arXiv subjects

Jingwen Wu

Publications and source records attributed to Jingwen Wu.

At least 19 recordsLinked to original sources

arXiv2026

Low Star Formation Efficiency in M31: Evidence for a Deficit of Bound Gas

The Andromeda galaxy (M31) exhibits a systematically low star formation efficiency (SFE) compared to other star-forming galaxies. Star formation is thought to be regulated by the mass of gravitationally bound gas. To investigate whether the low SFE in M31 originates from a scarcity of such bound gas, we analyze the dynamical state of its giant molecular cloud (GMC) population by estimating their virial parameters ($α_{\rm vir}$). Using a JCMT-SCUBA2 850 micron dust-continuum GMC catalog as the parent sample, we combine it with IRAM 30 m CO(1-0) data to define a working sample of 173 GMCs and derive their kinematic properties. Most analyzed GMCs exhibit high $α_{\rm vir}$, indicating that they are predominantly gravitationally unbound at the approximately 86 pc resolution of our observations. While no statistically significant global correlation is found between SFE and $α_{\rm vir}$ for the full cloud sample, the upper quantiles of the SFE distribution show progressively stronger negative trends with increasing $α_{\rm vir}$. This upper-tail trend may arise from the combined effects of the virial parameter limiting the upper range of SFE values accessible to the GMC population and feedback-driven disruption reducing the number of high-SFE, high-$α_{\rm vir}$ CO-bright clouds in the observed sample. The substantial scatter in the SFE-$α_{\rm vir}$ plane likely reflects the diverse evolutionary stages of GMCs, the temporal mismatch between gas and star formation tracers, and the limitations of a cloud-averaged virial parameter as a tracer of internal dynamical structure, making a simple one-to-one correspondence between $α_{\rm vir}$ and instantaneous SFE difficult to recover for individual GMCs.

astro-ph.GA↗

arXiv2026

Hessian-based photometric substructure as an evolutionary tracer of OB cluster candidates in M31

Using \textit{Hubble Space Telescope} images from the PHAT and PHAST surveys, we construct an updated catalogue of 747 OB cluster (OBC) candidates. We introduce a dimensionless structural metric, the trace coefficient of variation ($CV_{\rm tr}$), derived from the Hessian matrix in four \textit{HST} bands, to quantify the internal photometric substructure of partially resolved OBC candidates. Cross-matching with the subset of M31 clusters that have independent colour--magnitude diagram (CMD) age estimates yields 247 objects in common. We find statistically significant anti-correlations between $CV_{\rm tr}$ and age in the UV and blue bands, suggesting a progressive smoothing of the light distribution as clusters evolve. Bootstrap resampling confirms the robustness of these trends. Forward modelling of synthetic clusters analysed with the same pipeline recovers a monotonic $CV_{\rm tr}$--age relation under simplified but physically motivated assumptions. These results show that second-order photometric structure contains measurable evolutionary information within the CMD-calibrated regime ($\sim10$--300~Myr).

astro-ph.GA↗

arXiv2026

Dense Cores in the Vicinity of an HII Region

Massive stars strongly influence their surroundings through radiative and mechanical feedback, but its effects on dense gas structures at sub-pc scales remain poorly constrained. We investigate how feedback from a newly formed massive star affects dense cores in the filamentary molecular cloud IRAS 18530+0215. We analyze ALMA Band 6 observations of 1.3 mm dust continuum and DCN, N$_2$D$^+$, and $^{13}$CS line emission, together with VLA K-band continuum and NH$_3$ observations. Dense cores are identified with astrodendro, and their temperatures, masses, velocity dispersions, and virial parameters are derived. The dynamical state of the ultra-compact H II region is examined through energy and pressure estimates. The H II region has a radius of $\sim$0.1 pc and an expansion velocity of $\sim$2.5 km s$^{-1}$, corresponding to a shell dynamical age of $\sim$0.06 Myr. DCN and $^{13}$CS cores are concentrated near the H II region, whereas N$_2$D$^+$ cores preferentially lie farther away. Core temperatures and velocity dispersions decrease with projected distance from the H II region. Virial parameters increase within the inner $\sim$0.3 pc but decline sharply beyond this scale, while core masses show no significant trend with distance. Strong star formation signatures are found at $\sim$0.2 pc, whereas more distant regions still host quiescent, cold dense cores. The compact H II region appears trapped or choked within $\sim$0.1 pc, while its feedback extends to at least $\sim$0.3 pc. Within this region, feedback enhances core velocity dispersions, gas temperatures, and virial parameters, with no evidence that it promotes the formation of more massive dense cores.

astro-ph.GA↗

arXiv2026

XRFix: Exploring Performance Bug Repair of Extended Reality Applications with Large Language Models

As an emerging technology, Extended Reality provides end-users with an immersive experience of interacting with virtual and physical environments. Unlike traditional software, the execution of XR applications involves more computationally complex operations, such as 3D scene rendering, real-time animation, and process simulations. Inefficient coding practices during the software development of XR applications may cause various performance bugs, degrading user experience and even causing motion sickness. Thus, it is an urgent need to develop an automated program repair framework for fixing performance bugs in complex XR programs. However, it is non-trivial to achieve this goal due to several technical challenges: (1) a lack of a real-world XR codebase and bug dataset, (2) no accurate bug detection tool, and (3) no effective bug-fixing tool designed for XR performance bugs. To tackle these challenges, we present a novel large language model-based framework, namely XRFix, to repair performance bugs for open-source XR programs. We first construct a corpus of domain-specific performance bugs built with a codebase from 23 open-source XR projects and a dataset of XR-related bugs containing 104 real-world bugs. Then, we tailor two static analysis tools for accurately detecting bugs in both C# scripts and asset files. Last, we design different prompts to instruct LLMs to fix XR bugs in three types of bug scenarios with different complexities, i.e., single-line level, function level, and class level. We conduct extensive experiments on five off-the-shelf LLMs to evaluate the bug-fixing performance of XRFix. We also compare our XRFix with three SOTA APR approaches. Through static analysis, reference answer comparison, and manual inspection, we demonstrate that our XRFix can effectively fix XR bugs, outperforming SOTA APR methods.

cs.SE↗

arXiv2026

ALOHA IRDCs Molecular Line Follow-up: I. Gas properties and kinematics

Infrared Dark Clouds are ideal sites for investigating the initial conditions of massive star and cluster formation. The A Lei Of the Habitat and Assembly of Infrared Dark Clouds (ALOHA IRDCs), a James Clerk Maxwell Telescope (JCMT) Large Program, has mapped nearby IRDCs with SCUBA-2. Complementary molecular line observations are needed to characterise the physical, kinematic, and chemical properties of the dense gas. We aim to determine the thermal, kinematic, and chemical properties of clumps identified in the ALOHA IRDCs, and to assess their evolutionary status and level of star-forming activity. We performed single-pointing K-band and W-band observations towards 56 ALOHA IRDCs clumps using the Effelsberg 100-m and Yebes 40-m telescopes, respectively. We derived NH3 kinetic temperatures using the hyperfine group ratio (HFGR) method and identified infall and shock signatures from HCO+, H13CO+, SiO, and HNCO profiles. Water masers and NH2D emission were used as complementary tracers of chemical evolution and star formation. The clumps exhibit kinetic temperatures of 15-29 K. We detect NH2D emission towards 18 sources, with NH2D centroid velocities consistent with NH3, indicating both species trace the same dense gas component. More than half of the clumps display blue-asymmetric HCO+ profiles, identifying them as infall candidates. Water masers are detected in 22 sources, with prominent velocity ranges and variability. Broad SiO emission (>~20 km/s) indicates strong shocks, while narrower extents (<~6km/s) likely trace large-scale interactions or low-velocity shocks. The widespread infall signatures, shock tracers, masers, and NH2D emission suggest that relatively quiescent, chemically young material can coexist with dynamically active gas affected by early protostellar feedback, providing insight into the coupled physical and chemical evolution of massive IRDC clumps.

astro-ph.GA↗

arXiv2026

Trace the Self-Gravitating Gas Using CO Isotopologues

Recent studies have shown that the star formation rate (SFR) correlates tightly and linearly with the mass of gravitationally bound gas, which can be delineated from the power-law tail of the column-density probability distribution function ($N$-PDF) derived from dust emission observations. This relationship holds across four orders of magnitude within the Milky Way--spanning low-mass to high-mass star-forming regions and encompassing the extreme environment of the Central Molecular Zone. Building on this framework, we present a new approach for estimating the mass of gravitationally bound gas in molecular clouds using multi-line CO isotopologue observations. Our sample includes 16 molecular clouds with robust detections in $^{12}$CO, $^{13}$CO, and C$^{18}$O $J$ = 1-0, spanning both massive inner Galaxy clouds and nearby star-forming regions. We find that the $N$-PDFs derived from combined CO isotopologue data recover the characteristic log-normal plus power-law profiles seen in dust-based studies. The mass and spatial distribution of the self-gravitating structures estimated from both dust-based and CO-based methods agree well throughout the sample. This indicates that the CO isotopologue combination can robustly trace the self-gravitating component via the $N$-PDF method and provides a reliable, scalable, and velocity-resolved alternative to dust emission for identifying the star-forming gas in molecular clouds.

astro-ph.GA↗

arXiv2026

Resolving the black hole sphere of influence in a hyper-luminous obscured quasar at redshift 4.6

Supermassive black holes (SMBHs) imprint gravitational signatures on the matter within their sphere of influence (SoI). Nuclear gas dynamics can hence be used to accurately measure the mass of an SMBH, yet such measurements remain elusive in the early Universe. We report the first dynamical measurement of an SMBH mass at $z >$ 2, based on high spatial resolution observations of the [C II]157.7um and CO (12-11) 216.93um emission lines that resolve the SoI in an obscured quasar at $z$ = 4.6. The radial profile of the velocity dispersion reveals a clear Keplerian rise, requiring the presence of an approximately 6 $\times$ 10$^9~\rm M_{\odot}$ SMBH. We propose that obscured quasarsallow tracers like [C II] to survive in the inner regions, and may be ideal targets for increasing dynamical SMBH mass estimates in the early Universe.

astro-ph.GA↗

arXiv2026

Rethinking Visual Neglect: Steering via Context-Preference for MLLM Hallucination Mitigation

Object hallucination remains a primary obstacle to the reliable deployment of Multimodal Large Language Models (MLLMs). Current inference-time mitigation methods mainly assume hallucinations stem from visual neglect, steering models to enhance visual reliance. In contrast, our systematic interventions on multiple MLLMs show that pushing toward more visual reliance may exacerbate hallucinations on some models, while less may mitigate hallucinations. This result suggests that attributing hallucinations solely to visual insufficiency is underdetermined. We argue that the image, as a context, simultaneously competes with the model's parametric knowledge and the textual context. For this, we propose a training-free framework, Context-Preference Activation Steering (CAS). It extracts two semantically distinct Context Preference Vectors (CPVs) via two small sets of designed conflict samples and applies them via single-pass signed residual injection at mid-early MLP layers during inference to control information reliance. Experiments show that CAS substantially mitigates object hallucinations without increasing decoding latency and preserves native text-generation quality.

cs.CL↗

arXiv2026

Compact, AGN-hosting Dwarf Galaxies with "Little Red Dots"-like SEDs in the Local Universe

Local active galactic nuclei (AGNs) in dwarf galaxies are often considered as analogs for the earliest supermassive black holes, although their connections require more comprehensive examinations. Motivated by finding the local analogs of "Little Red Dots" (LRDs), the compact, red galaxies discovered by JWST at z > 5 characterized by "V-shaped" SEDs, we compile a sample of local AGN-hosting dwarf galaxies (ADGs) with comparable luminosities to statistically evaluate this connection. By applying K-means clustering to SED shapes and morphological sizes, we classified four groups which trace a sequence in physical properties, including metallicity, star formation rate, and dust emission, mainly driven by their distinct UV-optical slopes. Within these groups, we find that about half of the ADGs exhibit "V-shaped" SEDs and relatively compact morphologies. However, a direct comparison reveals fundamental physical differences: local "V-shaped", compact ADGs appear significantly more evolved than high-z LRDs, characterized by systematically larger effective radii and distinct ionization states. Our results suggest that local compact ADGs likely follow a different formation pathway from LRDs, highlighting the complexity of black hole-galaxy co-evolution across cosmic time.

astro-ph.GA↗

arXiv2026

An inverted infall profile for the collapse of the massive star-forming IRDC SDC335.579-0.292

There is increasing evidence for global collapse of clumps over parsec-scales in massive star formation regions. Such collapse may result in characteristic molecular line emission profiles but the spatial variation of such lines has rarely been quantitatively examined. Here we explore the infall properties using the spatially-resolved HCO$^+$ J=1--0 and H$^{13}$CO$^+$ J=1--0 maps of the massive infrared dark cloud (IRDC) SDC335.579-0.292. We compare the observations with the analytical Hill5 model and radiative transfer models. This shows that the best-fit infall velocity towards the cloud centre to be well-constrained to $-0.6$ to $-1.6$ km s$^{-1}$ and the mass infall rate between a few $\times10^{-3}$ and $10^{-2}$ M$_{\odot}$yr$^{-1}$. The comparison also highlights some limitations of the Hill5 method. We demonstrate that the width of optically thin spectral lines, which are usually interpreted as resulting from turbulent motions, are in fact dominated by unresolved, ordered infall motions within the beam. Our results suggest a complex collapse situation where there is a minimum in the infall velocity at $\sim2\times10^{18}$ cm (0.7 pc) with the infall velocity increasing at both smaller and larger radii. The parsec-scale infall with an inverted velocity profile indicates that the accretion in this massive star-forming cloud should have intermediate scales, at which fragmentation or filament formation has to occur before material flows onto the cloud centre.

astro-ph.GA↗

arXiv2025

Understanding Typing-Related Bugs in Solidity Compiler

The correctness of the Solidity compiler is crucial for ensuring the security of smart contracts. However, the implementation complexity of its type system often introduces elusive defects. This paper presents the first systematic empirical study on typing-related bugs in the Solidity compiler. To systematically analyze these bugs, we collected 146 officially confirmed and fixed typing-related bugs from the official GitHub repository of Solidity compiler. For each bug, we conducted an in-depth analysis and classification from four dimensions: symptoms, root causes, exposure conditions, and fix strategies. Through this study, we reveal unique distribution patterns and key characteristics of such bugs, and summarize 12 core findings. We additionally give the implications of our findings, and these implications not only deepen the understanding of inherent weaknesses in the Solidity compiler but also provide new insights for detecting and fixing typing-related bugs in the Solidity compiler.

cs.SE↗

arXiv2025

Parameter-Efficient Fine-Tuning with Attributed Patch Semantic Graph for Automated Patch Correctness Assessment

Automated program repair (APR) aims to automatically repair program errors without human intervention, and recent years have witnessed a growing interest on this research topic. While much progress has been made and techniques originating from different disciplines have been proposed, APR techniques generally suffer from the patch overfitting issue, i.e., the generated patches are not genuinely correct despite they pass the employed tests. To alleviate this issue, many research efforts have been devoted for automated patch correctness assessment (APCA). In particular, with the emergence of large language model (LLM) technology, researchers have employed LLM to assess the patch correctness and have obtained the state-of-the-art performance. The literature on APCA has demonstrated the importance of capturing patch semantic and explicitly considering certain code attributes in predicting patch correctness. However, existing LLM-based methods typically treat code as token sequences and ignore the inherent formal structure for code, making it difficult to capture the deep patch semantics. Moreover, these LLM-based methods also do not explicitly account for enough code attributes. To overcome these drawbacks, we in this paper design a novel patch graph representation named attributed patch semantic graph (APSG), which adequately captures the patch semantic and explicitly reflects important patch attributes. To effectively use graph information in APSG, we accordingly propose a new parameter-efficient fine-tuning (PEFT) method of LLMs named Graph-LoRA. Extensive evaluations have been conducted to evaluate our method, and the results show that compared to the state-of-the-art methods, our method improves the accuracy and F1 score by 3.1\% to 7.5\% and 3.0\% to 7.1\% respectively.

cs.SE↗

arXiv2025

Understanding Inconsistent State Update Vulnerabilities in Smart Contracts

Smart contracts enable contract terms to be automatically executed and verified on the blockchain, and recent years have witnessed numerous applications of them in areas such as financial institutions and supply chains. The execution logic of a smart contract is closely related to the contract state, and thus the correct and safe execution of the contract depends heavily on the precise control and update of the contract state. However, the contract state update process can have issues. In particular, inconsistent state update issues can arise for reasons such as unsynchronized modifications. Inconsistent state update bugs have been exploited by attackers many times, but existing detection tools still have difficulty in effectively identifying them. This paper conducts the first large-scale empirical study about inconsistent state update vulnerabilities (that is, inconsistent state update bugs that are exploitable) in smart contracts, aiming to shed light for developers, researchers, tool builders, and language or library designers in order to avoid inconsistent state update vulnerabilities. We systematically investigate 116 inconsistent state update vulnerabilities in 352 real-world smart contract projects, summarizing their root causes, fix strategies, and exploitation methods. Our study provides 11 original and important findings, and we also give the implications of our findings. To illustrate the potential benefits of our research, we also develop a proof-of-concept checker based on one of our findings. The checker effectively detects issues in 64 popular GitHub projects, and 19 project owners have confirmed the detected issues at the time of writing. The result demonstrates the usefulness and importance of our findings for avoiding inconsistent state update vulnerabilities in smart contracts.

cs.SE↗

arXiv2025

Predicting Quasar Counts Detectable in the LSST Survey

The Legacy Survey of Space and Time (LSST), being conducted by the Vera C. Rubin Observatory, is a wide-field multi-band survey that will revolutionize our understanding of extragalactic sources through its unprecedented combination of area and depth. While the LSST survey strategy is still being finalized, the Rubin Observatory team has generated a series of survey simulations using the LSST Operations Simulator to explore the optimal survey strategy that best accommodates the majority of scientific goals. In this study, we utilize the latest simulated data to predict the number of detectable quasars by LSST in each band and evaluate the impact of different survey strategies. We find that the number of quasars and lower luminosity AGNs detected in the baseline strategy (v4.3.1) in the redshift range z=0.3-6.7 will be highest in the i-band and lowest in the u-band. Over 70% of quasars are expected to be detected within the first year in all bands, as LSST will have already reached the break of the luminosity function at most redshifts. With a limiting magnitude of 25.7 mag, we expect to detect 184 million AGNs in the z-band over the 10-year survey, with quasars constituting only 6% of the total AGNs in each band. This arises because, considering that the luminosities of most low-luminosity AGNs are affected by contamination from their host galaxies, we set a magnitude threshold when predicting the number of quasars. We find that variations in the u-band strategy can impact the number of quasar detections. Specifically, the difference between the baseline strategy and that with the largest total exposure in u is 15%. In contrast, changes in rolling strategies, DDF strategies, weather conditions, and Target of Opportunity observations result in variations below 2%. These results provide valuable insights for optimizing approaches to maximize the scientific output of quasar studies.

astro-ph.GA↗

arXiv2025

Tails of Gravity: Persistence of Star Formation in the CMZ Environment

We characterize star-forming gas in six molecular clouds (Sgr B1-off, Sgr B2, Sgr C, the 20 km s$^{-1}$ and 50 km s$^{-1}$ molecular clouds, and the Brick) in the Galactic central molecular zone (CMZ), and compare their star-forming activities with those in molecular clouds outside the CMZ. Using multi-band continuum observations taken from ${\it Planck}$, ${\it Herschel}$, JCMT/SCUBA-2, and CSO/SHARC2, we derived 8.5" resolution column density maps for the CMZ clouds and evaluated the column density probability distribution functions (N-PDFs). With the archival Atacama Large Millimeter/submillimeter Array (ALMA) 1.3 mm dust continuum data, we further evaluated the mass of the most massive cores ($M_{\rm core}^{\rm ma x}$). We find that the N-PDFs of four of the selected CMZ clouds are well described by a piecewise log-normal + power-law function, while the N-PDFs of the remaining two can be approximated by log-normal functions. In the first four targets, the masses in the power-law component ($M_{\rm gas}^{\rm bound}$), $M_{\rm core}^{\rm max}$, and star formation rate (SFR) are correlated. These correlations are very similar to those derived from low-mass clouds in the Solar neighborhood and massive star-forming regions on the Galactic disk. These findings lead to our key hypotheses: (1) In the extreme environment of the CMZ, the power-law component in the N-PDF also represents self-gravitationally bound gas structures, and (2) evolution and star-forming activities of self-gravitationally bound gas structures may be self-regulated, insensitive to the exterior environment on $\gtrsim$5-10 pc scales.

astro-ph.GA↗

arXiv2025

Investigating the Impacts of AGN Activities on Dwarf Galaxies with FAST HI Observations

We present the results of Hi line observations towards 26 Active Galactic Nuclei (AGN)-hosting and one star-forming dwarf galaxies (Mstar < 10^9.5 Msun) with the 19-beam spectral line receiver of FAST at 1.4 GHz. Our FAST observed targets are combined with other AGN-hosting dwarf galaxies covered in the ALFALFA footprint to form a more comprehensive sample. Utilizing the information from optical surveys, we further divide them into isolated and accompanied subsamples by their vicinity of nearby massive galaxies. We compare the Hi gas abundance and star-forming rate (SFR) between the subsamples to assess the role of internal and external processes that may regulate the gas content in dwarf galaxies. As a result, we find that AGN are more commonly identified in accompanied dwarf galaxies than in their isolated counterparts. Meanwhile, AGN-hosting dwarf galaxies have slightly but significant lower Hi mass fraction relatively to the non-AGN control sample in accompanied dwarf galaxies. On the other hand, we find a decreasing SFR in AGN-hosting dwarf galaxies towards denser environments, as well as an extremely low incidence of quenched isolated dwarfs within both AGN and non-AGN subsamples. These results indicate that although these AGN could potentially regulate the gas reservoir of dwarf galaxies, environmental effects are likely the dominant quenching mechanism in the low-mass universe.

astro-ph.GA↗

arXiv2025

Deep Andromeda JCMT-SCUBA2 Observations. The Submillimeter Maps and Giant Molecular Clouds

We have carried out unprecedentedly deep, nearly confusion-limited JCMT-SCUBA2 mapping observations on the nearest spiral galaxy, M31 (Andromeda). The 850 $μ$m image with a $\sim$50 pc resolution yields a comprehensive catalog of 383 giant molecular clouds (GMCs) that are associated with the spiral arms. In addition, it unveiled a population of 189 compact inter-arm GMCs in M31, which are mostly unresolved or marginally resolved. The masses of all these GMCs are in the range of 2$\times$10$^4$ -- 6$\times$10$^6$ $M_{\odot}$; the sizes are in the range of 30--130 pc. They follow a mass-size correlation, $M$ $\propto$ $R_{c}$$^{2.5}$. The inter-arm GMCs are systematically less massive, more diffuse, colder, and have lower star-forming efficiency (SFE) than on-arm GMCs. Moreover, within individual spatially resolved on-arm and off-arm M31 GMCs, the SFE is considerably lower than the SFE in molecular clouds in main sequence and green valley galaxies. Follow-up investigations on M31 GMCs may provide clues for how star formation may be quenched in galactic environments. Finally, we reconstrained the dust opacity spectral index $β$ in the M31 galaxy by combining our new JCMT observations with archival Herschel and Planck data and found that the radial variation of $β$ may not be as large as was proposed by previous studies.

astro-ph.GA↗

arXiv2025

Probing the Physics of Dusty Outflows through Complex Organic Molecules in the Early Universe

Galaxy-scale outflows are of critical importance for galaxy formation and evolution. Dust grains are the main sites for the formation of molecules needed for star formation but are also important for the acceleration of outflows that can remove the gas reservoir critical for stellar mass growth. Using the MIRI medium-resolution integral field spectrograph aboard the James Webb Space Telescope (JWST), we detect the 3.28 $μ$m aromatic and the 3.4 $μ$m aliphatic hydrocarbon dust features in absorption in a redshift 4.601 hot dust-obscured galaxy, blue-shifted by $Δ$V=$-5250^{+276}_{-339}$ kms$^{-1}$ from the systemic redshift of the galaxy. The extremely high velocity of the dust indicates that the wind was accelerated by radiation pressure from the central quasar. These results pave a novel way for probing the physics of dusty outflows in active galaxies at early cosmic time.

astro-ph.GA↗