arXiv subjects

Weixiang Sun

Publications and source records attributed to Weixiang Sun.

36 records · Page 2Linked to original sources

arXiv2025

The Kinematic Signature of the Warp and Waves in the Milky Way Disk

Using over 170,000 red clump (RC) stars selected from LAMOST and APOGEE, we conduct a detailed analysis of the stellar $V_{Z}$ as a function of $L_{Z}$ (or $R_{g}$) across different $ϕ$ bins for various disk populations. The $V_{Z}$ of the whole RC sample stars exhibits a wave-like pattern superimposed on an exponentially increasing trend, indicating the contribution from disk warp, disk flare and disk waves. Our results across various populations suggest that the thin disk is similar to the whole RC sample behavior, while the thick disk displays a wave-like pattern superimposed on a linearly increasing trend, meaning that the features of disk warp and waves are present in both thin and thick disks, and the disk flare feature is only present in the thin disk. These results indicate that the disk warp is potentially driven by secular processes like disk perturbations from intergalactic magnetic fields and a misaligned dark halo. The line-of-node of the disk warp of various populations displays a slight difference, with $ϕ_{0}$ = 5.68 $\pm$ 2.91 degree for the whole RC sample stars, $ϕ_{0}$ = 5.78 $\pm$ 2.89 degree for the thin disk stars, and $ϕ_{0}$ = 4.10 $\pm$ 3.43 degree for the thick disk stars.

astro-ph.GA↗

arXiv2025

AdvLogo: Adversarial Patch Attack against Object Detectors based on Diffusion Models

With the rapid development of deep learning, object detectors have demonstrated impressive performance; however, vulnerabilities still exist in certain scenarios. Current research exploring the vulnerabilities using adversarial patches often struggles to balance the trade-off between attack effectiveness and visual quality. To address this problem, we propose a novel framework of patch attack from semantic perspective, which we refer to as AdvLogo. Based on the hypothesis that every semantic space contains an adversarial subspace where images can cause detectors to fail in recognizing objects, we leverage the semantic understanding of the diffusion denoising process and drive the process to adversarial subareas by perturbing the latent and unconditional embeddings at the last timestep. To mitigate the distribution shift that exposes a negative impact on image quality, we apply perturbation to the latent in frequency domain with the Fourier Transform. Experimental results demonstrate that AdvLogo achieves strong attack performance while maintaining high visual quality.

cs.CV↗

arXiv2025

The Age-velocity Dispersion Relations of the Galactic Disk as Revealed by the LAMOST-Gaia Red Clump Stars

Using nearly 230,000 red clump (RC) stars selected from LAMOST and Gaia, we conduct a comprehensive analysis of the stellar age-velocity dispersion relations (AVRs) for various disk populations, within 5.0 $\leq$ $R$ $\leq$ 15.0 kpc and $|Z|$ $\leq$ 3.0 kpc. The AVRs of the whole RC sample stars are accurately described as $σ_{v}$ = $σ_{v,0}$ ($τ$ + 0.1)$^{β_{v}}$, with $β_{R}$, $β_ϕ$ and $β_{Z}$ displaying a global exponential decreasing trend with $R$, which may point to the difference in spatial distributions of various disk heating mechanisms. The measurements of $β$ $-$ $R$ for various disks suggest that the thin disk exhibits a radial dependence, with a global exponential decreasing trend in $β_{R}$ $-$ $R$ and $β_{Z}$ $-$ $R$, while $β_ϕ$ remains a nearly constant value (around 0.20$\sim$0.25) within 8.5 $\leq$ $R$ $\leq$ 11.5 kpc. The thick disk displays a global increasing trend in $β_{R}$ $-$ $R$, $β_ϕ$ $-$ $R$ and $β_{Z}$ $-$ $R$. These results indicate that the thin disk stars are likely heated by long-term heating from GMCs and spiral arms, while thick disk stars are likely heated by some violent heating process from merger and accretion, and/or formed by the inside-out and upside-down star formation scenarios, and/or born in the chaotic mergers of gas-rich systems and/or turbulent ISM. Our results also suggest that the disk perturbation by a recent minor merger from Sagittarius may have occurred within 3.0 Gyr.

astro-ph.GA↗

arXiv2024

The Galactic Disk North-south Asymmetry in Metallicity May Be A New Tracer for the Disk Warp

Galactic disk warp has been widely characterized by stellar distributions and stellar kinematics but has not been traced by stellar chemistry. Here, we use a sample with over 170,000 red clump (RC) stars selected from LAMOST and APOGEE first to establish a correlation between the north-south asymmetry in metallicity ([Fe/H]) and the disk warp. Our results indicate that the height of the [Fe/H] mid-plane for the whole RC sample stars is accurately described as $Z_{w}$ = 0.017 ($R$ $-$ 7.112)$^{2}$ sin($ϕ$ $-$ 9.218). This morphology aligns closely with the warp traced by Cepheids, suggesting that the disk north-south asymmetry in [Fe/H] may serve as a new tracer for the Galactic warp. Our detailed analysis of the young/thin disk stars of this RC sample suggests that its warp is well-modeled as $Z_{w}$ = 0.016 ($R$ $-$ 6.507)$^{2}$ sin($ϕ$ $-$ 4.240), indicating that the line of node (LON) of the Galactic warp is oriented at 4.240$_{-1.747}^{+1.641}$ degree.

astro-ph.GA↗

arXiv2024

TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation

Biomedical image segmentation is crucial for accurately diagnosing and analyzing various diseases. However, Convolutional Neural Networks (CNNs) and Transformers, the most commonly used architectures for this task, struggle to effectively capture long-range dependencies due to the inherent locality of CNNs and the computational complexity of Transformers. To address this limitation, we introduce TTT-Unet, a novel framework that integrates Test-Time Training (TTT) layers into the traditional U-Net architecture for biomedical image segmentation. TTT-Unet dynamically adjusts model parameters during the testing time, enhancing the model's ability to capture both local and long-range features. We evaluate TTT-Unet on multiple medical imaging datasets, including 3D abdominal organ segmentation in CT and MR images, instrument segmentation in endoscopy images, and cell segmentation in microscopy images. The results demonstrate that TTT-Unet consistently outperforms state-of-the-art CNN-based and Transformer-based segmentation models across all tasks. The code is available at https://github.com/rongzhou7/TTT-Unet.

eess.IV↗

arXiv2024

Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?

Large Language Models (LLMs) are increasingly employed for simulations, enabling applications in role-playing agents and Computational Social Science (CSS). However, the reliability of these simulations is under-explored, which raises concerns about the trustworthiness of LLMs in these applications. In this paper, we aim to answer ``How reliable is LLM-based simulation?'' To address this, we introduce TrustSim, an evaluation dataset covering 10 CSS-related topics, to systematically investigate the reliability of the LLM simulation. We conducted experiments on 14 LLMs and found that inconsistencies persist in the LLM-based simulated roles. In addition, the consistency level of LLMs does not strongly correlate with their general performance. To enhance the reliability of LLMs in simulation, we proposed Adaptive Learning Rate Based ORPO (AdaORPO), a reinforcement learning-based algorithm to improve the reliability in simulation across 7 LLMs. Our research provides a foundation for future studies to explore more robust and trustworthy LLM-based simulations.

cs.CL↗

arXiv2024

Mora: Enabling Generalist Video Generation via A Multi-Agent Framework

Text-to-video generation has made significant strides, but replicating the capabilities of advanced systems like OpenAI Sora remains challenging due to their closed-source nature. Existing open-source methods struggle to achieve comparable performance, often hindered by ineffective agent collaboration and inadequate training data quality. In this paper, we introduce Mora, a novel multi-agent framework that leverages existing open-source modules to replicate Sora functionalities. We address these fundamental limitations by proposing three key techniques: (1) multi-agent fine-tuning with a self-modulation factor to enhance inter-agent coordination, (2) a data-free training strategy that uses large models to synthesize training data, and (3) a human-in-the-loop mechanism combined with multimodal large language models for data filtering to ensure high-quality training datasets. Our comprehensive experiments on six video generation tasks demonstrate that Mora achieves performance comparable to Sora on VBench, outperforming existing open-source methods across various tasks. Specifically, in the text-to-video generation task, Mora achieved a Video Quality score of 0.800, surpassing Sora 0.797 and outperforming all other baseline models across six key metrics. Additionally, in the image-to-video generation task, Mora achieved a perfect Dynamic Degree score of 1.00, demonstrating exceptional capability in enhancing motion realism and achieving higher Imaging Quality than Sora. These results highlight the potential of collaborative multi-agent systems and human-in-the-loop mechanisms in advancing text-to-video generation. Our code is available at \url{https://github.com/lichao-sun/Mora}.

cs.CV↗

arXiv2024

Biomedical SAM 2: Segment Anything in Biomedical Images and Videos

Medical image segmentation and video object segmentation are essential for diagnosing and analyzing diseases by identifying and measuring biological structures. Recent advances in natural domain have been driven by foundation models like the Segment Anything Model 2 (SAM-2). To explore the performance of SAM-2 in biomedical applications, we designed three evaluation pipelines for single-frame 2D image segmentation, multi-frame 3D image segmentation and multi-frame video segmentation with varied prompt designs, revealing SAM-2's limitations in medical contexts. Consequently, we developed BioSAM-2, an enhanced foundation model optimized for biomedical data based on SAM-2. Our experiments show that BioSAM-2 not only surpasses the performance of existing state-of-the-art foundation models but also matches or even exceeds specialist models, demonstrating its efficacy and potential in the medical domain.

cs.CV↗

arXiv2024

Bora: Biomedical Generalist Video Generation Model

Generative models hold promise for revolutionizing medical education, robot-assisted surgery, and data augmentation for medical AI development. Diffusion models can now generate realistic images from text prompts, while recent advancements have demonstrated their ability to create diverse, high-quality videos. However, these models often struggle with generating accurate representations of medical procedures and detailed anatomical structures. This paper introduces Bora, the first spatio-temporal diffusion probabilistic model designed for text-guided biomedical video generation. Bora leverages Transformer architecture and is pre-trained on general-purpose video generation tasks. It is fine-tuned through model alignment and instruction tuning using a newly established medical video corpus, which includes paired text-video data from various biomedical fields. To the best of our knowledge, this is the first attempt to establish such a comprehensive annotated biomedical video dataset. Bora is capable of generating high-quality video data across four distinct biomedical domains, adhering to medical expert standards and demonstrating consistency and diversity. This generalist video generative model holds significant potential for enhancing medical consultation and decision-making, particularly in resource-limited settings. Additionally, Bora could pave the way for immersive medical training and procedure planning. Extensive experiments on distinct medical modalities such as endoscopy, ultrasound, MRI, and cell tracking validate the effectiveness of our model in understanding biomedical instructions and its superior performance across subjects compared to state-of-the-art generation models.

cs.CV↗

arXiv2024

Medical Unlearnable Examples: Securing Medical Data from Unauthorized Training via Sparsity-Aware Local Masking

The rapid expansion of AI in healthcare has led to a surge in medical data generation and storage, boosting medical AI development. However, fears of unauthorized use, like training commercial AI models, hinder researchers from sharing their valuable datasets. To encourage data sharing, one promising solution is to introduce imperceptible noise into the data. This method aims to safeguard the data against unauthorized training by inducing degradation in the generalization ability of the trained model. However, they are not effective and efficient when applied to medical data, mainly due to the ignorance of the sparse nature of medical images. To address this problem, we propose the Sparsity-Aware Local Masking (SALM) method, a novel approach that selectively perturbs significant pixel regions rather than the entire image as previously. This simple yet effective approach, by focusing on local areas, significantly narrows down the search space for disturbances and fully leverages the characteristics of sparsity. Our extensive experiments across various datasets and model architectures demonstrate that SALM effectively prevents unauthorized training of different models and outperforms previous SoTA data protection methods.

eess.IV↗

arXiv2024

On the chemical and kinematic signatures of the resonances of the Galactic bar as revealed by the LAMOST-APOGEE red clump stars

The Milky Way is widely considered to exhibit features of a rotational bar or quadrupole bar. In either case, the feature of the resonance of the Galactic bar should be present in the properties of the chemistry and kinematics, over a large area of the disk. With a sample of over 170,000 red clump (RC) stars from LAMOST-APOGEE data, we attempt to detect the chemical and kinematic signatures of the resonances of the Galactic bar, within 4.0 $\leq$ $R$ $\leq$ 15.0 kpc and $|Z|$ $\leq$ 3.0 kpc. The measurement of the $Δ$[Fe/H]/$Δ|Z|$ $-$ $R$ with subtracted the global profiles trends, shows that the thin and thick disks values are Cor_$Δ$[Fe/H]/$Δ|Z|$ = 0.010 $\mathrm{sin}$ (1.598 $R$ + 2.551) and Cor_$Δ$[Fe/H]/$Δ|Z|$ = 0.006 $\mathrm{sin}$ (1.258 $R$ $-$ 0.019), respectively. The analysis of the tilt angle of the velocity ellipsoid indicates that the thin and thick disks are accurately described as $α$ = $α_{0}$ arctan (Z/R), with $α_{0}$ = 0.198 $\mathrm{sin}$ (0.853 $R$ + 1.982) + 0.630 and $α_{0}$ = 0.220 $\mathrm{sin}$ (0.884 $R$ + 2.012) + 0.679 for thin and thick disks, respectively. These periodic oscillations in Cor_$Δ$[Fe/H]/$Δ|Z|$ and $α_{0}$ with $R$ appear in both thin and thick disks, are the most likely chemical and kinematic signatures of the resonance of the Galactic bar. The difference in the phase of the functions of the fitted periodic oscillations for the thin and thick disks may be related to the presence of a second Galactic bar.

astro-ph.GA↗

arXiv2024

Mapping the Chemo-dynamics of the Galactic disk using the LAMOST and APOGEE red clump stars

A detailed measurement is made of the metallicity distributions, kinematics and dynamics of the thin and thick disks, across a large disk volume (5.0 $\leq$ $R$ $\leq$ 15.0 kpc and $|Z|$ $\leq$3.0 kpc), by using the LAMOST-APOGEE red clump stars. The metallicity distributions results show that the radial metallicity gradient $Δ$[Fe/H]/$Δ$R of the thin disk weakens with $|Z|$ from $-$0.06 dex kpc$^{-1}$ at around $|Z|$ $<$ 0.25 kpc to $-$0.02 dex kpc$^{-1}$ at around $|Z|$ $>$ 2.75 kpc, while the thick disk displays a global weak positive $Δ$[Fe/H]/$Δ$R, generally weaker than 0.01 dex kpc$^{-1}$. The vertical metallicity gradient $Δ$[Fe/H]/$Δ|Z|$ weakened steadily from $-$0.36 dex kpc$^{-1}$ at $R$ $\sim$ 5.5 kpc to $-$0.05 dex kpc$^{-1}$ at around R $>$ 11.5 kpc for the thin disk, while the thick disk presents an almost constant value (nearly $-$0.06 $\sim$ $-$0.08 dex kpc$^{-1}$) for all the $R$ bins. These results indicate the contribution of the radial migration to the disk evolution, and the obvious north-south asymmetry in [Fe/H] may be linked to the disk warp and/or the disk perturbation events. The oscillations of the corrected $Δ$[Fe/H]/$Δ|Z|$ with $R$ are likely because of the resonances with the Galactic Bar. Our detailed measurements of $Δ$V$_ϕ$/$Δ$[Fe/H] indicate an "inside-out" and "upside-down" star formation scenario for the thick disk. The results of eccentricity distributions and [$α$/Fe]--velocity dispersion relations are likely to suggest that the thick disk stars require an obvious contribution from other heating mechanisms such as merger and accretion, or born in the chaotic mergers of gas-rich systems and/or turbulent interstellar medium.

astro-ph.GA↗

arXiv2024

Mapping the Galactic disk with the LAMOST and Gaia Red clump sample: VIII: Mapping the kinematics of the Galactic disk using mono-age and mono-abundance stellar populations

We present a comprehensive study of the kinematic properties of the different Galactic disk populations, as defined by the chemical abundance ratios and stellar ages, across a large disk volume (4.5 $\leq$ R $\leq$ 15.0 kpc and $|Z|$ $\leq$ 3.0 kpc), by using the LAMOST-Gaia red clump sample stars. We determine the median velocities for various spatial and population bins, finding large-scale bulk motions, such as the wave-like behavior in radial velocity, the north-south discrepancy in azimuthal velocity and the warp signal in vertical velocity, and the amplitudes and spatial-dependences of those bulk motions show significant variations for different mono-age and mono-abundance populations. The global spatial behaviors of the velocity dispersions clearly show a signal of spiral arms and, a signal of the disk perturbation event within 4 Gyr, as well as the disk flaring in the outer region (i.e., $R \ge 12$ kpc) mostly for young or alpha-poor stellar populations. Our detailed measurements of age/[$α$/Fe]-velocity dispersion relations for different disk volumes indicate that young/$α$-poor populations are likely originated from dynamically heated by both giant molecular clouds and spiral arms, while old/$α$-enhanced populations require an obvious contribution from other heating mechanisms such as merger and accretion, or born in the chaotic mergers of gas-rich systems and/or turbulent interstellar medium.

astro-ph.GA↗

arXiv2023

The tilt of the velocity ellipsoid of different Galactic disk populations

The tilt of the velocity ellipsoid is a helpful tracer of the gravitational potential of the Milky Way. In this paper, we use nearly 140,000 RC stars selected from the LAMOST and Gaia to make a detailed analysis of the tilt of the velocity ellipsoid for various populations, as defined by the stellar ages and chemical information, within 4.5 $\leq$ $R$ $\leq$ 15.0 kpc and $|Z|$ $\leq$ 3.0 kpc. The tilt angles of the velocity ellipsoids of the RC sample stars are accurately described as $α$ = $α_{0}$ $\mathrm{arctan}$ ($Z$/$R$) with $α_{0}$ = (0.68 $\pm$ 0.05). This indicates the alignment of velocity ellipsoids is between cylindrical and spherical, implying that any deviation from the spherical alignment of the velocity ellipsoids may be caused by the gravitational potential of the baryonic disk. The results of various populations suggest that the $α_{0}$ displays an age and population dependence, with the thin and thick disks respectively values $α_{0}$ = (0.72 $\pm$ 0.08) and $α_{0}$ = (0.64 $\pm$ 0.07), and the $α_{0}$ displays a decreasing trend with age (and [$α$/Fe]) increases, meaning that the velocity ellipsoids of the kinematically relaxed stars are mainly dominated by the gravitational potential of the baryonic disk. We determine the $α_{0} - R$ for various populations, finding that the $α_{0}$ displays oscillations with $R$ for all the different populations. The oscillations in $α_{0}$ appear in both kinematically hot and cold populations, indicating that resonances with the Galactic bar are the most likely origin for these oscillations.

astro-ph.GA↗

arXiv2022

Estimating accurate reddening values of LAMOST M dwarfs

M dwarfs are the dominating type of stars in the solar neighbourhood. They serve as excellent tracers for the study of the distribution and properties of the nearby interstellar dust. In this work, we aim to obtain high accuracy reddening values of M dwarf stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release 8 (DR8). Combining the LAMOST spectra with the high-quality optical photometry from the Gaia Early Data Release 3 (Gaia EDR3), we have estimated the reddening values $E(G_{\rm BP}-G_{\rm RP})$ of 641,426 M dwarfs with the machine-learning algorithm Random Forest regression. The typical reddening uncertainty is only 0.03 mag in $E(G_{\rm BP}-G_{\rm RP})$. We have obtained the reddening coefficient $R_{(G_{\rm BP}-G_{\rm RP})}$, which is a function of the stellar intrinsic colour $(G_{\rm BP}-G_{\rm RP})_0$ and reddening value $E(B-V)$. The values of $E(B-V)$ are also provided for the individual stars in our catalogue. Our resultant high accuracy reddening values of M dwarfs, combined with the Gaia parallaxes, will be very powerful to map the fine structures of the dust in the solar neighbourhood.

astro-ph.SR↗

arXiv2020

Discovery of A candidate Hypervelocity star originated from the Sagittarius Dwarf Spheroidal galaxy

In this letter, we report the discovery of an intriguing HVS (J1443+1453) candidate that is probably from the Sagittarius Dwarf Spheroidal galaxy (Sgr dSph). The star is an old and very metal-poor low-mass main-sequence turn-off star (age $\sim14.0$ Gyr and [Fe/H] $= -2.23$ dex) and has a total velocity of $559.01^{+135.07}_{-87.40}$ km s$^{-1}$ in the Galactic rest-frame and a heliocentric distance of $2.90^{+0.72}_{-0.48}$ kpc. The velocity of J1443+1453 is larger than the escape speed at its position, suggesting it a promising HVS candidate. By reconstructing its trajectory in the Galactic potential, we find that the orbit of J1443+1453 intersects closely with that of the Sgr dSph $37.8^{+4.6}_{-6.0}$ Myr ago, when the latter has its latest pericentric passage through the Milky Way. The encounter occurs at a distance $2.42^{+1.80}_{-0.77}$ kpc from the centre of Sgr dSph, smaller than the size of the Sgr dSph. Chemical properties of this star are also consistent with those of one Sgr dSph associated globular cluster or of the Sgr stream member stars. Our finding suggests that J1443+1453 is an HVS either tidally stripped from the Sgr dSph or ejected from the Sgr dSph by the gravitational slingshot effect, requiring a (central) massive/intermediate-mass black hole or a (central) massive primordial black hole in the Sgr dSph.

astro-ph.GA↗

arXiv2020

Mapping the Galactic disk with the LAMOST and $Gaia$ Red clump sample: V: On the origin of the "young" [$α$/Fe]-enhanced stars

Using a sample of nearly 140,000 primary red clump stars selected from the LAMOST and $Gaia$ surveys, we have identified a large sample of "young" [$α$/Fe]-enhanced stars with stellar ages younger than 6.0 Gyr and [$α$/Fe] ratios greater than 0.15 dex. The stellar ages and [$α$/Fe] ratios are measured from LAMOST spectra, using a machine learning method trained with common stars in the LAMOST-APOGEE fields (for [$α$/Fe]) and in the LAMOST-$Kepler$ fields (for stellar age). The existence of these "young" [$α$/Fe]-enhanced stars is not expected from the classical Galactic chemical evolution models. To explore their possible origins, we have analyzed the spatial distribution, and the chemical and kinematic properties of those stars and compared the results with those of the chemically thin and thick disk populations. We find that those "young" [$α$/Fe]-enhanced stars have distributions in number density, metallicity, [C/N] abundance ratio, velocity dispersion and orbital eccentricity that are essentially the same as those of the chemically thick disk population. Our results clearly show those so-called "young" [$α$/Fe]-enhanced stars are not really young but $genuinely$ $old$. Although other alternative explanations can not be fully ruled out, our results suggest that the most possible origin of these old stars is the result of stellar mergers or mass transfer.

astro-ph.GA↗

arXiv2020

Mapping the Galactic disk with the LAMOST and Gaia Red clump sample: I: precise distances, masses, ages and 3D velocities of $\sim$ 140000 red clump stars

We present a sample of $\sim$ 140,000 primary red clump (RC) stars of spectral signal-to-noise ratios higher than 20 from the LAMOST Galactic spectroscopic surveys, selected based on their positions in the metallicity-dependent effective temperature--surface gravity and color--metallicity diagrams, supervised by high-quality $Kepler$ asteroseismology data. The stellar masses and ages of those stars are further determined from the LAMOST spectra, using the Kernel Principal Component Analysis method, trained with thousands of RCs in the LAMOST-$Kepler$ fields with accurate asteroseismic mass measurements. The purity and completeness of our primary RC sample are generally higher than 80 per cent. For the mass and age, a variety of tests show typical uncertainties of 15 and 30 per cent, respectively. Using over ten thousand primary RCs with accurate distance measurements from the parallaxes of Gaia DR2, we re-calibrate the $K_{\rm s}$ absolute magnitudes of primary RCs by, for the first time, considering both the metallicity and age dependencies. With the the new calibration, distances are derived for all the primary RCs, with a typical uncertainty of 5--10 per cent, even better than the values yielded by the Gaia parallax measurements for stars beyond 3--4 kpc. The sample covers a significant volume of the Galactic disk of $4 \leq R \leq 16$ kpc, $|Z| \leq 5$ kpc, and $-20 \leq ϕ\leq 50^{\circ}$. Stellar atmospheric parameters, line-of-sight velocities and elemental abundances derived from the LAMOST spectra and proper motions of Gaia DR2 are also provided for the sample stars. Finally, the selection function of the sample is carefully evaluated in the color-magnitude plane for different sky areas. The sample is publicly available.

astro-ph.SR↗