arXiv subjects

Long Wang

Publications and source records attributed to Long Wang.

At least 91 records · Page 5Linked to original sources

arXiv2025

LoD-Loc v2: Aerial Visual Localization over Low Level-of-Detail City Models using Explicit Silhouette Alignment

We propose a novel method for aerial visual localization over low Level-of-Detail (LoD) city models. Previous wireframe-alignment-based method LoD-Loc has shown promising localization results leveraging LoD models. However, LoD-Loc mainly relies on high-LoD (LoD3 or LoD2) city models, but the majority of available models and those many countries plan to construct nationwide are low-LoD (LoD1). Consequently, enabling localization on low-LoD city models could unlock drones' potential for global urban localization. To address these issues, we introduce LoD-Loc v2, which employs a coarse-to-fine strategy using explicit silhouette alignment to achieve accurate localization over low-LoD city models in the air. Specifically, given a query image, LoD-Loc v2 first applies a building segmentation network to shape building silhouettes. Then, in the coarse pose selection stage, we construct a pose cost volume by uniformly sampling pose hypotheses around a prior pose to represent the pose probability distribution. Each cost of the volume measures the degree of alignment between the projected and predicted silhouettes. We select the pose with maximum value as the coarse pose. In the fine pose estimation stage, a particle filtering method incorporating a multi-beam tracking approach is used to efficiently explore the hypothesis space and obtain the final pose estimation. To further facilitate research in this field, we release two datasets with LoD1 city models covering 10.7 km , along with real RGB queries and ground-truth pose annotations. Experimental results show that LoD-Loc v2 improves estimation accuracy with high-LoD models and enables localization with low-LoD models for the first time. Moreover, it outperforms state-of-the-art baselines by large margins, even surpassing texture-model-based methods, and broadens the convergence basin to accommodate larger prior errors.

cs.CV↗

arXiv2025

Consensus-Driven Uncertainty for Robotic Grasping based on RGB Perception

Deep object pose estimators are notoriously overconfident. A grasping agent that both estimates the 6-DoF pose of a target object and predicts the uncertainty of its own estimate could avoid task failure by choosing not to act under high uncertainty. Even though object pose estimation improves and uncertainty quantification research continues to make strides, few studies have connected them to the downstream task of robotic grasping. We propose a method for training lightweight, deep networks to predict whether a grasp guided by an image-based pose estimate will succeed before that grasp is attempted. We generate training data for our networks via object pose estimation on real images and simulated grasping. We also find that, despite high object variability in grasping trials, networks benefit from training on all objects jointly, suggesting that a diverse variety of objects can nevertheless contribute to the same goal.

cs.RO↗

arXiv2025

Compact Binary Formation in Open Star Clusters III: Probability of Binary Black Holes Hidden in Gaia Black Hole Binary

The Gaia mission and its follow-up observations have discovered a few candidates of non-interacting single black holes (BHs) and visible stars, Gaia BH1, BH2, and BH3, collectively called ``astrometric BH binaries''. This paper investigates whether any of these candidates harbor binary BHs (BBHs), namely, whether any such candidates are previously undiscovered ``astrimetric BBH triples''. Focusing on open star clusters, which are promising formation sites of astrometric BH binaries, we estimate the formation rate of astrometric BBH triples through gravitational $N$-body simulations. We find a competitively high formation efficiency of astrometric BBH triples ($\sim 10^{-6} {\rm M}_\odot^{-1}$ or $\sim 10$\% of astrometric BH binaries) in low-metallicity environments but no astrometric BBH triples in solar-metallicity environments. Most of the astrometric BBH triples in our simulations were dynamically stable for $10$ Gyrs, indicating that $\sim10$\% of astrometric BH binary candidates may indeed harbor inner BBHs if they originate from open star clusters in low-metallicity environments. Astrometric BBH triples can be distinguished from astrometric BH binaries through radial velocity follow-up of the tertiary star. According to the statistics of our simulated samples, a small percent of astrometric BH binary candidates should exhibit detectable radial-velocity modulations generated by inner BBHs. Such candidates preferentially exhibit ``outer'' orbital periods of $\gtrsim 10^3$ days and moderately high ``outer'' orbital eccentricities ($\gtrsim 0.7$). Our current result will strongly motivate the search for astrometric BBH triples in the upcoming Gaia Data Release 4 and Gaia Final Data Release.

astro-ph.GA↗

arXiv2025

Dynamical Iitaka theory on Fano contractions

We give several structure theorems for certain surjective endomorphisms on Mori fibre spaces, based on the dynamical Iitaka fibration of the ramification divisor. As an application, we prove the Kawaguchi-Silverman conjecture for projective bundles over abelian varieties or smooth projective varieties of Picard number one.

math.AG↗

arXiv2025

ATFusion: An Alternate Cross-Attention Transformer Network for Infrared and Visible Image Fusion

The fusion of infrared and visible images is essential in remote sensing applications, as it combines the thermal information of infrared images with the detailed texture of visible images for more accurate analysis in tasks like environmental monitoring, target detection, and disaster management. The current fusion methods based on Transformer techniques for infrared and visible (IV) images have exhibited promising performance. However, the attention mechanism of the previous Transformer-based methods was prone to extract common information from source images without considering the discrepancy information, which limited fusion performance. In this paper, by reevaluating the cross-attention mechanism, we propose an alternate Transformer fusion network (ATFusion) to fuse IV images. Our ATFusion consists of one discrepancy information injection module (DIIM) and two alternate common information injection modules (ACIIM). The DIIM is designed by modifying the vanilla cross-attention mechanism, which can promote the extraction of the discrepancy information of the source images. Meanwhile, the ACIIM is devised by alternately using the vanilla cross-attention mechanism, which can fully mine common information and integrate long dependencies. Moreover, the successful training of ATFusion is facilitated by a proposed segmented pixel loss function, which provides a good trade-off for texture detail and salient structure preservation. The qualitative and quantitative results on public datasets indicate our ATFusion is effective and superior compared to other state-of-the-art methods.

eess.IV↗

arXiv2025

High Probability Convergence of Distributed Clipped Stochastic Gradient Descent with Heavy-tailed Noise

In this paper, the problem of distributed optimization is studied via a network of agents. Each agent only has access to a noisy gradient of its own objective function, and can communicate with its neighbors via a network. To handle this problem, a distributed clipped stochastic gradient descent algorithm is proposed, and the high probability convergence of the algorithm is studied. Existing works on distributed algorithms involving stochastic gradients only consider the light-tailed noises. Different from them, we study the case with heavy-tailed settings. Under mild assumptions on the graph connectivity, we prove that the algorithm converges in high probability under a certain clipping operator. Finally, a simulation is provided to demonstrate the effectiveness of our theoretical results

math.OC↗

arXiv2025

Bandit based Dynamic Candidate Edge Selection in Solving Traveling Salesman Problems

Algorithms designed for routing problems typically rely on high-quality candidate edges to guide their search, aiming to reduce the search space and enhance the search efficiency. However, many existing algorithms, like the classical Lin-Kernighan-Helsgaun (LKH) algorithm for the Traveling Salesman Problem (TSP), often use predetermined candidate edges that remain static throughout local searches. This rigidity could cause the algorithm to get trapped in local optima, limiting its potential to find better solutions. To address this issue, we propose expanding the candidate sets to include other promising edges, providing them an opportunity for selection. Specifically, we incorporate multi-armed bandit models to dynamically select the most suitable candidate edges in each iteration, enabling LKH to make smarter choices and lead to improved solutions. Extensive experiments on multiple TSP benchmarks show the excellent performance of our method. Moreover, we employ this bandit-based method to LKH-3, an extension of LKH tailored for solving various TSP variant problems, and our method also significantly enhances LKH-3's performance across typical TSP variants.

cs.AI↗

arXiv2025

Direct reciprocity in asynchronous interactions

Cooperation is vital for the survival of living systems but is challenging due to the costs borne by altruistic individuals. Direct reciprocity, where actions are based on past encounters, is a key mechanism fostering cooperation. However, most studies assume synchronous decision-making, whereas real-world interactions are often asynchronous, with individuals acting in sequence. This asynchrony can undermine standard cooperative strategies like Tit-for-Tat and Win-Stay Lose-Shift. To better understand cooperation in real-world contexts, it is crucial to explore the theory of direct reciprocity in asynchronous interactions. To address this, we introduce a framework based on asynchronous stochastic games, incorporating asynchronous decisions and dynamic environmental feedback. We analytically derive the conditions under which strategies form cooperative Nash equilibria. Our results demonstrate that the order of interactions can significantly alter outcomes: interaction asynchrony generally inhibits cooperation, except under specific conditions where environmental feedback effectively mitigates its negative impact. When environmental feedback is incorporated, a variety of stable reciprocal strategies can be sustained. Notably, above a critical environmental threshold, any cooperative strategy can form a Nash equilibrium. Overall, our work underscores the importance of interaction order in long-term evolutionary processes and highlights the pivotal role of environmental feedback in stabilizing cooperation in asynchronous interactions.

physics.soc-ph↗

arXiv2025

Detection for Intermediate-mass Binary Black Holes in Population III Star Clusters with TianQin

Context. Population III star clusters are predicted to form in unenriched dark matter halos. Direct N-body simulation of Pop III clusters implies the possible formation and merger of intermediate-mass binary black holes (IMBBHs). The gravitational wave signals could be detected by space-borne gravitational wave detectors like TianQin. Aims. This study evaluates the potential of TianQin in detecting IMBBHs from Pop III star clusters, focusing on key factors such as the detection horizon, detection number, and Fisher uncertainty. Methods. A Monte Carlo simulation is employed to derive IMBBH sources, utilizing the IMRPhenomD waveform model to simulate catalogs of observable IMBBH mergers. The mass and redshift distributions are derived from direct N-body simulations of IMBBHs in Population III star clusters. Detection numbers are determined by calculating the signal-to-noise ratios (SNR) of the simulated signals and applying thresholds for detection. Fisher uncertainty is obtained through Fisher information matrix analysis. Results. The findings suggest that TianQin could achieve detection numbers within 5 years ranging from 1 in the most pessimistic scenario to 253 in the most optimistic scenario. Furthermore, TianQin can precisely constrain the IMBBH mass with a relative uncertainty of $10^{-6}$, coalescence time $t_c$ within 1 second, and sky location $\barΩ_S$ within 1 $\rm{deg}^2$. However, the luminosity distance $D_L$ and inclination angle $ι$ exhibit substantial degeneracies, limiting their precise estimation.

astro-ph.GA↗

arXiv2025

Pair-Instability Gap Black Holes in Population III Star Clusters: Pathways, Dynamics, and Gravitational Wave Implications

The detection of the gravitational wave (GW) event GW190521 raises questions about the formation of black holes within the pair-instability mass gap (PIBHs). We propose that Population III (Pop III) star clusters significantly contribute to events similar to GW190521. We perform $N$-body simulations and find that PIBHs can form from stellar collisions or binary black hole (BBH) mergers, with the latter accounting for 90\% of the contributions. Due to GW recoil during BBH mergers, approximately 10-50% of PIBHs formed via BBH mergers escape from clusters, depending on black hole spins and cluster escape velocities. The remaining PIBHs can participate in secondary and multiple BBH formation events, contributing to GW events. Assuming Pop III stars form in massive clusters (initially 100,000 $M_\odot$) with a top-heavy initial mass function, the average merger rates for GW events involving PIBHs with 0% and 100% primordial binaries are $0.005$ and $0.017$ $\text{yr}^{-1} \text{Gpc}^{-3}$, respectively, with maximum values of $0.030$ and $0.106$ $\text{yr}^{-1} \text{Gpc}^{-3}$. If Pop III stars form in low-mass clusters (initial mass of $1000M_\odot$ and $10000 M_\odot$), the merger rate is comparable with a 100% primordial binary fraction but significantly lower without primordial binaries. We also calculate the characteristic strains of the GW events in our simulations and find that about 43.4% (LISA) 97.8% (Taiji) and 66.4% (Tianqin) of these events could potentially be detected by space-borne detectors, including LISA, Taiji, and TianQin. The next-generation GW detectors such as DECIGO, ET, and CE can nearly cover all these signals.

astro-ph.HE↗

arXiv2025

Unveiling Bifurcated Blue Straggler Sequences in NGC 2173: Insights from Binary Evolution

Identifying bifurcated blue straggler (BS) sequences in color-magnitude diagrams (CMDs) of star clusters has long been regarded as a powerful diagnostic for distinguishing different BS formation mechanisms. While such bifurcations are typically associated with core-collapsed clusters, their detection in dynamically young clusters raises new questions about their origins. In this study, using high-precision proper motion data derived from Hubble Space Telescope multi-epoch observations, we confirm the existence of two distinct BS sequences in the Large Magellanic Cloud cluster NGC 2173 (~ 1.58 Gyr): a well-defined, narrow blue sequence and a sparser red sequence. The extended core region excludes collisional formation as a viable channel for BS formation. Our binary evolution models suggest that non-conservative mass transfer (MT) is essential for shaping the distribution of BS binaries in the CMD. The red sequence primarily comprises BS binaries formed through conservative ongoing MT. In contrast, the blue sequence BS binaries are formed through non-conservative post-MT processes, all involving white dwarf (WD) companions. These BS+WD binary systems may subsequently undergo a second MT phase, leading to the formation of double WD systems.

astro-ph.SR↗

arXiv2025

Massive star cluster formation I. High star formation efficiency while resolving feedback of individual stars

The mode of star formation that results in the formation of globular clusters and young massive clusters is difficult to constrain through observations. We present models of massive star cluster formation using the Torch framework, which uses AMUSE to couple distinct multi-physics codes that handle star formation, stellar evolution and dynamics, radiative transfer, and magnetohydrodynamics. We upgrade Torch by implementing the N-body code PeTar, thereby enabling Torch to handle massive clusters forming from $10^6\rm\, M_\odot$ clouds with $\ge10^5$ individual stars. We present results from Torch simulations of star clusters forming from $10^4, 10^5$, and $10^6\rm M_\odot$ turbulent, spherical gas clouds (named M4, M5, M6) of radius $R=11.7$ pc. We find that star formation is highly efficient and becomes more so at higher cloud mass and surface density. For M4, M5, and M6 with initial surface densities $2.325\times 10^{1,2,3}\rm\, M_\odot\, pc^{-2}$, after a free-fall time of $t_{ff}=6.7,2.1,0.67$ Myr, we find that $\sim$30%, 40%, and 60% of the cloud mass has formed into stars, respectively. The final integrated star formation efficiency is 32%, 65%, and 85% for M4, M5, and M6. Observations of nearby clusters similar to M4 have similar integrated star formation efficiencies of $\leq$30%. The M5 and M6 models represent a different regime of cluster formation that is more appropriate for the conditions in starburst galaxies and gas-rich galaxies at high redshift, and that leads to a significantly higher efficiency of star formation. We argue that young massive clusters build up through short efficient bursts of star formation in regions that are sufficiently dense ($\ge 10^2 \rm\,M_\odot\,pc^{-2}$) and massive ($\ge10^5\rm\, M_\odot$). In such environments, the dynamical time of the cloud becomes short enough that stellar feedback cannot act quickly enough to slow star formation.

astro-ph.GA↗

arXiv2025

Multi-armed Bandit and Backbone boost Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problems

The Lin-Kernighan-Helsguan (LKH) heuristic is a classic local search algorithm for the Traveling Salesman Problem (TSP). LKH introduces an $α$-value to replace the traditional distance metric for evaluating the edge quality, which leads to a significant improvement. However, we observe that the $α$-value does not make full use of the historical information during the search, and single guiding information often makes LKH hard to escape from some local optima. To address the above issues, we propose a novel way to extract backbone information during the TSP local search process, which is dynamic and can be updated once a local optimal solution is found. We further propose to combine backbone information, $α$-value, and distance to evaluate the edge quality so as to guide the search. Moreover, we abstract their different combinations to arms in a multi-armed bandit (MAB) and use an MAB model to help the algorithm select an appropriate evaluation metric dynamically. Both the backbone information and MAB can provide diverse guiding information and learn from the search history to suggest the best metric. We apply our methods to LKH and LKH-3, which is an extension version of LKH that can be used to solve about 40 variant problems of TSP and Vehicle Routing Problem (VRP). Extensive experiments show the excellent performance and generalization capability of our proposed method, significantly improving LKH for TSP and LKH-3 for two representative TSP and VRP variants, the Colored TSP (CTSP) and Capacitated VRP with Time Windows (CVRPTW).

cs.DS↗

arXiv2024

Narrowband parallel coherent LiDAR with frequency interleaving

The high demand for 3D imaging in intelligent robotics is motivating the advances of coherent LiDARs towards high performances with low complexity/cost. However, the current coherent LiDARs suffer from the tight coupling between the high ranging-imaging performance and the high complexity/cost. Herein, we propose a narrowband parallel coherent LiDAR with frequency-interleaving architecture. The LiDAR architecture utilizes narrowband signals for ranging, and interleaves multi-channel sparse and narrowband signals in frequency domain at the receiving end to significantly reduce the required bandwidth and the number of detection branches, facilitating massive parallelization with low system complexity/cost. In experiments, a ranging precision of 0.49 mm that approaches the shot noise limit, and a power sensitivity of -95 dBm (~9 photons) are achieved. Parallel 3D imaging with an equivalent imaging rate of 10 Mpixel/s and a 2 cm ranging precision is also demonstrated using only two 150 MHz receiving branches. With these desirable properties, this new LiDAR opens an avenue for the LiDAR ecosystem.

physics.optics↗

arXiv2024

New insight of time-transformed symplectic integrator I: hybrid methods for hierarchical triples

Accurate $N$-body simulations of multiple systems such as binaries and triples are essential for understanding the formation and evolution of interacting binaries and binary mergers, including gravitational wave sources, blue stragglers and X-ray binaries. The logarithmic time-transformed explicit symplectic integrator (LogH), also known as algorithmic regularization, is a state-of-the-art method for this purpose.However, we show that this method is accurate for isolated Kepler orbits because of its ability to trace Keplerian trajectories, but much less accurate for hierarichal triple systems. The method can lead to an unphysical secular evolution of inner eccentricity in Kozal-Lidov triples, despite a small energy error. We demonstrate that hybrid methods, which apply LogH to the inner binary and alternative methods to the outer bodies, are significantly more effective, though not symplectic. Additionally, we introduce a more efficient hybrid method, BlogH, which eliminates the need for time synchronization and is time symmetric. The method is implemented in the few-body code SDAR. We explore suitable criteria for switching between the LogH and BlogH methods for general triple systems. These hybrid methods have the potential to enhance the integration performance of hierarchial triples.

astro-ph.IM↗

arXiv2024

ALKPU: an active learning method for the DeePMD model with Kalman filter

Neural network force field models such as DeePMD have enabled highly efficient large-scale molecular dynamics simulations with ab initio accuracy. However, building such models heavily depends on the training data obtained by costly electronic structure calculations, thereby it is crucial to carefully select and label the most representative configurations during model training to improve both extrapolation capability and training efficiency. To address this challenge, based on the Kalman filter theory we propose the Kalman Prediction Uncertainty (KPU) to quantify uncertainty of the model's prediction. With KPU we design the Active Learning by KPU (ALKPU) method, which can efficiently select representative configurations that should be labelled during model training. We prove that ALKPU locally leads to the fastest reduction of model's uncertainty, which reveals its rationality as a general active learning method. We test the ALKPU method using various physical system simulations and demonstrate that it can efficiently coverage the system's configuration space. Our work demonstrates the benefits of ALKPU as a novel active learning method, enhancing training efficiency and reducing computational resource demands.

physics.comp-ph↗

arXiv2024

Global Challenge for Safe and Secure LLMs Track 1

This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme Office (CRPO) to foster the development of advanced defense mechanisms against automated jailbreaking attacks. With the increasing integration of LLMs in critical sectors such as healthcare, finance, and public administration, ensuring these models are resilient to adversarial attacks is vital for preventing misuse and upholding ethical standards. This competition focused on two distinct tracks designed to evaluate and enhance the robustness of LLM security frameworks. Track 1 tasked participants with developing automated methods to probe LLM vulnerabilities by eliciting undesirable responses, effectively testing the limits of existing safety protocols within LLMs. Participants were challenged to devise techniques that could bypass content safeguards across a diverse array of scenarios, from offensive language to misinformation and illegal activities. Through this process, Track 1 aimed to deepen the understanding of LLM vulnerabilities and provide insights for creating more resilient models.

cs.CR↗

arXiv2024

Unveiling the Binary Nature of NGC 2323

As a well-known open cluster, NGC 2323 (also called M50) has been widely investigated for over a hundred years and has always been considered a classical single cluster. In this work, with the help of Gaia DR3, we study the binary structure nature of this cluster. Although indistinguishable in the spatial space, the small but undeniable difference in the proper motion indicates that they may be two individual clusters. After investigating the properties of the two clusters, it is found that they have very close positions (three-dimensional $Δ$pos = 12.3 pc, $σ_{Δ\mathrm{pos}} = 3.4$ pc) and similar tangential velocities (two-dimensional $Δ$V = 2.2 km s$^{-1}$, $σ_{Δ\mathrm{V}} = 0.02$ km s$^{-1}$), indicating the existence of their physical association. Moreover, the best isochrone fitting ages of the two clusters are the same (158 Myr), further proving their possibly common origin. To comprehensively understand the formation and evolution of this binary cluster, we employ the PETAR $N$-body code to trace back their birthplace and deduce their dynamical evolutionary fate. With observational mean cluster properties, the simulations suggest that they may form together, and then orbit each other as a binary cluster for over 200 Myr. After that, because of their gradual mass loss, the two clusters will eventually separate and evolve into two independent clusters. Meanwhile, the numerical $N$-body simulation suggests that the less massive cluster is unlikely to be the cluster tidal tails created by the differential rotation of the Milky Way.

astro-ph.GA↗