparisons with Multiple Distributed Single-arm Trials

When randomized controlled trials are impractical or unethical to simultaneously compare multiple treatments, indirect treatment comparisons using single-arm trials offer valuable evidence for health technology assessments, especially for rare diseases and early-phase drug development. In practice, each sponsor conducts a single-arm trial on its own drug with restricted data-sharing and targets effects in its trial population, which can lead to unfair comparisons. This motivates methods for fair treatment comparisons across a range of target populations in distributed networks of single-arm trials sharing only aggregated data. Existing federated methods, which assume at least one site contains all treatments and allow pooling of treatment groups within the same site, cannot address this problem. We propose a novel distributed augmented calibration weighting (DAC) method to simultaneously estimate the pairwise average treatment effects (ATEs) across all trial population combinations in a distributed network of multiple single-arm trials. Using two communication rounds, DAC estimators balance covariates via calibration weighting, incorporate flexible nuisance parameter estimation, achieve doubly robust consistency, and yield results identical to pooled-data analysis. When nuisance parameters are estimated parametrically, DAC estimators are enhanced to achieve doubly robust inference with minimal squared first-order asymptotic bias. Simulations and a real-data application show good performance.

stat.ME↗

arXiv2025

Mass stratification in the globular cluster system revealing the assembly history of the nearest S0 galaxy NGC 3115

Galaxy formation and evolution is hierarchical. The most massive galaxies are thought to form their central regions early through violent dissipational processes, then grow inside-out by accreting smaller satellites. While widely supported, direct observational confirmation of this process in individual galaxies remains lacking, except for the Milky Way. We present a detailed analysis of globular cluster (GC) candidates within a $70^\prime$ ($\sim190$ kpc) radius around the nearest S0 galaxy, NGC 3115, using images in \textit{g,r,z} bands from the DESI Legacy Imaging Surveys and data from Gaia. We report the discovery of mass stratification in the GC system (GCS), evident in two ways: first, the effective radius of the GCS increases monotonically from the bright to faint end, up to the detection limit near the turnover magnitude of the GC luminosity function (GCLF); second, the GCLF shows fainter turnover magnitudes and smaller standard deviations at larger galactocentric radii. This stratification cannot be readily explained by radial migration or tidal dissolution, but most likely reflects the hierarchical assembly of NGC 3115's stellar halo, with later-accreted satellites deposited across broader galactocentric distances. This interpretation is supported by cosmological simulations of subhalos with comparable mass and bulge-to-total mass ratios and is consistent with the negative color gradients observed in the GCS. Additionally, we identify several substructures within the GCS, indicating ongoing assembly of NGC 3115. This work highlights the power of GCS as tracers of galaxy assembly and sets the stage for upcoming space-based wide-field imaging surveys to constrain the assembly of massive galaxies.

astro-ph.GA↗

arXiv2025

DarkAI: Reconstructing the density, velocity and tidal field of dark matter from a DESI-like bright galaxy sample

Reconstructing the mass density, velocity, and tidal (MTV) fields of dark matter from galaxy surveys is essential for advancing our understanding of the LSS of the Universe. In this work, we present a machine learning-based framework using a UNet convolutional neural network to reconstruct the MTV fields from mock samples of the DESI bright galaxy survey within the redshift range $0.1 < z < 0.4$. Our approach accounts for realistic observational effects, including geometric selection, flux-limited data, and redshift space distortion (RSD) effects, thereby improving the fidelity of the reconstructed fields. Testing on mock galaxy catalogs generated from the Jiutian N-body simulation, our method achieves significant accuracy level. The reconstructed density field exhibits strong consistency with the true field, effectively eliminating most RSD effects and achieving a cross-correlation power spectrum coefficient greater than 0.985 on scales with $k < 0.1 \, h \, \mathrm{Mpc}^{-1}$. The velocity field reconstruction accurately captures large-scale coherent flows and small-scale turbulent features, exhibiting slopes of grid-to-grid relationships close to unity and scatter below $\sim$100 $\mathrm{km} \, \mathrm{s}^{-1}$. Additionally, the tidal field is reconstructed without bias, successfully recovering the features of the large-scale cosmic web, including clusters, filaments, sheets, and voids. Our results confirm that the proposed framework effectively captures the large-scale distribution and dynamics of dark matter while addressing key systematic challenges. These advancements provide a reliable and robust tool for analyzing current and future galaxy surveys, paving the way for new insights into cosmic structure formation and evolution.

astro-ph.CO↗

arXiv2025

Physical Processes Behind the Co-Evolution of Halos, Galaxies and Supermassive Black Holes in the IllustrisTNG Simulation

We explore the co-evolution of dark matter halos, their central galaxies, and central supermassive black holes (SMBHs) using the IllustrisTNG (TNG) simulation. We find that the evolutionary histories of individual galaxies in the $M_{\rm BH}$-$M_*$ plane can be decomposed into four distinct phases, separated by three transition points. We identify the driving processes of galaxy evolution within each phase and derive the conditions necessary and sufficient for transitions to subsequent phases. The first phase is dominated by star formation, with its duration primarily determined by the mass of the SMBH seed and the surrounding gas environment. The second phase is characterized by rapid SMBH growth, and the transition to the next phase occurs when the thermal-mode feedback of active galactic nucleus (AGN) can unbind gas from the galaxy. The third phase involves self-regulation of the SMBH, and the transition to the quenched phase occurs when the kinetic-mode feedback of AGN counterbalances gas cooling within the subhalo. The final phase is dominated by mergers. We investigate the use of scaling relations among different mass components and evolutionary phases to understand processes implemented in TNG and other simulations, and discuss how current and forthcoming observations can be used to constrain models.

astro-ph.GA↗

arXiv2025

Robust Detection of Watermarks for Large Language Models Under Human Edits

Watermarking has offered an effective approach to distinguishing text generated by large language models (LLMs) from human-written text. However, the pervasive presence of human edits on LLM-generated text dilutes watermark signals, thereby significantly degrading detection performance of existing methods. In this paper, by modeling human edits through mixture model detection, we introduce a new method in the form of a truncated goodness-of-fit test for detecting watermarked text under human edits, which we refer to as Tr-GoF. We prove that the Tr-GoF test achieves optimality in robust detection of the Gumbel-max watermark in a certain asymptotic regime of substantial text modifications and vanishing watermark signals. Importantly, Tr-GoF achieves this optimality \textit{adaptively} as it does not require precise knowledge of human edit levels or probabilistic specifications of the LLMs, in contrast to the optimal but impractical (Neyman--Pearson) likelihood ratio test. Moreover, we establish that the Tr-GoF test attains the highest detection efficiency rate in a certain regime of moderate text modifications. In stark contrast, we show that sum-based detection rules, as employed by existing methods, fail to achieve optimal robustness in both regimes because the additive nature of their statistics is less resilient to edit-induced noise. Finally, we demonstrate the competitive and sometimes superior empirical performance of the Tr-GoF test on both synthetic data and open-source LLMs in the OPT and LLaMA families.

stat.ME↗

arXiv2025

A Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules

Since ChatGPT was introduced in November 2022, embedding (nearly) unnoticeable statistical signals into text generated by large language models (LLMs), also known as watermarking, has been used as a principled approach to provable detection of LLM-generated text from its human-written counterpart. In this paper, we introduce a general and flexible framework for reasoning about the statistical efficiency of watermarks and designing powerful detection rules. Inspired by the hypothesis testing formulation of watermark detection, our framework starts by selecting a pivotal statistic of the text and a secret key -- provided by the LLM to the verifier -- to enable controlling the false positive rate (the error of mistakenly detecting human-written text as LLM-generated). Next, this framework allows one to evaluate the power of watermark detection rules by obtaining a closed-form expression of the asymptotic false negative rate (the error of incorrectly classifying LLM-generated text as human-written). Our framework further reduces the problem of determining the optimal detection rule to solving a minimax optimization program. We apply this framework to two representative watermarks -- one of which has been internally implemented at OpenAI -- and obtain several findings that can be instrumental in guiding the practice of implementing watermarks. In particular, we derive optimal detection rules for these watermarks under our framework. These theoretically derived detection rules are demonstrated to be competitive and sometimes enjoy a higher power than existing detection approaches through numerical experiments.

math.ST↗

arXiv2025

Efficient Semiparametric Inference for Distributed Data with Blockwise Missingness

We consider statistical inference for a finite-dimensional parameter in a regular semiparametric model under a distributed setting with blockwise missingness, where entire blocks of variables are unavailable at certain sites and sharing individual-level data is not allowed. To improve efficiency of the internal study, we propose a class of augmented one-step estimators that incorporate information from external sites through ``transfer functions.'' The proposed approach has several advantages. First, it is communication-efficient, requiring only one-round communication of summary-level statistics. Second, it satisfies a do-no-harm property in the sense that the augmented estimator is no less efficient than the original one based solely on the internal data. Third, it is statistically optimal, achieving the semiparametric efficiency bound when the transfer function is appropriately estimated from data. Finally, it is scalable, remaining asymptotically normal even when the number of external sites and the data dimension grow exponentially with the internal sample size. Simulation studies confirm both the statistical efficiency and computational feasibility of our method in distributed settings.

stat.ME↗

arXiv2025

A two-phase model of galaxy formation: III. The formation of globular clusters

We develop a model of globular cluster (GC) formation within the cosmological hierarchy of structure formation. The model is rooted in the `two-phase' scenario of galaxy formation developed in Paper-I, where the fast accretion of dark matter halos at high redshift leads to the formation of self-gravitating, turbulent gas clouds that subsequently fragment into dynamically hot systems of dense sub-clouds with masses $\sim 10^6$--$10^7 {\rm M}_\odot$. Here we elaborate on the formation, evolution, and fate of these sub-clouds, and show that some of the sub-clouds can be compactified via two distinctive channels into a `supernova-free' regime to form two distinct populations of GCs. The model is simple, characterized by a small number of free parameters underpinned by physical considerations, and can be efficiently implemented into cosmological N-body simulations to generate a coherent sample of halos, galaxies, and GCs. Calibrated with observations, our model can reproduce a range of observational statistics, including those for GC masses, sizes, metallicities, spatial distributions, and the relation of GC systems with host galaxies/halos. Significant discrepancies between model results and existing observations are discussed in connection to processes implemented in the model. Predictions for GCs are made for both the local Universe and for redshift up to $z \approx 10$, and can be tested by upcoming observations.

astro-ph.GA↗

arXiv2025

The Cosmic Evolution and Spatial Distribution of Multiphase Gas associated with QSOs

We investigate the multi-phase gas surrounding QSOs traced by 33 absorption lines (e.g., Ly$α$, C\,\textsc{iv}, Fe\,\textsc{ii}, Mg\,\textsc{ii}, etc.) in the stacked spectra of background sources, using the early data release from the Dark Energy Spectroscopic Instrument. Our analysis reveals that the equivalent width ($ W $) of metal absorption lines decreases with increasing redshift, following an overall trend described by $W \propto (1+z)^{-4.0\pm 2.7}$. Different species that trace multi-phases of QSO-associated gas exhibit distinct evolutionary patterns. Additionally, the $ W $ of these absorption lines decreases with distance ($D$) from QSOs, which can be effectively characterized by a two-halo model. Compared to the projected two point correlation function of galaxies at similar redshifts, low-ionization ions exhibit similar clustering scales, while high-ionization ions show a significantly more extended spatial distribution. We also find that $W_{\text{FeII}}/W_{\text{MgII}}$ increases towards lower redshifts, which can be attributed to evolving star formation histories and/or changes in initial mass function for galaxies. By leveraging multiple absorption tracers, we conduct the first comprehensive investigation of diffuse, multiphase gas from the circumgalactic medium to cosmological scales, offering new insights into baryon cycles and the transport of metals throughout cosmic time.

astro-ph.GA↗

arXiv2025

The Internal Kinematics, Stellar Population, and Gas-phase Properties of The Pseudobulge in An Ultra-diffuse Galaxy: AGC721966

Leveraging spectroscopic data from the Sloan Digital Sky Survey, we conduct a comprehensive analysis of the central stellar velocity dispersion, stellar population properties, star formation history, and gas-phase chemical abundances in AGC721966, a unique ultra-diffuse galaxy (UDG) harboring a pseudobulge. Our findings reveal that the pseudobulge formed in the early universe but underwent a recent episode of rejuvenated star formation. The system exhibits a mass-weighted (light-weighted) stellar population age of $τ_{\star}\sim 7.4\pm2.5$ ($2.9\pm1.5$)~Gyr, a stellar metallicity of [M/H]$\sim -0.62\pm0.26$ ($-0.55\pm0.20$), an $α$-element enhancement of [$α$/Fe]$\sim 0.36\pm0.09$ ($0.37\pm0.07$), and a gas-phase oxygen abundance of \Oabund$\sim 8.15\pm0.03$. The central stellar velocity dispersion is measured as $σ_{\rm c}\sim 57.9\pm15.7$~km/s. These results provide robust evidence supporting the early halo-halo merging formation scenario proposed by \cite{Rong25}, while unequivocally ruling out the ``failed'' $L^{\star}$ formation model, at least for AGC721966. Furthermore, through systematic application of the baryonic Tully-Fisher relation, we establish that these pseudobulge-hosting UDGs are neither misidentified nuclear star cluster-bearing dwarf galaxies nor bulge-dominated massive galaxies, thereby affirming their distinct evolutionary pathway.

astro-ph.GA↗

arXiv2025

The Jiutian simulations for the CSST extra-galactic surveys

We provide an overview of the Jiutian simulations, a hybrid simulation suite for the China Space Survey Telescope (CSST) extragalactic surveys. It consists of four complementary modules: the primary runs with high resolutions with the fiducial concordance cosmology, the emulator runs exploring the parameter uncertainties around the fiducial cosmology, the reconstruction runs intended for recovering the observed Universe position by position, and the extension runs employing extended cosmologies beyond the standard model. For the primary runs, two independent pipelines are adopted to construct subhaloes and merger trees. On top of them, four sets of mock galaxy light-cone catalogs are produced from semi-analytical models and subhalo abundance matching, providing a variety of observational properties including galaxy SED, emission lines, lensing distortions, and mock images. The 129 emulator runs are used to train the CSST emulator, achieving one percent accuracy in predicting the matter power spectrum over $k\leq 10h{\rm Mpc}^{-1}$ and $z\leq 2$. The reconstruction runs employ a number of subgrid baryonic models to predict the evolution and galaxy population resembling certain regions in the real Universe with constrained initial conditions, enabling controlled investigation of galaxy formation on top of structure formation. The extension runs cover models with warm dark matter, $f(R)$ gravity, interacting dark energy, and nonzero neutrino masses, revealing differences in the cosmic structure under alternative cosmological models. We introduce the specifications for each run, the data products derived from them, the corresponding pipeline developments, and present some main tests. Using the primary runs, we also show that the subhalo peak mass functions of different levels are approximately universal. These simulations form a comprehensive and open library for CSST surveys and beyond.

astro-ph.CO↗

arXiv2025

Unexpected clustering pattern in dwarf galaxies challenges formation models

The galaxy correlation function serves as a fundamental tool for studying cosmology, galaxy formation, and the nature of dark matter. It is well established that more massive, redder and more compact galaxies tend to have stronger clustering in space. These results can be understood in terms of galaxy formation in Cold Dark Matter (CDM) halos of different mass and assembly history. Here, we report an unexpectedly strong large-scale clustering for isolated, diffuse and blue dwarf galaxies, comparable to that seen for massive galaxy groups but much stronger than that expected from their halo mass. Our analysis indicates that the strong clustering aligns with the halo assembly bias seen in simulations with the standard $Λ$CDM cosmology only if more diffuse dwarfs formed in low-mass halos of older ages. This pattern is not reproduced by existing models of galaxy evolution in a $Λ$CDM framework, and our finding provides new clues for the search of more viable models. Our results can be explained well by assuming self-interacting dark matter, suggesting that such a scenario should be considered seriously.

astro-ph.CO↗