arXiv subjects

Shiyin Shen

Publications and source records attributed to Shiyin Shen.

At least 37 records · Page 2Linked to original sources

arXiv2025

The Velocity Map Asymmetry of Ionized Gas in MaNGA II. Correlation between Velocity Map Morphology, Star Formation, and Metallicity in Regular Disk Galaxies

The morphology of ionized gas velocity maps provides a direct probe of the internal gas kinematics of galaxies. Using integral field spectroscopy from SDSS-IV MaNGA, we analyze a sample of 528 low-inclination, regular disk galaxies to investigate the correlations between velocity map morphology, star formation rate, and gas-phase metallicity. We quantify velocity map morphology using harmonic expansion and adopt two complementary diagnostics: the global kinematic asymmetry, which traces non-axisymmetric perturbations, and the first-order term ratio, which captures axisymmetric radial motions. We find that galaxies with higher kinematic asymmetry are more likely to deviate from the scaling relations, typically lying either above or below the star formation main sequence and systematically below the mass-metallicity relation. In contrast, the first-order term ratio shows only a correlation with gas-phase metallicity in the low-mass range and no significant dependence on star formation rate. Moreover, galaxies below the mass-metallicity relation generally exhibit higher HI gas fractions. These results suggest that external gas accretion is the primary driver of the observed phenomena: inflowing metal-poor gas increases velocity map asymmetry in disk galaxies, dilutes the metallicity, and triggers enhanced star formation. Feedback-driven outflows, bar- and spiral-driven inflows, and galaxy mergers may also contribute, but likely play a secondary role.

astro-ph.GA↗

arXiv2025

The origin of double-peaked narrow emission-line galaxies in MaNGA Survey

We select 36 double-peaked narrow emission-line galaxies (DPGs) from 10,010 unique galaxies in MaNGA survey. These DPGs show double-peaked Balmer lines and forbidden lines in the spectra. We use a double Gaussian model to separate the double-peaked profiles of each emission line into blue and red components ($λ_\text{blue}$ < $λ_\text{red}$), and analyze the spatially resolved kinematics and ionization mechanisms of each component. We find that in 35 out of 36 DPGs, the flux ratio between the blue and red components varies systematically along the major axes, while it keeps roughly a constant along the minor axes. The blue and red components of these DPGs exhibit similar distributions in both the value of line-of-sight velocity and the velocity dispersion. Additionally, 83.3% DPGs have both blue and red components located in the same ionization region in the [SII]-BPT diagram. Combining all these observational results, we suggest that the double-peaked emission line profiles in these 35 DPGs primarily originate from rotating discs. The remaining one galaxy shows clear outflow features. 8 out of 35 DPGs show symmetric line profiles that indicate undisturbed rotating discs, and the other 27 DPGs exhibit asymmetric profiles, suggesting dynamic disturbances in the rotating discs. Furthermore, we find that 58.3% DPGs experienced external processes, characterized by tidal features, companion galaxies, as well as gas-star misalignments. This fraction is about twice as much as that of the control sample, suggesting the origin of double-peaked emission line profiles is associated with external processes.

astro-ph.GA↗

arXiv2025

SEW: A full-spectrum linear fitting with stellar population synthesis method Based on "Equivalent Widths spectrum"

We present a full-spectrum linear fitting method, SEW, for stellar population synthesis based on equivalent widths (EWs) to extract galaxy properties from observed spectra. This approach eliminates the need for prior assumptions about dust attenuation curves, which are instead derived as outputs of the fitting process. By leveraging the invariance of EWs and employing the Discrete Penalised Least Squares (DPLS) method to extract EWs, we address the nonlinear aspects of the fitting process by linearising the matrix equations. This enables accurate recovery of key parameters, stellar age, metallicity and dust attenuation, even under systematic calibration biases and varying attenuation conditions. Rigorous testing with mock spectra across signal-to-noise ratios (S/N = 5-30) and calibration biases demonstrates the robustness of method. The derived attenuation curves align closely with input models, and stellar population parameters are recovered with minimal bias. To facilitate adoption, we implement this method as a Python extension package for \texttt{pPXF} (\texttt{pPXF-SEW}). Our work addresses critical degeneracies in traditional spectral fitting and enhances the reliability of extragalactic studies.

astro-ph.GA↗

arXiv2025

Introduction to the Chinese Space Station Survey Telescope (CSST)

The Chinese Space Station Survey Telescope (CSST) is an upcoming Stage-IV sky survey telescope, distinguished by its large field of view (FoV), high image quality, and multi-band observation capabilities. It can simultaneously conduct precise measurements of the Universe by performing multi-color photometric imaging and slitless spectroscopic surveys. The CSST is equipped with five scientific instruments, i.e. Multi-band Imaging and Slitless Spectroscopy Survey Camera (SC), Multi-Channel Imager (MCI), Integral Field Spectrograph (IFS), Cool Planet Imaging Coronagraph (CPI-C), and THz Spectrometer (TS). Using these instruments, CSST is expected to make significant contributions and discoveries across various astronomical fields, including cosmology, galaxies and active galactic nuclei (AGN), the Milky Way and nearby galaxies, stars, exoplanets, Solar System objects, astrometry, and transients and variable sources. This review aims to provide a comprehensive overview of the CSST instruments, observational capabilities, data products, and scientific potential.

astro-ph.IM↗

arXiv2025

Dependence of halo properties on central-satellite magnitude gaps through weak lensing measurements

The magnitude gap between the central and satellite galaxies encodes information about the mass accretion history of a dark matter halo, and serves as a useful observational probe for the mass distribution in a halo. In this work, we perform the first weak lensing test of the connections between the magnitude gap and the halo profile. We measure the halo profiles of isolated central galaxies (ICGs) selected primarily from the SDSS Main Galaxy Sample. Halo mass and concentration are inferred by fitting stacked lensing profiles in bins of central luminosity, $L_\mathrm{c}$, and the central-satellite magnitude gap, $L_\mathrm{gap}$. We detect dependence on the magnitude gap in both halo properties. The dependence is the strongest in the ICG luminosity range of $10^{10.3}<L_\mathrm{c}[h^{-2}L_\odot]\leq 10^{10.7}$, where halos with smaller gaps have higher masses and lower concentrations. When $10^{10.7} <L_c[h^{-2}L_\odot] \leq 10^{11.1}$, however, no significant gap dependence is detected. In the range of $10^{9.9}<L_\mathrm{c}[h^{-2}L_\odot] \leq 10^{10.3}$, a disordering of the gap dependence is marginally observable. We compare the observational results with predictions by two lightcone catalogs built from the Illustris TNG300 and the Millennium simulations. The gap dependence in the two mock samples show overall consistency with observations, but neither matches them in all $L_\mathrm{c}$ bins to a quantitative level. We also compare the significance of the gap dependence on halo mass and concentration and find that our measurement prefers gap dependence in both parameters, while the halo mass dependence is preferred over the concentration if only one of the two dependencies is allowed.

astro-ph.CO↗

arXiv2025

SDSS-IV MaNGA: Physical Origins of Double-Peaked Narrow Emission-Line Spaxels in Barred Galaxies

The physical origins of double-peaked narrow emission-line spaxels (DPSs) in barred galaxies are explored through the analysis of a sample of 72 barred double-peaked emission-line galaxies (DPGs) extracted from the MaNGA dataset. In this study, we examine two potential scenarios: the gas inflow along the bar and the formation of a bar-induced gaseous nuclear ring. By applying a classical galactic dynamics model, we calculate the radii and rotational velocities of the nuclear rings for all barred DPGs, and compare them with the observed properties of their DPSs. Our analysis reveals a significant correlation between the predicted radii of the nuclear rings and the maximum centric distances of the DPSs, as well as a marginal correlation between the predicted rotational velocities of the nuclear rings and the observed maximum velocity differences of the DPSs. These findings provide strong evidence to support the hypothesis that the DPSs of a barred DPG in MaNGA primarily originate from the convolution of the PSF effect with its bar-induced fast-rotating gaseous nuclear ring.

astro-ph.GA↗

arXiv2025

GalaxyGenius: Mock galaxy image generator for various telescopes from hydrodynamical simulations

We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation will support and advance research on galaxies in the era of large-scale sky surveys. The package comprises three main modules: data preprocessing, ideal data cube generation, and mock observation. Specifically, the preprocessing module extracts necessary properties of star and gas particles for a selected subhalo from hydrodynamical simulations and creates the execution file for the following radiative transfer procedure. Subsequently, building on the above information, the ideal data cube generation module executes a widely used radiative transfer project, specifically the SKIRT, to perform the SED assignment for each particle and the radiative transfer procedure to produce an IFU-like ideal data cube. Lastly, the mock observation module takes the ideal data cube and applies the throughputs of aiming telescopes, while also incorporating the relevant instrumental effects, point spread functions (PSFs), and background noise to generate the required mock observational images of galaxies. To showcase the outcomes of GalaxyGenius, we created a series of mock images of galaxies based on the IllustrisTNG and EAGLE simulations for both space and ground-based surveys, spanning ultraviolet (UV) to infrared (IR) wavelength coverage, including CSST, Euclid, HST, JWST, Roman, and HSC. GalaxyGenius offers a flexible framework to generate mock galaxy images with customizable recipes. These generated images can serve as valuable references for verifying and validating new approaches in astronomical research. They can also serve as training sets for relevant studies using deep learning in cases where real observational data are insufficient.

astro-ph.IM↗

arXiv2025

Capivara: A Spectral-based Segmentation Method for IFU Data Cubes

We present capivara, a fast and scalable spectral-based segmentation package designed to study astrophysical properties within distinct structural components of galaxies. This spectro-segmentation code for integral field unit (IFU) data provides a holistic view of galactic structure, moving beyond conventional radial gradients and the bulge-plus-disk dichotomy. It enables detailed comparisons of stellar ages and metallicities across components, and naturally identifies outliers by grouping spaxels according to dominant spectral features. The algorithm leverages Torch's scalability and GPU acceleration, outputting a masked FITS file that assigns each pixel to its respective group and generates the corresponding one-dimensional spectrum per group, without relying on Voronoi binning. We demonstrate the capabilities of the method using a sample of MaNGA galaxies, combining capivara segmentation with the starlight spectral fitting code to derive stellar population and ionized gas properties. The method effectively identifies regions with similar spectral properties across both continuum and emission lines. By aggregating the spectra of these regions, we enhance the signal-to-noise ratio of the analysis while preserving the spectral coherence within each group. capivara is released under an MIT license and is available at https://github.com/RafaelSdeSouza/capivara.

astro-ph.GA↗

arXiv2025

The Universe is Odd

The cosmological principle posits that the universe does not exhibit any specific preference for position or direction. However, it remains unclear whether the universe has a distinct preference for parity: whether certain properties are more likely to be classified as even or odd. In this study, we analyze the largest available galaxy group catalogs to explore this hypothesis: specifically, whether the number of galaxies within a galaxy group or cluster is more likely to be odd or even. Our findings convincingly indicate that the universe indeed favors odd numbers, with results achieving a significance level well above the $4.1-σ$ threshold.

physics.pop-ph↗

arXiv2025

Robust machine learning model of inferring the ex-situ stellar fraction of galaxies from photometric data

We search for parameters defined from photometric images to quantify the ex situ stellar mass fraction of galaxies. We created mock images using galaxies in the cosmological hydrodynamical simulations TNG100, EAGLE, and TNG50 at redshift $z=0$. We define a series of parameters describing their structures. In particular, the inner and outer halo of a galaxy are defined by sectors ranging from $45-135$ degrees from the disk major axis, and with radii ranging from $3.5-10$ kpc and $10-30$ kpc, respectively, to avoid the contamination of disk and bulge. The surface brightness and colour gradients are defined by the same sectors along the minor axis and with similar radii ranges. We used the Random Forest method to create a model that predicts $f_{\rm exsitu}$ from morphological parameters. The model predicts $f_{\rm exsitu}$ well with a scatter smaller than 0.1 compared to the ground truth in all mass ranges. The models trained from TNG100 and EAGLE work similarly well and are cross-validated; they also work well in making predictions for TNG50 galaxies. The analysis using Random Forest reveals that $\nabla ρ_{\rm outer}$, $\nabla (g-r)_{\rm outer}$, $f_{\rm outerhalo}$ and $f_{\rm innerhalo}$ are the most influential parameters in predicting $f_{\rm exsitu}$, underscoring their significance in uncovering the merging history of galaxies. We further analyse how the quality of images will affect the results by using SDSS-like and HSC-like mock images for galaxies at different distances. Our results can be used to infer the ex situ stellar mass fractions for a large sample of galaxies from photometric surveys.

astro-ph.GA↗

arXiv2024

From Galaxy Zoo DECaLS to BASS/MzLS: detailed galaxy morphology classification with unsupervised domain adaption

The DESI Legacy Imaging Surveys (DESI-LIS) comprise three distinct surveys: the Dark Energy Camera Legacy Survey (DECaLS), the Beijing-Arizona Sky Survey (BASS), and the Mayall z-band Legacy Survey (MzLS). The citizen science project Galaxy Zoo DECaLS 5 (GZD-5) has provided extensive and detailed morphology labels for a sample of 253,287 galaxies within the DECaLS survey. This dataset has been foundational for numerous deep learning-based galaxy morphology classification studies. However, due to differences in signal-to-noise ratios and resolutions between the DECaLS images and those from BASS and MzLS (collectively referred to as BMz), a neural network trained on DECaLS images cannot be directly applied to BMz images due to distributional mismatch. In this study, we explore an unsupervised domain adaptation (UDA) method that fine-tunes a source domain model trained on DECaLS images with GZD-5 labels to BMz images, aiming to reduce bias in galaxy morphology classification within the BMz survey. Our source domain model, used as a starting point for UDA, achieves performance on the DECaLS galaxies' validation set comparable to the results of related works. For BMz galaxies, the fine-tuned target domain model significantly improves performance compared to the direct application of the source domain model, reaching a level comparable to that of the source domain. We also release a catalogue of detailed morphology classifications for 248,088 galaxies within the BMz survey, accompanied by usage recommendations.

astro-ph.GA↗

arXiv2024

Radial Profiles of $Σ_{\ast}$, $Σ_{\rm SFR}$, Gas Metallicity and Their Correlations Across the Galactic Mass-Size Plane

We analyzed the global and resolved properties of approximately 1,240 nearby star-forming galaxies from the MaNGA survey, comparing compact and extended galaxies -- those with smaller and larger radii ($R_{\rm e}$), respectively -- at a fixed stellar mass ($M_{\ast}$). Compact galaxies typically exhibit lower HI gas fractions, higher dust extinction, higher metallicity, greater mass concentration, and lower angular momentum on a global scale. Radial profiles of stellar mass surface density ($Σ_{\ast}$) and star formation rate surface density ($Σ_{\rm SFR}$), as functions of the effective radius ($R/$$R_{\rm e}$), reveal that compact galaxies display steeper gradients and higher values, resulting in elevated specific star formation rates (sSFR) in their inner regions compared to their outskirts. At a given $Σ_{\ast}$, compact galaxies have higher sSFR than extended galaxies, particularly in low-mass galaxies (log($M_{\ast}$/$M_{\odot}$)$\,\leq\,$10$^{10}$). Additionally, their metallicity profiles differ significantly: extended galaxies have steeper metallicity gradients, while compact galaxies exhibit flatter slopes and higher metallicity at a given $R/$$R_{\rm e}$. After accounting for the dependence of metallicity on $M_{\ast}$ and $Σ_{\ast}$, no further correlation with SFR is observed. The combination of higher sSFR and potentially higher star formation efficiency in compact galaxies suggests that their central gas is being rapidly consumed, leading to older stellar populations, as indicated by D$_{n}$(4000) and EW(H$δ_A$), and resulting in faster central growth. Our results reveal that radial SFR profiles cannot be fully determined by $M_{\ast}$ and $Σ_{\ast}$ alone; other factors, such as galaxy size or angular momentum, must be considered to fully understand the observed trends.

astro-ph.GA↗

arXiv2024

Double-peaked Narrow Emission-Line Galaxies in SDSS-IV MaNGA

Narrow emission lines in a galaxy's spectrum that show double peaks indicate the presence of distinct gas components with different velocities, and its physical origin remains uncertain. This study uses galaxies from the final MaNGA data release to detect double-peaked narrow emission-line spaxels (DPSs) by examining the double Gaussian profiles of the H$ α$-[N \uppercase\expandafter{\romannumeral2}] doublets across all MaNGA spaxels. A total of 5,420 DPSs associated with 304 double-peaked narrow emission-line galaxies (DPGs) are identified, each DPG containing a minimum of 5 DPSs and being free from overlap with other galaxies. We find that DPSs can be categorized into three groups according to their central distance $r/R_e$ and the velocity difference $Δv$ between their two components: the inner low-$Δv$, inner high-$Δv$ and outer DPSs. By incorporating the physical characteristics of the DPGs into their DPSs, we demonstrate for the first time the existence of statistical correlations between barred DPGs and inner low-$Δv$ DPSs, AGN-hosting DPGs and inner high-$Δv$ DPSs, as well as tidal DPGs and outer DPSs.

astro-ph.GA↗

arXiv2024

Systematic analysis of jellyfish galaxy candidates in Fornax, Antlia, and Hydra from the S-PLUS survey: A self-supervised visual identification aid

We study 51 jellyfish galaxy candidates in the Fornax, Antlia, and Hydra clusters. These candidates are identified using the JClass scheme based on the visual classification of wide-field, twelve-band optical images obtained from the Southern Photometric Local Universe Survey. A comprehensive astrophysical analysis of the jellyfish (JClass > 0), non-jellyfish (JClass = 0), and independently organized control samples is undertaken. We develop a semi-automated pipeline using self-supervised learning and similarity search to detect jellyfish galaxies. The proposed framework is designed to assist visual classifiers by providing more reliable JClasses for galaxies. We find that jellyfish candidates exhibit a lower Gini coefficient, higher entropy, and a lower 2D Sérsic index as the jellyfish features in these galaxies become more pronounced. Jellyfish candidates show elevated star formation rates (including contributions from the main body and tails) by $\sim$1.75 dex, suggesting a significant increase in the SFR caused by the ram-pressure stripping phenomenon. Galaxies in the Antlia and Fornax clusters preferentially fall towards the cluster's centre, whereas only a mild preference is observed for Hydra galaxies. Our self-supervised pipeline, applied in visually challenging cases, offers two main advantages: it reduces human visual biases and scales effectively for large datasets. This versatile framework promises substantial enhancements in morphology studies for future galaxy image surveys.

astro-ph.GA↗

arXiv2024

A Versatile Framework for Analyzing Galaxy Image Data by Implanting Human-in-the-loop on a Large Vision Model

The exponential growth of astronomical datasets provides an unprecedented opportunity for humans to gain insight into the Universe. However, effectively analyzing this vast amount of data poses a significant challenge. Astronomers are turning to deep learning techniques to address this, but the methods are limited by their specific training sets, leading to considerable duplicate workloads too. Hence, as an example to present how to overcome the issue, we built a framework for general analysis of galaxy images, based on a large vision model (LVM) plus downstream tasks (DST), including galaxy morphological classification, image restoration, object detection, parameter extraction, and more. Considering the low signal-to-noise ratio of galaxy images and the imbalanced distribution of galaxy categories, we have incorporated a Human-in-the-loop (HITL) module into our large vision model, which leverages human knowledge to enhance the reliability and interpretability of processing galaxy images interactively. The proposed framework exhibits notable few-shot learning capabilities and versatile adaptability to all the abovementioned tasks on galaxy images in the DESI legacy imaging surveys. Expressly, for object detection, trained by 1000 data points, our DST upon the LVM achieves an accuracy of 96.7%, while ResNet50 plus Mask R-CNN gives an accuracy of 93.1%; for morphology classification, to obtain AUC ~0.9, LVM plus DST and HITL only requests 1/50 training sets compared to ResNet18. Expectedly, multimodal data can be integrated similarly, which opens up possibilities for conducting joint analyses with datasets spanning diverse domains in the era of multi-message astronomy.

astro-ph.IM↗

arXiv2024

Galmoss: A package for GPU-accelerated Galaxy Profile Fitting

We introduce galmoss, a python-based, torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, galmoss meets the high computational demands of large-scale galaxy surveys, placing galaxy profile fitting in the LSST-era. It incorporates widely used profiles such as the Sérsic, Exponential disk, Ferrer, King, Gaussian, and Moffat profiles, and allows for the easy integration of more complex models. Tested on 8,289 galaxies from the Sloan Digital Sky Survey (SDSS) g-band with a single NVIDIA A100 GPU, galmoss completed classical Sérsic profile fitting in about 10 minutes. Benchmark tests show that galmoss achieves computational speeds that are 6 $\times$ faster than those of default implementations.

astro-ph.GA↗

arXiv2023

From Images to Features: Unbiased Morphology Classification via Variational Auto-Encoders and Domain Adaptation

We present a novel approach for the dimensionality reduction of galaxy images by leveraging a combination of variational auto-encoders (VAE) and domain adaptation (DA). We demonstrate the effectiveness of this approach using a sample of low redshift galaxies with detailed morphological type labels from the Galaxy-Zoo DECaLS project. We show that 40-dimensional latent variables can effectively reproduce most morphological features in galaxy images. To further validate the effectiveness of our approach, we utilised a classical random forest (RF) classifier on the 40-dimensional latent variables to make detailed morphology feature classifications. This approach performs similarly to a direct neural network application on galaxy images. We further enhance our model by tuning the VAE network via DA using galaxies in the overlapping footprint of DECaLS and BASS+MzLS, enabling the unbiased application of our model to galaxy images in both surveys. We observed that DA led to even better morphological feature extraction and classification performance. Overall, this combination of VAE and DA can be applied to achieve image dimensionality reduction, defect image identification, and morphology classification in large optical surveys.

astro-ph.GA↗

arXiv2023

Linking the Metallicity Enrichment History to the Star Formation History: An SFH-regulated Chemical Evolution Model and Its Implications for the Gas Cycling Process

The metallicity enrichment history (MEH) of a galaxy is determined by its star formation history (SFH) and the gas cycling process. In this paper, we construct a chemical evolution model that is regulated by the SFH of the system. In this SFH-regulated model, the evolution of all other variables, including the MEH, can be determined by the SFH. We test this model on six locally isolated dwarf galaxies covering three dwarf types that were observed by the Local Cosmology from Isolated Dwarfs (LCID) project. The SFHs and MEHs of these LCID galaxies have been measured from the deep color-magnitude diagrams that are down to the main sequence turn-offs stars. With simple assumptions of the star formation law and the mass-dependent outflows, our SFH-regulated model successfully reproduces the MEHs of all six LCID galaxies from their SFHs, with only one free parameter, the wind efficiency $η\sim 1.0$, for all six galaxies. This model provides a physically motivated link that directly connects the SFH and MEH of a galaxy, which will be useful to accommodate into the state-of-the-art stellar population synthesis models to help relieve the nuisance of the heavy degeneracy between the ages and metallicities of the stellar populations.

astro-ph.GA↗