arXiv subjects

Shu Wang

Publications and source records attributed to Shu Wang.

At least 91 records · Page 5Linked to original sources

arXiv2025

The Tip of Red Giant Branch Distances to Nearby Dwarf Galaxies WLM and Sextans A with JWST

Distance measurements to extragalactic systems that are both accurate and precise are cornerstones of modern astrophysics, underpinning the calibration of standard candles and the determination of the Hubble constant. Dwarf galaxies, such as Wolf-Lundmark-Melotte (WLM) and Sextans A, provide valuable laboratories for testing distance scales across different stellar populations. In this work, we utilize the high sensitivity and spatial resolution of the James Webb Space Telescope (JWST) to measure the distances to WLM and Sextans A using the tip of the red giant branch (TRGB) method. Adopting the TRGB absolute magnitude calibrated by NGC 4258, we determine distance moduli of $μ_{\mathrm{0,WLM}} = 24.977 \pm 0.018 (\mathrm{stat}) \pm 0.056 (\mathrm{sys})$ mag for WLM and $μ_{\mathrm{0,SexA}} = 25.740 \pm 0.011 (\mathrm{stat}) \pm 0.057 (\mathrm{sys})$ mag for Sextans A. Our results are consistent within a 3% distance uncertainty with previous measurements based on TRGB, Cepheids, and J-Region Asymptotic Giant Branch (JAGB) methods. With improved distance measurements in the future, these two galaxies have the potential to serve as additional anchor points for TRGB calibration, aiming to reduce the TRGB-based distance uncertainty to below 2%.

astro-ph.GA↗

arXiv2025

Period-luminosity and period-luminosity-metallicity relation for $δ$ Scuti Stars

$δ$ Scuti ($δ$ Sct) stars are potential distance tracers for studying the Milky Way structure. We conduct a comprehensive analysis of the period-luminosity (PL) and period-luminosity-metallicity (PLZ) relation for $δ$ Sct stars, integrating data from the Zwicky Transient Facility (ZTF), the Transiting Exoplanet Survey Satellite (TESS), Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST), Apache Point Observatory Galactic Evolution Experiment (APOGEE), and Gaia. To mitigate the impact of the Gaia parallax zero point offset, we applied a correction method, determining the optimal zero point value to be $zp_\varpi = 35 \pm 2 \, μ\text{as}$. Using the three best bands, by varying the parallax error threshold, we found that the total error of the PLR zero point was minimized to 0.9\% at a parallax error threshold of 6\%. With this threshold, we derived the PL and PLZ relation for nine bands (from optical to mid-infrared) and five Wesenheit bands. Through our analysis, we conclude that the influence of metallicity on the PLR of $δ$ Sct stars is not significant, and the differences across various bands are minimal.

astro-ph.SR↗

arXiv2025

DMPT: Decoupled Modality-aware Prompt Tuning for Multi-modal Object Re-identification

Current multi-modal object re-identification approaches based on large-scale pre-trained backbones (i.e., ViT) have displayed remarkable progress and achieved excellent performance. However, these methods usually adopt the standard full fine-tuning paradigm, which requires the optimization of considerable backbone parameters, causing extensive computational and storage requirements. In this work, we propose an efficient prompt-tuning framework tailored for multi-modal object re-identification, dubbed DMPT, which freezes the main backbone and only optimizes several newly added decoupled modality-aware parameters. Specifically, we explicitly decouple the visual prompts into modality-specific prompts which leverage prior modality knowledge from a powerful text encoder and modality-independent semantic prompts which extract semantic information from multi-modal inputs, such as visible, near-infrared, and thermal-infrared. Built upon the extracted features, we further design a Prompt Inverse Bind (PromptIBind) strategy that employs bind prompts as a medium to connect the semantic prompt tokens of different modalities and facilitates the exchange of complementary multi-modal information, boosting final re-identification results. Experimental results on multiple common benchmarks demonstrate that our DMPT can achieve competitive results to existing state-of-the-art methods while requiring only 6.5% fine-tuning of the backbone parameters.

cs.CV↗

arXiv2025

The Binary Fraction of Red Supergiants in the Magellanic Clouds

Red supergiants (RSGs), as the descendants of OB-type stars and the progenitors of supernovae, provide crucial insights into the evolution of massive stars, particularly in binary systems. Previous studies show that the binary fraction of RSGs ($\approx$ 15% - 40%) is significantly lower than that of their predecessors ($\approx$ 50% - 70%). In this work, we investigate the binary fraction of RSGs with the recently selected largest samples of 4695 and 2097 RSGs in the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC), respectively. The binary system with a hot companion (O-, B- and A-type star) is identified by detecting the ultraviolet (UV) excess in the observed spectral energy distribution (SED) ranging from ultraviolet to mid-infrared after subtracting the model SED of RSG since RSGs are very weak in the UV band. It is found that the lower limit of binarity is 30.2% $\pm$ 0.7% and 32.2% $\pm$ 1% in the LMC and SMC, respectively. If the sample is limited to luminous RSGs with log $L/L_{\odot} > 4.0$, the binary fraction becomes 26.6% $\pm$ 1.1% and 26.4% $\pm$ 1.7% in the LMC and SMC, respectively. The derived binary fraction is valid in the range of $\sim$ 2.3 < $\log P / [\text{d}]$ < $\sim$ 8. Our study suggests that roughly one-third of massive stars host a third companion within $\sim$ 30,000 AU. In addition, 15 RSGs are also identified as binary via HST/STIS spectra, and a handful of the binaries identified by the SED fitting are confirmed by their light curve and radial velocity dispersion. The stellar parameters of the companions, i.e. $T_{\mathrm{eff}}$, $R$, $L$ and log $g$, are calculated by model fitting.

astro-ph.SR↗

arXiv2025

A 0.3\% calibration of the W UMa-type contact binary luminosity based on Gaia DR3

W Ursa Majoris (W UMa)-type contact binary systems (CBs) with period--luminosity (PL) relations are valuable distance indicators. The PL relations of CBs are affected by metallicity. Here, we establish PL relations and period--luminosity--metallicity (PLZ) relations in nine bands from optical to mid-infrared ($BP$, $G$, $RP$, $J$, $H$, $K_S$, $W1$, $W2$, $W3$) and in five Wesenheit bands based on Gaia DR3 parallaxes. The dispersion of PLZ relations gradually decreases from the optical to mid-infrared bands, with the minimum dispersion of 0.138 mag. We fit the best PL relations for three bands ($W1$, $W_{G,BP,RP}$, $W_{W1,BP,RP}$) under different parallax uncertainty criteria and determine a parallax (after correction) zero point of $zp_\varpi=24\pm4$ $μ$as. After fixing the parallax zero point, we find that the total zero errors of the PL and PLZ relation are smallest when the parallax uncertainty is less than 2\%, resulting in a calibrated CB luminosity with an accuracy of 0.33\%, which is more accurate than the classical Cepheids. Furthermore, by examining the absolute magnitude residuals in different metallicity intervals, we find that the use of a linear metallicity effect is appropriate for CBs with different metallicities. These results indicate that CBs are excellent standard candles.

astro-ph.SR↗

arXiv2025

ToolGen: Unified Tool Retrieval and Calling via Generation

As large language models (LLMs) advance, their inability to autonomously execute tasks by directly interacting with external tools remains a critical limitation. Traditional methods rely on inputting tool descriptions as context, which is constrained by context length and requires separate, often inefficient, retrieval mechanisms. We introduce ToolGen, a paradigm shift that integrates tool knowledge directly into the LLM's parameters by representing each tool as a unique token. This enables the LLM to generate tool calls and arguments as part of its next token prediction capabilities, seamlessly blending tool invocation with language generation. Our framework allows the LLM to access and utilize a vast amount of tools with no additional retrieval step, significantly enhancing both performance and scalability. Experimental results with over 47,000 tools show that ToolGen not only achieves superior results in both tool retrieval and autonomous task completion but also sets the stage for a new era of AI agents that can adapt to tools across diverse domains. By fundamentally transforming tool retrieval into a generative process, ToolGen paves the way for more versatile, efficient, and autonomous AI systems. ToolGen enables end-to-end tool learning and opens opportunities for integration with other advanced techniques such as chain-of-thought and reinforcement learning, thereby expanding the practical capabilities of LLMs.

cs.CL↗

arXiv2025

Exploring the Evolution of Physics Cognition in Video Generation: A Survey

Recent advancements in video generation have witnessed significant progress, especially with the rapid advancement of diffusion models. Despite this, their deficiencies in physical cognition have gradually received widespread attention - generated content often violates the fundamental laws of physics, falling into the dilemma of ''visual realism but physical absurdity". Researchers began to increasingly recognize the importance of physical fidelity in video generation and attempted to integrate heuristic physical cognition such as motion representations and physical knowledge into generative systems to simulate real-world dynamic scenarios. Considering the lack of a systematic overview in this field, this survey aims to provide a comprehensive summary of architecture designs and their applications to fill this gap. Specifically, we discuss and organize the evolutionary process of physical cognition in video generation from a cognitive science perspective, while proposing a three-tier taxonomy: 1) basic schema perception for generation, 2) passive cognition of physical knowledge for generation, and 3) active cognition for world simulation, encompassing state-of-the-art methods, classical paradigms, and benchmarks. Subsequently, we emphasize the inherent key challenges in this domain and delineate potential pathways for future research, contributing to advancing the frontiers of discussion in both academia and industry. Through structured review and interdisciplinary analysis, this survey aims to provide directional guidance for developing interpretable, controllable, and physically consistent video generation paradigms, thereby propelling generative models from the stage of ''visual mimicry'' towards a new phase of ''human-like physical comprehension''.

cs.CV↗

arXiv2025

Period--Luminosity Relations for Double-mode $δ$ Sct Stars

Previous studies of the Period--Luminosity relations (PLRs) of Delta Scuti ($δ$ Sct) stars have focused on those with a single pulsation mode. However, for $δ$ Sct stars with many different pulsation modes, classifying a single mode is difficult. In this study, an all-sky dataset is constructed using double-mode $δ$ Sct stars from ZTF and OGLE, and is used to determine F-mode and 1O-mode PLRs for eight single bands and six Wesenheit bands. In the $W1$ band, the PLR dispersion is about 0.171 mag and the total zero point error is 1\%. Our results show that to accurately classify the 1O modes of $δ$ Sct stars requires authentication based on multiple modes. Classification based on amplitude alone leads to impure 1O-mode $δ$ Sct stars and significant deviations in the PLRs. We compare the PLRs of the different sequences in the Petersen diagram and find that they are consistent after a strict criterion filtering, suggesting that their evolutionary state is similar. In addition, we find a weak period--metallicity relation for double-mode $δ$ Sct stars, unlike double-mode RR Lyrae stars. As distance tracers, large-amplitude F-mode $δ$ Sct and double-mode $δ$ Sct stars are the most suitable of the $δ$ Sct family.

astro-ph.SR↗

arXiv2025

Sampling Innovation-Based Adaptive Compressive Sensing

Scene-aware Adaptive Compressive Sensing (ACS) has attracted significant interest due to its promising capability for efficient and high-fidelity acquisition of scene images. ACS typically prescribes adaptive sampling allocation (ASA) based on previous samples in the absence of ground truth. However, when confronting unknown scenes, existing ACS methods often lack accurate judgment and robust feedback mechanisms for ASA, thus limiting the high-fidelity sensing of the scene. In this paper, we introduce a Sampling Innovation-Based ACS (SIB-ACS) method that can effectively identify and allocate sampling to challenging image reconstruction areas, culminating in high-fidelity image reconstruction. An innovation criterion is proposed to judge ASA by predicting the decrease in image reconstruction error attributable to sampling increments, thereby directing more samples towards regions where the reconstruction error diminishes significantly. A sampling innovation-guided multi-stage adaptive sampling (AS) framework is proposed, which iteratively refines the ASA through a multi-stage feedback process. For image reconstruction, we propose a Principal Component Compressed Domain Network (PCCD-Net), which efficiently and faithfully reconstructs images under AS scenarios. Extensive experiments demonstrate that the proposed SIB-ACS method significantly outperforms the state-of-the-art methods in terms of image reconstruction fidelity and visual effects. Codes are available at https://github.com/giant-pandada/SIB-ACS_CVPR2025.

cs.CV↗

arXiv2025

Nonreciprocal quantum photon-pair source with chiral ferroelectric nematics

Quantum nonreciprocity-a fundamental phenomenon enabling directional control of quantum states and photon correlations-has long been recognized as pivotal for quantum technologies. However, the experimental realization of nonreciprocal quantum photon-pair generation, as a critical prerequisite for advancing quantum systems, continues to be an outstanding challenge that remains unaddressed in practice. Here, we experimentally implement a highly-efficient nonreciprocal quantum photon source in a micro/nano-scale helical structured nonlinear optical fluid. Intriguing helical quasi-phase matching is achieved by deliberately engineering the pitch of the chiral ferroelectric structure, thus enabling spontaneous parametric down-conversion with record-high brightness (5,801.6 Hz*mW-1, 10,071% enhancement over phase-mismatched systems) and high coincidence-to-accidental ratio, rivaling state-of-the-art centimeter-scale nonlinear crystals. In particular, by tailoring the ferroelectric helix structure with orthogonally aligned head and tail polarization vectors, we demonstrate up to 22.6 dB isolation in biphoton generation coupled with nonreciprocal quantum polarization states, while maintaining classical optical reciprocity. This quantum liquid-crystal-based platform, combining flexible tunability and superior performance of purely quantum nonreciprocity at micro/nano scales, builds a bridge between a wide range of soft-matter systems, nonreciprocal physics, and emerging quantum photonic technologies.

physics.optics↗

arXiv2025

MetricGrids: Arbitrary Nonlinear Approximation with Elementary Metric Grids based Implicit Neural Representation

This paper presents MetricGrids, a novel grid-based neural representation that combines elementary metric grids in various metric spaces to approximate complex nonlinear signals. While grid-based representations are widely adopted for their efficiency and scalability, the existing feature grids with linear indexing for continuous-space points can only provide degenerate linear latent space representations, and such representations cannot be adequately compensated to represent complex nonlinear signals by the following compact decoder. To address this problem while keeping the simplicity of a regular grid structure, our approach builds upon the standard grid-based paradigm by constructing multiple elementary metric grids as high-order terms to approximate complex nonlinearities, following the Taylor expansion principle. Furthermore, we enhance model compactness with hash encoding based on different sparsities of the grids to prevent detrimental hash collisions, and a high-order extrapolation decoder to reduce explicit grid storage requirements. experimental results on both 2D and 3D reconstructions demonstrate the superior fitting and rendering accuracy of the proposed method across diverse signal types, validating its robustness and generalizability. Code is available at https://github.com/wangshu31/MetricGrids}{https://github.com/wangshu31/MetricGrids.

cs.CV↗

arXiv2025

The size of the continuum emission region and its scaling relations with active galactic nucleus luminosity and the broad-line region size

We present a continuum lag analysis for a sample of 37 relatively high-luminosity active galactic nuclei (AGNs) from the Seoul National University AGN Monitoring Project (SAMP), utilizing the light curve data in $B$ and $V$ bands from SAMP and in $g,r,i$ bands from the Zwicky Transient Facility. We find that the inter-band lags ($τ$) increase with wavelength (i.e., $τ\propto λ^{\sim 4/3}$) as prescribed by the standard disk model (SSD), suggesting consistency with the "lamp-post" reprocessing model. We report that the size of the continuum emitting region (CER) normalized at 2500 Å ($R_{2500}$) is a factor of $\sim$5 (i.e, $0.69\pm0.04$ dex) larger than predicted by SSD. By combining our new measurements with the re-measurements of the literature sample, we report a correlation between $R_{2500}$ and AGN continuum luminosity as $R_{2500} \, \propto \, L_{5100}^{0.58\pm0.03}$, which suggests that the observed continuum could be composed of both the disk emission and the diffuse emission from the broad line region (BLR). The size of CER shows a tight relation with the size of H$β$ BLR with a sublinear slope (i.e., $R_{\text{BLR}} \, \propto \, R_{\text{2500}}^{0.87\pm0.07}$) and a scatter of 0.29 dex. This empirical relation offers a promising method for estimating single-epoch black hole masses, once established over a large dynamic range of AGN luminosity.

astro-ph.GA↗

arXiv2025

Explore the Reasoning Capability of LLMs in the Chess Testbed

Reasoning is a central capability of human intelligence. In recent years, with the advent of large-scale datasets, pretrained large language models have emerged with new capabilities, including reasoning. However, these models still struggle with long-term, complex reasoning tasks, such as playing chess. Based on the observation that expert chess players employ a dual approach combining long-term strategic play with short-term tactical play along with language explanation, we propose improving the reasoning capability of large language models in chess by integrating annotated strategy and tactic. Specifically, we collect a dataset named MATE, which consists of 1 million chess positions with candidate moves annotated by chess experts for strategy and tactics. We finetune the LLaMA-3-8B model and compare it against state-of-the-art commercial language models in the task of selecting better chess moves. Our experiments show that our models perform better than GPT, Claude, and Gemini models. We find that language explanations can enhance the reasoning capability of large language models.

cs.CL↗

arXiv2025

The Multi-wavelength Extinction Law and its Variation in the Coalsack Molecular Cloud Based on the Gaia, APASS, SMSS, 2MASS, GLIMPSE, and WISE Surveys

Accurate interpretation of observations relies on the interstellar dust extinction law, which also serves as a powerful diagnostic for probing dust properties. In this study, we investigate the multi-wavelength extinction law of the quiescent, starless molecular cloud Coalsack and explore its potential variation across different interstellar environments: the surrounding region, the nearby high Galactic latitude region, the inner dense region, and the inner diffuse region. Using a sample of 368,524 dwarf stars selected from Gaia DR3 as tracers, we establish the effective temperature Teff-intrinsic color relations to derive the intrinsic color indices and optical-mid-infrared (MIR) color excess (CE) for 20 bands. Linear fits to the CE-CE diagrams provide color excess ratios (CERs), which are subsequently converted into relative extinction. The resulting extinction curves for different environments exhibit steep slopes in the near-infrared (NIR) and flat profiles in the MIR. In the optical-NIR range, the Coalsack extinction law is consistent with R_V = 3.1 while in the MIR it follows R_V= 5.5 similar to the results of active star-forming clouds. At an angular resolution of 1.3', our extinction map reveals fine cloud structures. No correlation is found between R_V and E(B-V) for E(B-V) > 0.3 mag, implying a uniform optical extinction law in the Coalsack cloud. The derived average R_V value is 3.24.

astro-ph.GA↗

arXiv2025

Dependence of Multi-band Absolute Magnitudes and Color Indexes of the Tip of Red Giant Branch Stars on Metallicity in the Galactic Globular Clusters

The tip of red giant branch (TRGB) stars have attracted intensive attention in recent years because their $I$-band absolute magnitudes, $M_\rm I$, are often used for distance calibration in the Hubble constant measurements because of its almost independence on metallicity ([Fe/H]). However, a discrepancy exists between various studies and the theoretical stellar model predicts dependence of their luminosity on [Fe/H]. Here we present a careful study of the dependence of absolute magnitudes and color indexes on metallicity in optical and near-infrared bands. With the TRGB stars identified in 33 Galactic globular clusters by the reddest color in the $G_{\rm BP}-G_{\rm RP}$ vs. $G_{\rm RP}$ diagram, it is confirmed that $M_\rm I$ is almost constant of $-4.017 \pm 0.036 \pm 0.027$ mag when $[\rm Fe/H]<-1.2$, which would give $H_0=70.86\pm 1.2\pm0.9$ $\rm kms^{-1} Mp c^{-1}$ with this updated luminosity calibration for type Ia supernovae. However, for $[\rm Fe/H]>-1.2$, $M_\rm I$ is found to become fainter with lower metallicity, which would lead to a larger Hubble constant. In the optical $G_{\rm BP}, G_{\rm RP}$ and $V$ bands, the absolute magnitude of TRGB stars tends to increase with metallicity, while in the infrared $J, H$, and $K_{\rm S}$ bands, the variation with metallicity shows an inverse tendency. In addition, the analytical relations of the color indexes with metallicity are presented, which have smaller dispersion than those derived for the corresponding absolute magnitudes.

astro-ph.SR↗

arXiv2025

TYPEPULSE: Detecting Type Confusion Bugs in Rust Programs

Rust supports type conversions and safe Rust guarantees the security of these conversions through robust static type checking and strict ownership guidelines. However, there are instances where programmers need to use unsafe Rust for certain type conversions, especially those involving pointers. Consequently, these conversions may cause severe memory corruption problems. Despite extensive research on type confusion bugs in C/C++, studies on type confusion bugs in Rust are still lacking. Also, due to Rust's new features in the type system, existing solutions in C/C++ cannot be directly applied to Rust. In this paper, we develop a static analysis tool called TYPEPULSE to detect three main categories of type confusion bugs in Rust including misalignment, inconsistent layout, and mismatched scope. TYPEPULSE first performs a type conversion analysis to collect and determine trait bounds for type pairs. Moreover, it performs a pointer alias analysis to resolve the alias relationship of pointers. Following the integration of information into the property graph, it constructs type patterns and detects each type of bug in various conversion scenarios. We run TYPEPULSE on the top 3,000 Rust packages and uncover 71 new type confusion bugs, exceeding the total number of type confusion bugs reported in RUSTSEC over the past five years. We have received 32 confirmations from developers, along with one CVE ID and six RUSTSEC IDs.

cs.CR↗

arXiv2025

Three Brown Dwarfs Masquerading as High-Redshift Galaxies in JWST Observations

We report the spectroscopic identification of three brown dwarf candidates -- o005_s41280, o006_s00089, and o006_s35616 -- discovered in the RUBIES using James Webb Space Telescope (JWST) Near-Infrared Spectrograph (NIRSpec) PRISM/CLEAR spectroscopy. We fit these sources with multiple substellar atmosphere models and present the atmospheric parameters, including effective temperature ($T_\mathrm{eff}$), surface gravity, and other derived properties. The results suggest that o005_s41280 and o006_s35616, with $T_\mathrm{eff}$ in the ranges of 2100--2300 K and 1800--2000 K, are likely L dwarfs, while o006_s00089, with $T_\mathrm{eff} < 1000$ K, is consistent with a late T dwarf classification. The best-fit model spectra provide a reasonable match to the observed spectra. However, distinct residuals exist in the $Y$, $J$, and $H$ bands for the two L dwarf candidates, particularly for o006_s35616. Incorporating the extinction parameter into the fitting process can significantly reduce these residuals. The distance estimates indicate that these candidates are about 2 kpc away. The analysis of the color-color diagram using multiple JWST NIRcam photometry suggests that cooler T dwarfs, such as o006_s00089, overlap with little red dots (LRDs), while hotter L dwarfs, like o005_s41280 and o006_s35616, tend to contaminate the high-redshift galaxy cluster. These findings suggest a brown dwarf contamination rate of approximately 0.1% in extragalactic deep field surveys, with L dwarfs being more frequently detected than cooler T and Y dwarfs.

astro-ph.SR↗

arXiv2025

ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono

Recently, the integration of advanced simulation technologies with artificial intelligence (AI) is revolutionizing science and engineering research. ChronoLlama introduces a novel framework that customizes the open-source LLMs, specifically for code generation, paired with PyChrono for multi-physics simulations. This integration aims to automate and improve the creation of simulation scripts, thus enhancing model accuracy and efficiency. This combination harnesses the speed of AI-driven code generation with the reliability of physics-based simulations, providing a powerful tool for researchers and engineers. Empirical results indicate substantial enhancements in simulation setup speed, accuracy of the generated codes, and overall computational efficiency. ChronoLlama not only expedites the development and testing of multibody systems but also spearheads a scalable, AI-enhanced approach to managing intricate mechanical simulations. This pioneering integration of cutting-edge AI with traditional simulation platforms represents a significant leap forward in automating and optimizing design processes in engineering applications.

cs.SE↗