arXiv subjects

Hao He

Publications and source records attributed to Hao He.

At least 55 records · Page 3Linked to original sources

arXiv2025

Constraining resolved extragalactic $R_{21}$ variation with well calibrated ALMA observations

CO(1-0) and CO(2-1) are commonly used as bulk molecular gas tracers. The CO line ratios (especially CO(2-1)/CO(1-0) - $R_{21}$) vary within and among galaxies, yet previous studies on $R_{21}$ and alike often rely on measurements constructed by combining data from facilities with substantial relative calibration uncertainties that have the same order as physical line ratio variations. Hence robustly determining systematic $R_{21}$ variations is challenging. Here, we compare CO(1-0) and CO(2-1) mapping data from ALMA for 14 nearby galaxies, at a common physical resolution of 1.7 kpc. Our dataset includes new ALMA (7m+TP) CO(1-0) maps of 12 galaxies. We investigate $R_{21}$ variation to understand its dependence on global galaxy properties, kpc-scale environmental factors, and its correlation with star formation rate (SFR) surface density and metallicity. We find that the galaxy-to-galaxy scatter is 0.05 dex. This is lower than previous studies which reported over 0.1 dex variation, likely reflecting significant flux calibration uncertainties in single-dish surveys. Within individual galaxies, $R_{21}$ has a typical mean value of ~0.64 and 0.1 dex variation, with an increase to ~0.75 towards galactic centers. We find strong correlations between $R_{21}$ and various galactic parameters, particularly SFR surface density, which shows a power-law slope of 0.10-0.11 depending on the adopted binning/fitting methods. Our findings suggest that, for studies covering main sequence galaxy samples, assuming a fixed $R_{21}$=0.64 does not significantly bias kpc-scale molecular gas mass estimates from CO(2-1). Instead, systematic uncertainties from flux calibration and the CO-to-H$_2$ conversion factor account for more systematic scatter of CO-derived molecular gas properties.

astro-ph.GA↗

arXiv2025

Communication Efficient Multiparty Private Set Intersection from Multi-Point Sequential OPRF

Multiparty private set intersection (MPSI) allows multiple participants to compute the intersection of their locally owned data sets without revealing them. MPSI protocols can be categorized based on the network topology of nodes, with the star, mesh, and ring topologies being the primary types, respectively. Given that star and mesh topologies dominate current implementations, most existing MPSI protocols are based on these two topologies. However, star-topology MPSI protocols suffer from high leader node load, while mesh topology protocols suffer from high communication complexity and overhead. In this paper, we first propose a multi-point sequential oblivious pseudorandom function (MP-SOPRF) in a multi-party setting. Based on MP-SOPRF, we then develop an MPSI protocol with a ring topology, addressing the challenges of communication and computational overhead in existing protocols. We prove that our MPSI protocol is semi-honest secure under the Hamming correlation robustness assumption. Our experiments demonstrate that our MPSI protocol outperforms state-of-the-art protocols, achieving a reduction of 74.8% in communication and a 6% to 287% improvement in computational efficiency.

cs.CR↗

arXiv2025

UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents

In this paper, we introduce UI-Genie, a self-improving framework addressing two key challenges in GUI agents: verification of trajectory outcome is challenging and high-quality training data are not scalable. These challenges are addressed by a reward model and a self-improving pipeline, respectively. The reward model, UI-Genie-RM, features an image-text interleaved architecture that efficiently pro- cesses historical context and unifies action-level and task-level rewards. To sup- port the training of UI-Genie-RM, we develop deliberately-designed data genera- tion strategies including rule-based verification, controlled trajectory corruption, and hard negative mining. To address the second challenge, a self-improvement pipeline progressively expands solvable complex GUI tasks by enhancing both the agent and reward models through reward-guided exploration and outcome verification in dynamic environments. For training the model, we generate UI- Genie-RM-517k and UI-Genie-Agent-16k, establishing the first reward-specific dataset for GUI agents while demonstrating high-quality synthetic trajectory gen- eration without manual annotation. Experimental results show that UI-Genie achieves state-of-the-art performance across multiple GUI agent benchmarks with three generations of data-model self-improvement. We open-source our complete framework implementation and generated datasets to facilitate further research in https://github.com/Euphoria16/UI-Genie.

cs.CL↗

arXiv2025

Relationships between PAHs, Small Dust Grains, H$_2$, and HI in Local Group Dwarf Galaxies NGC 6822 and WLM Using JWST, ALMA, and the VLA

We present 0.7-3.3 pc resolution mid-infrared (MIR) JWST images at 7.7 $μ$m (F770W) and 21 $μ$m (F2100W) covering the main star-forming regions of two of the closest star-forming low-metallicity dwarf galaxies, NGC6822 and Wolf-Lundmark-Melotte (WLM). The images of NGC6822 reveal filaments, edge-brightened bubbles, diffuse emission, and a plethora of point sources. By contrast, most of the MIR emission in WLM is point-like, with a small amount of extended emission. Compared to solar metallicity galaxies, the ratio of 7.7 $μ$m intensity ($I_ν^{F770W}$), tracing polycyclic aromatic hydrocarbons (PAHs), to 21 $μ$m intensity ($I_ν^{F2100W}$), tracing small, warm dust grain emission, is suppressed in these low-metallicity dwarfs. Using ALMA CO(2-1) observations, we find that detected CO intensity versus $I_ν^{F770W}$ at ~2 pc resolution in dwarfs follows a similar relationship to that at solar metallicity and lower resolution, while the CO versus $I_ν^{F2100W}$ relationship in dwarfs lies significantly below that derived from solar metallicity galaxies at lower resolution, suggesting more pronounced destruction of CO molecules at low metallicity. Finally, adding in Local Group L-Band Survey VLA 21 cm HI observations, we find that $I_ν^{F2100W}$ and $I_ν^{F770W}$ vs. total gas ratios are suppressed in NGC6822 and WLM compared to solar metallicity galaxies. In agreement with dust models, the level of suppression appears to be at least partly accounted for by the reduced galaxy-averaged dust-to-gas and PAH-to-dust mass ratios in the dwarfs. Remaining differences are likely due to spatial variations in dust model parameters, which should be an exciting direction for future work in local dwarf galaxies.

astro-ph.GA↗

arXiv2025

Polycyclic Aromatic Hydrocarbon and CO(2-1) Emission at 50-150 pc Scales in 70 Nearby Galaxies

Combining Atacama Large Millimeter/sub-millimeter Array CO(2-1) mapping and JWST near- and mid-infrared imaging, we characterize the relationship between CO(2-1) and polycyclic aromatic hydrocarbon (PAH) emission at ~100 pc resolution in 70 nearby star-forming galaxies. Leveraging a new Cycle 2 JWST treasury program targeting nearby galaxies, we expand the sample size by more than an order of magnitude compared to previous ~100 pc resolution CO-PAH comparisons. Focusing on regions of galaxies where most of the gas is likely to be molecular, we find strong correlations between CO(2-1) and 3.3 um, 7.7 um, and 11.3 um PAH emission, estimated from JWST's F335M, F770W, and F1130W filters. We derive power law relations between CO(2-1) and PAH emission, which have indices in the range 0.8-1.3, implying relatively weak variations in the observed CO-to-PAH ratios across the regions that we study. We find that CO-to-PAH ratios and scaling relationships near HII regions are similar to those in diffuse sight lines. The main difference between the two types of regions is that sight lines near HII regions show higher intensities in all tracers. Galaxy centers, on the other hand, show higher overall intensities and enhanced CO-to-PAH ratios compared to galaxy disks. Individual galaxies show 0.19 dex scatter in the normalization of CO at fixed I_PAH, and this normalization anti-correlates with specific star formation rate (sSFR) and correlates with stellar mass. We provide a prescription that accounts for these galaxy-to-galaxy variations and represents our best current empirical predictor to estimate CO(2-1) intensity from PAH emission, which allows one to take advantage of JWST's excellent sensitivity and resolution to trace cold gas.

astro-ph.GA↗

arXiv2025

CameraCtrl: Enabling Camera Control for Text-to-Video Generation

Controllability plays a crucial role in video generation, as it allows users to create and edit content more precisely. Existing models, however, lack control of camera pose that serves as a cinematic language to express deeper narrative nuances. To alleviate this issue, we introduce CameraCtrl, enabling accurate camera pose control for video diffusion models. Our approach explores effective camera trajectory parameterization along with a plug-and-play camera pose control module that is trained on top of a video diffusion model, leaving other modules of the base model untouched. Moreover, a comprehensive study on the effect of various training datasets is conducted, suggesting that videos with diverse camera distributions and similar appearance to the base model indeed enhance controllability and generalization. Experimental results demonstrate the effectiveness of CameraCtrl in achieving precise camera control with different video generation models, marking a step forward in the pursuit of dynamic and customized video storytelling from textual and camera pose inputs.

cs.CV↗

arXiv2025

CameraCtrl II: Dynamic Scene Exploration via Camera-controlled Video Diffusion Models

This paper introduces CameraCtrl II, a framework that enables large-scale dynamic scene exploration through a camera-controlled video diffusion model. Previous camera-conditioned video generative models suffer from diminished video dynamics and limited range of viewpoints when generating videos with large camera movement. We take an approach that progressively expands the generation of dynamic scenes -- first enhancing dynamic content within individual video clip, then extending this capability to create seamless explorations across broad viewpoint ranges. Specifically, we construct a dataset featuring a large degree of dynamics with camera parameter annotations for training while designing a lightweight camera injection module and training scheme to preserve dynamics of the pretrained models. Building on these improved single-clip techniques, we enable extended scene exploration by allowing users to iteratively specify camera trajectories for generating coherent video sequences. Experiments across diverse scenarios demonstrate that CameraCtrl Ii enables camera-controlled dynamic scene synthesis with substantially wider spatial exploration than previous approaches.

cs.CV↗

arXiv2025

LucidFusion: Reconstructing 3D Gaussians with Arbitrary Unposed Images

Recent large reconstruction models have made notable progress in generating high-quality 3D objects from single images. However, current reconstruction methods often rely on explicit camera pose estimation or fixed viewpoints, restricting their flexibility and practical applicability. We reformulate 3D reconstruction as image-to-image translation and introduce the Relative Coordinate Map (RCM), which aligns multiple unposed images to a main view without pose estimation. While RCM simplifies the process, its lack of global 3D supervision can yield noisy outputs. To address this, we propose Relative Coordinate Gaussians (RCG) as an extension to RCM, which treats each pixel's coordinates as a Gaussian center and employs differentiable rasterization for consistent geometry and pose recovery. Our LucidFusion framework handles an arbitrary number of unposed inputs, producing robust 3D reconstructions within seconds and paving the way for more flexible, pose-free 3D pipelines.

cs.CV↗

arXiv2025

LiCoEval: Evaluating LLMs on License Compliance in Code Generation

Recent advances in Large Language Models (LLMs) have revolutionized code generation, leading to widespread adoption of AI coding tools by developers. However, LLMs can generate license-protected code without providing the necessary license information, leading to potential intellectual property violations during software production. This paper addresses the critical, yet underexplored, issue of license compliance in LLM-generated code by establishing a benchmark to evaluate the ability of LLMs to provide accurate license information for their generated code. To establish this benchmark, we conduct an empirical study to identify a reasonable standard for "striking similarity" that excludes the possibility of independent creation, indicating a copy relationship between the LLM output and certain open-source code. Based on this standard, we propose LiCoEval, to evaluate the license compliance capabilities of LLMs, i.e., the ability to provide accurate license or copyright information when they generate code with striking similarity to already existing copyrighted code. Using LiCoEval, we evaluate 14 popular LLMs, finding that even top-performing LLMs produce a non-negligible proportion (0.88% to 2.01%) of code strikingly similar to existing open-source implementations. Notably, most LLMs fail to provide accurate license information, particularly for code under copyleft licenses. These findings underscore the urgent need to enhance LLM compliance capabilities in code generation tasks. Our study provides a foundation for future research and development to improve license compliance in AI-assisted software development, contributing to both the protection of open-source software copyrights and the mitigation of legal risks for LLM users.

cs.SE↗

arXiv2025

Performance Evaluation of Large Language Models in Statistical Programming

The programming capabilities of large language models (LLMs) have revolutionized automatic code generation and opened new avenues for automatic statistical analysis. However, the validity and quality of these generated codes need to be systematically evaluated before they can be widely adopted. Despite their growing prominence, a comprehensive evaluation of statistical code generated by LLMs remains scarce in the literature. In this paper, we assess the performance of LLMs, including two versions of ChatGPT and one version of Llama, in the domain of SAS programming for statistical analysis. Our study utilizes a set of statistical analysis tasks encompassing diverse statistical topics and datasets. Each task includes a problem description, dataset information, and human-verified SAS code. We conduct a comprehensive assessment of the quality of SAS code generated by LLMs through human expert evaluation based on correctness, effectiveness, readability, executability, and the accuracy of output results. The analysis of rating scores reveals that while LLMs demonstrate usefulness in generating syntactically correct code, they struggle with tasks requiring deep domain understanding and may produce redundant or incorrect results. This study offers valuable insights into the capabilities and limitations of LLMs in statistical programming, providing guidance for future advancements in AI-assisted coding systems for statistical analysis.

stat.AP↗

arXiv2025

Pinning Is Futile: You Need More Than Local Dependency Versioning to Defend against Supply Chain Attacks

Recent high-profile incidents in open-source software have greatly raised practitioner attention on software supply chain attacks. To guard against potential malicious package updates, security practitioners advocate pinning dependency to specific versions rather than floating in version ranges. However, it remains controversial whether pinning carries a meaningful security benefit that outweighs the cost of maintaining outdated and possibly vulnerable dependencies. In this paper, we quantify, through counterfactual analysis and simulations, the security and maintenance impact of version constraints in the npm ecosystem. By simulating dependency resolutions over historical time points, we find that pinning direct dependencies not only (as expected) increases the cost of maintaining vulnerable and outdated dependencies, but also (surprisingly) even increases the risk of exposure to malicious package updates in larger dependency graphs due to the specifics of npm's dependency resolution mechanism. Finally, we explore collective pinning strategies to secure the ecosystem against supply chain attacks, suggesting specific changes to npm to enable such interventions. Our study provides guidance for practitioners and tool designers to manage their supply chains more securely.

cs.SE↗

arXiv2025

Dense gas scaling relations at kiloparsec scales across nearby galaxies with the ALMA ALMOND and IRAM 30m EMPIRE surveys

Dense, cold gas is the key ingredient for star formation. Over the last two decades, HCN(1-0) emission has been utilised as the most accessible dense gas tracer to study external galaxies. We present new measurements tracing the relationship between dense gas tracers, bulk molecular gas tracers, and star formation in the ALMA ALMOND survey, the largest sample of resolved (1-2 kpc resolution) HCN maps of galaxies in the local universe (d < 25 Mpc). We measure HCN/CO, a line ratio sensitive to the physical density distribution, and SFR/HCN, a proxy for the dense gas star formation efficiency, as a function of molecular gas surface density, stellar mass surface density, and dynamical equilibrium pressure across 31 galaxies, increasing the number of galaxies by a factor of > 3 over the previous largest such study (EMPIRE). HCN/CO increases (slope of ~ 0.5 and scatter of ~ 0.2 dex), while SFR/HCN decreases (slope of ~ -0.6 and scatter of ~ 0.4 dex) with increasing molecular gas surface density, stellar mass surface density and pressure. Galaxy centres with high stellar mass surface density show a factor of a few higher HCN/CO and lower SFR/HCN compared to the disc average, but both environments follow the same average trend. Our results emphasise that molecular gas properties vary systematically with the galactic environment and demonstrate that the scatter in the Gao-Solomon relation (SFR against HCN) is of physical origin.

astro-ph.GA↗

arXiv2025

Does the HCN/CO ratio trace the star-forming fraction of gas? II. Variations in CO and HCN Emissivity

We model emissivities of the HCN and CO $J=1-0$ transitions using measured properties of clouds found in normal star forming galaxies and more extreme systems. These models are compared with observations of HCN and CO $J=1-0$ transitions. We combine these model emissivities with predictions of gravoturbulent models of star formation, explore the impact of excitation and optical depth on CO and HCN emission, and assess if observed HCN/CO ratios track the fraction of gravitationally-bound dense gas, $f_\mathrm{grav}$, in molecular clouds. Our modeled HCN/CO ratios and emissivities are consistent with measurements from observations. CO emission shows a range of optical depths across different environments, from optically thick in normal galaxies to moderately optically thin in extreme systems. HCN is only moderately optically thick, with significant subthermal excitation in both normal and extreme galaxies. We find an anticorrelation between HCN/CO and $f_\mathrm{grav}$ as predicted by gravoturbulent models of star formation. Instead this ratio tracks gas at moderate densities ($n>10^{3.5}\ \mathrm{cm}^{-3}$), which is below the standard dense gas threshold of $n>10^{4.5}\ \mathrm{cm}^{-3}$. Variations in CO emissivity depend strongly on optical depth, due to variations in the dynamics of the cloud gas. HCN emissivity depends more strongly on excitation, and thus does not directly track variations in CO emissivity. We conclude that a single line ratio, such as HCN/CO, will not consistently track the fraction of gravitationally-bound, star-forming gas if the critical density for star formation varies in molecular clouds. This work highlights important uncertainties that need to be considered when observationally applying an HCN conversion factor in order to estimate the dense (i.e. $n>10^{4.5}\ \mathrm{cm}^{-3}$) gas content in nearby galaxies.

astro-ph.GA↗

arXiv2025

Bi-stability and period-doubling cascade of frequency combs in exceptional-point lasers

Recent studies have demonstrated that a laser can self-generate frequency combs when tuned near an exceptional point (EP), where two cavity modes coalesce. These EP combs induce periodic modulation of the population inversion in the gain medium, and their repetition rate is independent of the laser cavity's free spectral range. In this work, we perform a stability analysis that reveals two notable properties of EP combs, bi-stability and a period-doubling cascade. The period-doubling cascade enables halving of the repetition rate while maintaining the comb's total bandwidth, presenting opportunities for the design of highly compact frequency comb generators.

physics.optics↗

arXiv2025

SEGT: A General Spatial Expansion Group Transformer for nuScenes Lidar-based Object Detection Task

In the technical report, we present a novel transformer-based framework for nuScenes lidar-based object detection task, termed Spatial Expansion Group Transformer (SEGT). To efficiently handle the irregular and sparse nature of point cloud, we propose migrating the voxels into distinct specialized ordered fields with the general spatial expansion strategies, and employ group attention mechanisms to extract the exclusive feature maps within each field. Subsequently, we integrate the feature representations across different ordered fields by alternately applying diverse expansion strategies, thereby enhancing the model's ability to capture comprehensive spatial information. The method was evaluated on the nuScenes lidar-based object detection test dataset, achieving an NDS score of 73.9 without Test-Time Augmentation (TTA) and 74.5 with TTA, demonstrating the effectiveness of the proposed method. Notably, our method ranks the 1st place in the nuScenes lidar-based object detection task.

cs.CV↗

arXiv2025

A descent method for nonsmooth multiobjective optimization problems on Riemannian manifolds

In this paper, a descent method for nonsmooth multiobjective optimization problems on complete Riemannian manifolds is proposed. The objective functions are only assumed to be locally Lipschitz continuous instead of convexity used in existing methods. A necessary condition for Pareto optimality in Euclidean space is generalized to the Riemannian setting. At every iteration, an acceptable descent direction is obtained by constructing a convex hull of some Riemannian $\varepsilon$-subgradients. And then a Riemannian Armijo-type line search is executed to produce the next iterate. The convergence result is established in the sense that a point satisfying the necessary condition for Pareto optimality can be generated by the algorithm in a finite number of iterations. Finally, some preliminary numerical results are reported, which show that the proposed method is efficient.

math.OC↗

arXiv2024

Quasinormal coupled-mode analysis of dynamic gain in exceptional-point lasers

One of the key features of lasers operating near exceptional points (EPs) is that the gain medium can support an oscillating population inversion above a pump threshold, leading to self-modulated laser dynamics. This unusual behavior opens up new possibilities for frequency comb generation and temporal modulation. However, the dynamic population inversion couples signals with different frequencies and thus cannot be captured by conventional temporal coupled-mode theory (TCMT) based on static saturable gain. In this paper, we develop a perturbative coupled-mode analysis framework to capture the spatial-temporal dynamics of near-EP lasers. By decomposing discrete frequency generation into multiple excitations of resonant modes, our analysis establishes a minimal physical model that translates the local distribution of dynamic population-inversion into a resonant modal interpretation of laser gain. This work enables the exploration of unique properties in this self-time-modulated systems, such as time-varying scattering and non-reciprocal transmission.

physics.optics↗

arXiv2024

Topological Insulator in Twisted Transition Metal Dichalcogenide Heterotrilayers

The quantum spin Hall effect has been predicted in twisted homobilayer transition metal dichalcogenides (TMDs) owing to the layer-pseudospin magnetic field. Recently, experimental observations have also confirmed such topological states of matter. However, the topological electronic properties in multilayer moiré superlattices remain to be further explored. In twisted TMDs heterotrilayers, the realization of moiré potential with various symmetries becomes feasible. Here, we demonstrate that twisted trilayer TMDs can enter a topological insulator phase under the influence of moiré potential with ${C_6}$ symmetry. Specifically, we built two types of trilayer heterostructures, where the low-energy valence band electrons are contributed by the middle layer. In the AA-stacked moiré WS$_2$/WSe$_2$/MoS$_2$ heterotrilayers where only the middle layer is twisted, the maxima of the moiré potential exhibits an approximate ${C_6}$ symmetry. The $C_6$ symmetry effectively compensates for the spatial inversion symmetry breaking in the WSe$_2$ layer, leading to a twist-angle-dependent topological phase transition. Leveraging a Green's function approach, we calculate the local state density of edge states at topological minigaps, confirming their nature as moiré edge states. In the helical twisted AA-stacked moiré MoS$_2$/WSe$_2$/MoS$_2$ heterotrilayers, we observed a mosaic pattern of topological and trivial insulators. The emergence of topological mosaic is attributed to the maxima of the local moiré potential possessing $C_6$ symmetry. The results provide a new way for the experimental realization of topological phases in TMDs heterojunctions.

cond-mat.mes-hall↗