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Dandan Xu

Publications and source records attributed to Dandan Xu.

At least 19 recordsLinked to original sources

Can third- and fourth-order multipoles plus radial variation of iso-density ellipses explain the observed flux ratios in B1422$+$231? YES, and a lesson learned from a TNG100 lensing galaxy sample

Flux ratio anomalies in multiply-imaged quasar lenses are a long-standing issue. Using a classical system B1422+231 as a case study, we investigate how typical non-clumpy perturbations beyond elliptical shapes -- multipoles $m_3, m_4$ and radial variations in $q, \phi_q$ -- can account for the observed image positions and flux ratios under different observational precisions. We extract these perturbations from a pre-selected strong-lensing galaxy sample from the TNG100 simulation. Smooth macroscopic models (SIE+$\gamma$, EPL+$\gamma$) are then fitted to the observed image positions alone and to both positions and flux ratios, with and without including the extracted perturbations. With astrometric uncertainty of $\sigma_{p}=10$ mas, both macro-models alone can already successfully fit image positions within $3\sigma_{p}$. At $\sigma_{p}=2$ mas, however, 'astrometric anomalies' appear if smooth macro-models alone are adopted. In this case, adding the extracted perturbations can explain the anomalous image positions. When both positions and flux ratios are adopted, the SIE+$\gamma$ model family already shows 'flux ratio anomalies' at photometric uncertainty $\sigma_{f} \le 10\%$ (keeping $\sigma_{p}=10$ mas). When EPL+$\gamma$ is used, the smooth model alone can simultaneously fit both positions and flux ratios with $\sigma_{f}=10\%, 5\%$, but not with $\sigma_{f}=2\%$, where 'flux ratio anomalies' appear. Adding all four types of extracted perturbations can rescue the macro-models and explain the observed anomalous flux ratios. We present important lessons learned regarding model flexibility and degeneracy.

astro-ph.GA

Optically Selected Superthin Galaxies Remain Thin in the Near-infrared

We investigate whether galaxies identified as superthin in optical images remain superthin in the near-infrared (NIR), and how their extreme disk morphology is related to environment. From a nearby volume-limited sample, we select 210 superthin galaxies using two-dimensional bulge/disk decomposition of SDSS $r$-band images, requiring the disk component to have a major-to-minor axis ratio $a/b>9$. We measure disk shapes from SDSS $griz$ to UKIDSS $JHK$ bands. Both the major- and minor-axis scales decrease from the optical to the NIR, reaching $\sim0.6$ of their $r$-band values in the $K$ band, but the disk axis ratio remains nearly unchanged. Thus, optically selected superthin galaxies remain superthin in the NIR, implying that the old stellar populations traced by NIR light do not form a prominent thick disk. Reanalysis of our sample and a previous superthin sample shows that earlier reported NIR thickening is mainly due to a magnitude- and band-dependent bias in one-dimensional fitting. We further compare their environments with matched control samples using projected cross-correlations, reconstructed local overdensities, and large-scale-structure classifications. Superthin galaxies show lower clustering on $\sim0.1$--$1\,h^{-1}\,\mathrm{Mpc}$ scales and lower overdensities at $1\,h^{-1}\,\mathrm{Mpc}$, but no clear residual dependence on large-scale-structure type. These results suggest that superthin galaxies are preferentially central galaxies in relatively low-mass dark matter halos, consistent with a picture in which high host-halo spin helps build and preserve extended, vertically thin stellar disks.

astro-ph.GA

The Galaxy Stellar Mass-SFR-Size Relation in EAGLE, TNG100, and Observations

Stellar mass, size, and star formation rate (SFR) are fundamental properties that encode the structural and evolutionary states of galaxies. Observations reveal a mass-SFR-size relation whereby galaxies become more compact both above and below the ridge of the star-forming main sequence (SFMS), linking galaxy structure to star formation activity. We investigate this relation by comparing galaxies from two cosmological hydrodynamical simulations, EAGLE and TNG100, with observational samples from SDSS and CANDELS over three redshift intervals (0 < z < 0.2, 0.5 < z < 1.5, and 1.5 < z < 2.5). Both simulations reproduce the observed trend that galaxy sizes decrease with increasing offset away from the SFMS. This trend, however, weakens and is not detected in the observational sample at 1.5 < z < 2.5, likely due to increased measurement uncertainties. In contrast, the trend persists in both simulations up to z = 2.5. Across all redshifts, EAGLE predicts a stronger size dependence on SFMS offset than observed, whereas TNG100 exhibits a weaker dependence. We discuss how this mass-SFR-size relation can be understood in terms of different time variability in star formation rate across the SFMS.

astro-ph.GA

Dynamical Modelling of Galactic Kinematics using Neural Networks

The advent of integral field data has revolutionised the study of galaxy evolution. A key component of this is dynamical modelling methods which have allowed for crucial insights to be made from kinematic data. Despite this importance, most dynamical models make a number of key assumptions which do not hold for real galaxies. These include assumptions about the geometry (axisymmetry or triaxiality), the shape of the velocity ellipsoid, and the shape of the underlying stellar distribution. At the same time, machine learning methods are becoming increasingly powerful, with many applications appearing in astronomy. As a first step towards building new dynamical modelling methods with machine learning, it is important to understand the types of machine learning architectures that are best fit for dynamical modelling. To investigate this, we construct a training set of dynamical models of early-type galaxies using Jeans Anisotropic Modelling (JAM). We then train a neural network on this data using the parameters of JAM and mock photometry as the input. We are able to accurately model JAM galaxies with relatively simple machine learning architectures, leading to a significant speed increase over traditional JAM modelling.

astro-ph.GA

Episodic Star Formation -- I. Overview and Scatter of the Star-Forming Main Sequence

Episodic star formation cycles in both high- and low-redshift galaxies have gained more and more evidence. This paper aims to understand the detailed physical processes behind such behaviors and investigate how such an episodic star-forming scenario can explain the scatter in star-formation rate (SFR) of star-forming main-sequence galaxies. This is achieved through tracing back in time the history of z=0 star-forming central galaxies in the TNG100 simulation over the past 7-8 Gyrs. As the first paper in this series, we provide an overview of the episodic star formation history. We find that two branches of star formation typically develop during each episode: while one branch happens in heavily metal-enriched gas in the centers of galaxies, a secondary branch starts in lower-metallicity regions at galaxy outskirts where fresh gas first arrives, and gradually progresses to inner regions of galaxies. Additionally, the temporal variation in the SFR at galaxy outskirts is more significant than that at centers. As a consequence, the metallicities in both gas and young stars exhibit remarkably different distributions between SFR peaks and valleys. The resulting temporal SFR fluctuation within individual galaxies has an average of ~ 0.2 dex, while the intrinsic differentiation between (the historical mean of) galaxies is ~ 0.15 dex. These two together can well account for the scatter in SFR of ~ 0.25 dex as observed for z=0 star-forming main-sequence galaxies.

astro-ph.GA

The Impact of Orbital Anisotropy Assumptions in Lensing-Dynamics Modeling

We investigate potential systematic biases introduced by assumptions regarding stellar orbital anisotropy in joint lensing-dynamics modeling. Our study employs the massive early-type galaxies from the TNG100 simulation at redshifts z = 0.2, 0.5, and 0.7. Based on the simulated galaxies, we generate a self-consistent mock dataset containing both lensing and stellar kinematic observables. This is achieved through taking the potential composed of both dark matter and baryons of the simulated galaxies, plus the radial variation of the stellar orbit anisotropy depicted by a logistic function. By integrating constraints from both lensing and stellar kinematics, we separate the contributions of stars and dark matter inside the galaxies. Under three commonly adopted stellar anisotropy assumptions (isotropic orbits, constant anisotropy, and the Osipkov-Merritt profile), the model inferences suggest that the systematic biases in the total stellar mass and central dark matter fraction are not significant. Specifically, the total stellar mass on average is underestimated by less than $0.03\pm0.10$ $\rm dex$ while the dark matter fraction experiences only a statistically insignificant increase of less than $2\%\pm10\%$ at the population level. The dark matter inner density slope in our tests is over-predicted by $0.15\pm0.2$. Additionally, these lacks of significant biases are insensitive to the discrepancies between the assumed anisotropy in modeling and the ground truth orbital anisotropy of mock sample. Our results suggest that conventional assumptions regarding orbital anisotropy, such as an isotropic profile or the Osipkov-Merritt model, would not introduce a significant systematic bias when inferring galaxy mass density distribution at the population level.

astro-ph.GA

Soft X-ray line emission from hot gas in intervening galaxy halos and diffuse gas in the cosmic web

Cosmic hot-gas emission is closely related to halo gas acquisition and galactic feedback processes. Their X-ray observations reveal important physical properties and movements of the baryonic cycle of galactic ecosystems. However, the measured emissions toward a target at a cosmological distance would always include contributions from hot gases along the entire line of sight to the target. Observationally, such contaminations are routinely subtracted via different strategies. With this work, we aim to answer an interesting theoretical question regarding the amount of soft X-ray line emissions from intervening hot gases of different origins. We tackled this problem with the aid of the TNG100 simulation. We generated typical wide-field light cones and estimated their impacts on spectral and flux measurements toward X-ray-emitting galaxy-, group- and cluster-halo targets at lower redshifts. We split the intervening hot gases into three categories; that is, the hot gas that is gravitationally bound to either star-forming or quenched galaxy halos, and the diffuse gas, which is more tenuously distributed permeating the cosmic web structures. We find that along a given line of sight, the diffuse gas that permeates the cosmic web structures produces strong oxygen and iron line emissions at different redshifts. The diffuse gas emission in the soft X-ray band can be equal to the emission from hot gases that are gravitationally bound to intervening galaxy halos. The hot-gas emission from the quiescent galaxy halos can be significantly less than that from star-forming halos along the line of sight. The fluxes from all of the line-of-sight emitters as measured in the energy band of 0.4--0.85 keV can reach ~20--200 % of the emission from the target galaxy, group, and cluster halos.

astro-ph.CO

Bumblebee cosmology: The FLRW solution and the CMB temperature anisotropy

We put into test the idea of replacing dark energy by a vector field against the cosmic microwave background (CMB) observation using the simplest vector-tensor theory, where a massive vector field couples to the Ricci scalar and the Ricci tensor quadratically. First, a remarkable Friedmann-Lema\^{i}tre-Robertson-Walker (FLRW) metric solution that is completely independent of the matter-energy compositions of the universe is found. Second, based on the FLRW solution as well as the perturbation equations, a numerical code calculating the CMB temperature power spectrum is built. We find that though the FLRW solution can mimic the evolution of the universe in the standard $\Lambda$CDM model, the calculated CMB temperature power spectrum shows unavoidable discrepancies from the CMB power spectrum measurements.

gr-qc

Bumblebee cosmology: Tests using distance- and time-redshift probes

In modern cosmology, the discovery of the universe's accelerated expansion has significantly transformed our understanding of cosmic evolution and expansion history. The unknown properties of dark energy, the driver of this acceleration, have not only prompted extensive studies on its nature but also spurred interest in modified gravity theories that might serve as alternatives. In this paper, we adopt a bumblebee vector-tensor modified gravity theory to model the cosmic expansion history and derive predictions for the Hubble parameter. We constrain the bumblebee model parameters using observational data from established probes, including the Pantheon+ Type Ia Supernovae calibrated via the SH0ES (Supernova $H_0$ for the Equation of State) Cepheid distance ladder analysis and Baryon Acoustic Oscillations (BAO) measurements from Dark Energy Spectroscopic Instrument (DESI) Data Release 2 (DR2), as well as recently included cosmic chronometers (CC) and gamma-ray bursts (GRBs). The Markov Chain Monte Carlo (MCMC) sampling of the Bayesian posterior distribution enables us to rigorously constrain the bumblebee models and compare them with the standard $\Lambda$CDM cosmology. We find that the bumblebee theory on its own can provide sufficiently good fits to the current observational data of distance- and time-redshift relations, suggesting its potential to explain the cosmic background dynamics. However, when compared to $\Lambda$CDM, the latter still outperforms the former according to the information criteria. We propose that further constraints from cosmological perturbation tests could impose more stringent constraints on bumblebee cosmology.

astro-ph.CO

CS-Eval: A Comprehensive Large Language Model Benchmark for CyberSecurity

Over the past year, there has been a notable rise in the use of large language models (LLMs) for academic research and industrial practices within the cybersecurity field. However, it remains a lack of comprehensive and publicly accessible benchmarks to evaluate the performance of LLMs on cybersecurity tasks. To address this gap, we introduce CS-Eval, a publicly accessible, comprehensive and bilingual LLM benchmark specifically designed for cybersecurity. CS-Eval synthesizes the research hotspots from academia and practical applications from industry, curating a diverse set of high-quality questions across 42 categories within cybersecurity, systematically organized into three cognitive levels: knowledge, ability, and application. Through an extensive evaluation of a wide range of LLMs using CS-Eval, we have uncovered valuable insights. For instance, while GPT-4 generally excels overall, other models may outperform it in certain specific subcategories. Additionally, by conducting evaluations over several months, we observed significant improvements in many LLMs' abilities to solve cybersecurity tasks. The benchmarks are now publicly available at https://github.com/CS-EVAL/CS-Eval.

cs.CR

From larger-scale cold-gas angular-momentum environment to galaxy star-formation activeness

We study the influence of the ambient large-scale cold-gas vorticity on the specific star formation rate (sSFR) of central galaxies with stellar masses of $10.0<\log\,M_{\ast}/\mathrm{M_{\odot}}<11.5$ at $z=0$, using the TNG100 simulation. The cold-gas vorticity defined and calculated for gas with $T_{\rm gas} < 2\times 10^4 \mathrm{K}$ and on scales of $\sim$ 1 Mpc can well describe the angular motion of the ambient cold gas. We find crucial evidence for connections between the cold-gas vorticity and star-formation activeness, such that at any given halo mass (particularly below $10^{13}\,\mathrm{M_{\odot}}$), galaxies living in higher cold-gas vorticity environments are generally less star-forming, regardless of their large-scale environment types (filament or knot), or star formation states (star-forming or quenched). Specifically, at a fixed halo mass scale of $10^{12}-10^{13}\,\mathrm{M_{\odot}}$, the median sSFR of galaxies living in environments with the top 30\% cold-gas vorticity is $\sim 0.5$ dex below that of galaxies living in environments with the bottom 30\% cold-gas vorticity. At any fixed halo mass scale, cold-gas vorticities around filament galaxies are generally higher than those around knot galaxies, consistent with that filament galaxies have lower sSFRs than knot galaxies. This large-scale cold-gas vorticity is highly connected to the orbital angular momentum of neighboring galaxies up to a distance of $\sim$ 500 kpcs, indicating their common origin and a possible angular momentum inheritance/modulation from the latter to the former. The negative modulation by the environmental vorticity to galaxy star formation is only significantly observed for the cold gas, indicating the unique role of cold-gas angular momentum.

astro-ph.GA

Biases in galaxy spectral analysis from strong lensing differential magnification effect and correction methods

Strong gravitational lensing has significantly advanced the study of high-redshift galaxies, but the differential magnification effect inevitably introduces biases in the spectral analysis of source galaxies. This work investigates these biases using mock lensing systems from MaNGA survey data and IllustrisTNG simulations. We analyze the impact of lensing effect on several spectral properties, including stellar age, metallicity, H$\alpha$ flux, and optical emission line ratios. Our results show significant biases in all properties after lensing. The values of quantities can be either over- or under-estimated, except for the consistently enhanced H$\alpha$ flux. The bias varies with lensing configurations and always arises when part of the source galaxy falls into the strong lensing regime. We evaluate two correction methods to recover the intrinsic source properties: the average magnification factor ($\bar{\mu}$) and full ray-tracing. While both methods reduce the overestimated H$\alpha$ flux, the $\bar{\mu}$ method shows a much larger discrepancy. For stellar population properties and emission line ratios, the $\bar{\mu}$ method fails whereas the ray-tracing method proves effective. Applying these two methods to a statistical sample of mock systems further shows their strong dependence on lens modeling accuracy. As a demonstrative study, our results highlight the importance of spatially resolved spectroscopic observations and precise lens modeling for reconstructing spectra of strongly lensed galaxies. While our conclusions are based on a specific source and lens galaxy, further studies with a statistical sample of realistic mock lensing systems are needed for understanding any systematic differences between the two correction methods.

astro-ph.GA

Disparate Effects of Circumgalactic Medium Angular Momentum in IllustrisTNG and SIMBA

In this study, we examine the role of circumgalactic medium (CGM) angular momentum ($j_{\rm CGM}$) on star formation in galaxies, whose influence is currently not well understood. The analysis utilises central galaxies from two hydrodynamical simulations, SIMBA and IllustrisTNG. We observe a substantial divergence in how star formation rates correlate with CGM angular momentum between the two simulations. Specifically, quenched galaxies in IllustrisTNG show high $j_{\rm CGM}$, while in SIMBA, quenched galaxies have low $j_{\rm CGM}$. This difference is attributed to the distinct active galactic nucleus (AGN) feedback mechanisms active in each simulation. Moreover, both simulations demonstrate similar correlations between $j_{\rm CGM}$ and environmental angular momentum ($j_{\rm Env}$) in star-forming galaxies, but these correlations change notably when kinetic AGN feedback is present. In IllustrisTNG, quenched galaxies consistently show higher $j_{\rm CGM}$ compared to their star-forming counterparts with the same $j_{\rm Env}$, a trend not seen in SIMBA. Examining different AGN feedback models in SIMBA, we further confirm that AGN feedback significantly influences the CGM gas distribution, although the relationship between the cold gas fraction and the star formation rate (SFR) remains largely stable across different feedback scenarios.

astro-ph.GA

Formation of super-thin galaxies in Illustris-TNG

Superthin galaxies are observed to have stellar disks with extremely small minor-to-major axis ratios. In this work, we investigate the formation of superthin galaxies in the TNG100 simulation. We trace the merger history and investigate the evolution of galaxy properties of a selected sample of superthin galaxies and a control sample of galaxies that share the same joint probability distribution in the stellar-mass and color diagram. Through making comparisons between the two galaxy samples, we find that present-day superthin galaxies had similar morphologies as the control sample counterparts at higher redshifts, but have developed extended flat `superthin' morphologies since $z \sim 1$. During this latter evolution stage, superthin galaxies undergo overwhelmingly higher frequency of prograde mergers (with orbit-spin angle $\theta_{\rm orb} \leqslant 40^\circ$). Accordingly the spins of their dark matter halos have grown significantly and become noticeably higher than that of their normal disk counterparts. This further results in the buildup of their stellar disks at larger distances much beyond the regimes of normal disk galaxies. We also discuss the formation scenario of those superthin galaxies that live in larger dark matter halos as satellite galaxies therein.

astro-ph.GA

MaNGA DynPop -- V. The dark-matter fraction versus stellar velocity dispersion relation and stellar initial mass function variations in galaxies: dynamical models and full spectrum fitting of integral-field spectroscopy

Using the final MaNGA sample of 10K galaxies, we investigate the dark matter fraction $f_{\rm DM}$ within one half-light radius $R_{\rm e}$ for about 6K galaxies with good kinematics spanning a wide range of morphologies and stellar velocity dispersion. We employ two techniques to estimate $f_{\rm DM}$: (i) Jeans Anisotropic Modelling (JAM), which performs dark matter decomposition based on stellar kinematics and (ii) comparing the total dynamical mass-to-light ratios $(M/L)_{\rm JAM}$ and $(M_{\ast}/L)_{\rm SPS}$ from Stellar Population Synthesis (SPS). We find that both methods consistently show a significant trend of increasing $f_{\rm DM}$ with decreasing $σ_{\rm e}$ and low $f_{\rm DM}$ at larger $σ_{\rm e}$. For 235 early-type galaxies with the best models, we explore the variation of stellar initial mass function (IMF) by comparing the stellar mass-to-light ratios from JAM and SPS. We confirm that the stellar mass excess factor $α_{\rm IMF}$ increases with $σ_{\rm e}$, consistent with previous studies that reported a transition from Chabrier-like to Salpeter IMF among galaxies. We show that the $α_{\rm IMF}$ trend cannot be driven by $M_{\ast}/L$ or IMF gradients as it persists when allowing for radial gradients in our model. We find no evidence for the total $M/L$ increasing toward the centre. We detect weak positive correlations between $α_{\rm IMF}$ and age, but no correlations with metallicity. We stack galaxy spectra according to their $α_{\rm IMF}$ to search for differences in IMF-sensitive spectral features (e.g. the $\rm Na_{\rm I}$ doublet). We only find marginal evidence for such differences, which casts doubt on the validity of one or both methods to measure the IMF.

astro-ph.GA

Galaxy stellar and total mass estimation using machine learning

Conventional galaxy mass estimation methods suffer from model assumptions and degeneracies. Machine learning, which reduces the reliance on such assumptions, can be used to determine how well present-day observations can yield predictions for the distributions of stellar and dark matter. In this work, we use a general sample of galaxies from the TNG100 simulation to investigate the ability of multi-branch convolutional neural network (CNN) based machine learning methods to predict the central (i.e., within $1-2$ effective radii) stellar and total masses, and the stellar mass-to-light ratio $M_*/L$. These models take galaxy images and spatially-resolved mean velocity and velocity dispersion maps as inputs. Such CNN-based models can in general break the degeneracy between baryonic and dark matter in the sense that the model can make reliable predictions on the individual contributions of each component. For example, with $r$-band images and two galaxy kinematic maps as inputs, our model predicting $M_*/L$ has a prediction uncertainty of 0.04 dex. Moreover, to investigate which (global) features significantly contribute to the correct predictions of the properties above, we utilize a gradient boosting machine. We find that galaxy luminosity dominates the prediction of all masses in the central regions, with stellar velocity dispersion coming next. We also investigate the main contributing features when predicting stellar and dark matter mass fractions ($f_*$, $f_{\rm DM}$) and the dark matter mass $M_{DM}$, and discuss the underlying astrophysics.

astro-ph.GA

Kinematical coherence between satellite galaxies and host stellar discs for MaNGA & SAMI galaxies

The effect of angular momentum on galaxy formation and evolution has been studied for several decades. Our recent two papers using IllustrisTNG-100 simulation have revealed the acquisition path of the angular momentum from large-scale environment (satellites within hundreds of kpc) through the circum-galactic medium (CGM) to the stellar discs, putting forward the co-rotation scenario across the three distance scales. In real observations, although the rotation signature for the CGM and environmental three-dimensional (3d) angular momentum are difficult to obtain, line-of-sight kinematics of group member galaxies and stellar disc kinematics of central galaxies are available utilizing existing group catalogue data and integral field unit (IFU) data. In this paper, we use (1) the group catalogue of SDSS DR7 and MaNGA IFU stellar kinematic maps and (2) the group catalogue of GAMA DR4 data and SAMI IFU stellar kinematic maps, to test if the prediction above can be seen in real data. We found the co-rotation pattern between stellar discs and satellites can be concluded with 99.7 percent confidence level ($\sim 3σ$) when combining the two datasets. And the random tests show that the signal can be scarcely drawn from random distribution.

astro-ph.GA

Modeling biases from constant stellar mass-to-light ratio assumption in galaxy dynamics and strong lensing

A constant stellar mass-to-light ratio $M_\star/L$ has been widely-used in studies of galaxy dynamics and strong lensing, which aim at disentangling the mass distributions of dark matter and baryons. However, systematic biases arising from constant $M_\star/L$ assumption have not been fully quantified. In this work, we take massive early-type galaxies from the TNG100 simulation to investigate possible systematic biases in the inferences due to a constant $M_\star/L$ assumption. We construct two-component matter density models, where one component describes the dark matter, the other for the stars, which is made to follow the light profile by assuming a constant $M_\star/L$. We fit the two-component model directly to the {\it total} matter density distributions of simulated galaxies to eliminate systematics coming from other model assumptions. We find that galaxies generally have more centrally-concentrated stellar mass profile than their light distribution. Given the light profiles adopted (i.e., single- and double-S{\'e}rsic profiles), the assumption of a constant $M_\star/L$ would artificially break the model degeneracy between baryons and dark matter {\it for non-constant} $M_\star/L$ systems. For such systems, without knowing the true $M_{\star}/L$ but assuming a constant ratio, the two-component modeling procedure tend to generally overestimate $M_{\star}/L$ by $30\%-50\%$, and underestimate the central dark matter fraction $f_{\rm DM}$ by $\sim 20\%$ on average.

astro-ph.GA