arXiv subjects

Huan Yang

Publications and source records attributed to Huan Yang.

At least 19 recordsLinked to original sources

arXiv2026

How significant is the lensing interpretation of GW231123?

GW231123 is one of the most unusual gravitational-wave (GW) events, with exceptionally large inferred masses and near-extremal spins, offering an opportunity to test whether propagation effects contribute to these properties. We therefore examine whether the data support wave-optics microlensing embedded in a strong-lensing galaxy, whose detection becomes increasingly likely as observations accumulate, whether this interpretation can explain these properties, and how significant the preference remains under detector noise and waveform systematics. We compare six hypotheses: unlensed, isolated point mass, and embedded point-mass (EPM) and binary-lens (EB) effective models in Type-I (minimum) and Type-II (saddle) macro images. The EB Type-I model is most favored. For the most accurate waveform model NRSur7dq4, it gives $\log_{10}B^{\rm EB-I}_{\rm U}=2.60$, versus $0.89$ for Type II, indicating sensitivity to macro-image geometry. Within Type I, however, the binary improves over the point mass by only $\log_{10}B^{\rm EB-I}_{\rm EPM-I}=0.16$ and $Δ\ln\mathcal{L}_{\max}=0.56$, providing no clear evidence for structure beyond a single effective perturber. Moreover, under embedded lensing, waveform-template discrepancies and inferred masses and spins are reduced. However, real O4a backgrounds from numerical-relativity injections show that the apparent lensing evidence is sensitive to waveform systematics and realistic detector noise: although the commonly used waveform IMRPhenomXPHM gives the largest Bayes factor, $\log_{10}B^{\rm EB-I}_{\rm U}=4.52$, it is less exceptional relative to its own background, with a false-alarm probability of $6.5$--$8\%$, whereas NRSur7dq4 gives only $2$--$3\%$. Thus, waveform systematics can amplify apparent lensing evidence, but GW231123 remains an intriguing lensing candidate.

astro-ph.GA↗

arXiv2026

Identifying Kilonovae in the Presence of Optical Afterglow for the Wide Field Survey Telescope

Identifying kilonovae associated with binary neutron star mergers is often complicated by the presence of a dominant synchrotron afterglow. In this work, we evaluate the performance of the Wide Field Survey Telescope (WFST) in identifying kilonova signals in composite afterglow-kilonova transients. Using a numerical framework based on the Fisher information matrix, we simulate $10,000$ realizations for each of two scenarios: an AT2017gfo-based template model and a physically sampled population that accounts for kilonova diversity. Our results indicate that kilonova identification is primarily limited by source distance. In both scenarios, the identification efficiency is largely insensitive to variations in afterglow microphysical parameters and exceeds $80\%$ at distances within approximately $600~\rm Mpc$ for AT2017gfo-like events. Under our adopted assumptions and a short gamma-ray burst (sGRB)-triggered target-of-opportunity (ToO) observational strategy, we estimate that the WFST could identify $0.1-1.2$ kilonovae per year in the optimistic scenario. Furthermore, we find that the discriminating power of color-based filters rapidly saturates, reaching a stable plateau by the second night after the merger. We therefore propose a staged observing strategy that prioritizes high-cadence $g$ and $r$-band monitoring during the first night and incorporates the $z$ band from the second night onward. This strategy improves the identification precision by exploiting the increasingly prominent red excess produced by the kilonova. Our results provide a physical basis for optimizing WFST observing resources to efficiently detect and characterize kilonovae in the multimessenger era.

astro-ph.HE↗

arXiv2026

A nonlinear voice from GW250114 ringdown

Gravitational-wave astronomy, by detecting ripples in spacetime, has opened a new window to observe compact objects and probe theories of gravity in the nonlinear strong-field regime. The ringdown signal of a binary black hole merger contains a superposition of damped sinusoids known as quasi-normal modes (Ref.[1]), whose frequencies are completely determined by the mass and spin of the remnant black hole and form the basis of black hole spectroscopy (Refs.[2-4]). A crucial prediction yet to be observationally confirmed is the existence of quadratic quasi-normal modes, which represent fundamental properties associated with wave-wave coupling in general relativity, and the leading mode is predicted to be detectable with next-generation ground-based detectors (Refs.[5-7]) using traditional methods. Here we show the first observational evidence for a set of quadratic quasi-normal modes in the ringdown of the binary black hole merger GW250114, the loudest gravitational-wave event detected to date, enabled by a novel analysis. These nonlinear modes result from the quadratic coupling of the linear $(2,2,n)$ modes with $n\leq3$. Starting the analysis at a time corresponding to four times the remnant mass ($M_\mathrm{f}$) after the merger, the evidence for their presence reaches a Bayes factor of 62. A phenomenological test allowing these modes to deviate from the theoretical prediction rejects the zero-amplitude hypothesis at a significance of 3.4 $σ$, while the inferred amplitude and complex frequency are consistent with the prediction of general relativity. This finding provides the first observational evidence of gravitational wave-wave interaction and extends black hole spectroscopy from the linear to the nonlinear regime. It also establishes a new direction for testing the fundamental nonlinear structure of general relativity with the most extreme gravity.

gr-qc↗

arXiv2026

Gravitational lensing of gravitational waves by galaxy clusters

Strongly lensed gravitational waves (GWs) are commonly searched for using population priors, including time-delay and magnification-ratio distributions, to suppress false alarms. Current LIGO, Virgo, and KAGRA (LVK) searches mainly adopt priors calibrated with galaxy-scale lenses; however, these may penalize the longer time delays produced by galaxy clusters, which could contribute 10%--20% of lensed events. Cluster member galaxies may also perturb the macro-lens potential and alter image magnifications. We investigate the time-delay and magnification-ratio distributions of binary black hole GWs lensed by galaxy clusters, together with microlensing systematics. In the full lensed sample, the median time delay is about 76 days for cluster lenses, compared with 6.9 days for galaxy lenses. After imposing an SNR threshold of $ρ>8$ at LVK O4 sensitivity, the medians are 15.4 and 0.24 days. The detected cluster sample retains a long-delay tail, with 9.1% of image pairs delayed by more than 365 days and 3.3% by more than 1000 days, so galaxy-based time-delay priors can suppress cluster-lensed pairs. By contrast, although cluster member galaxies broaden the magnification-ratio distribution of the full cluster sample, the detected cluster- and galaxy-lensing samples are very similar at O4 sensitivity, suggesting little bias in candidate selection. Cluster lenses also generally produce weak microlensing distortions: only about 0.8% of single-image mismatches exceed ${\cal M}=0.03$, while 4.8% exceed the parameter-estimation threshold $1.35/ρ^2$. Thus, microlensing is subdominant for most cluster-lensed events, mainly because images often form far from the brightest cluster galaxy, where the stellar density is low and dominated by intracluster light, although nearby satellites can locally enhance it. These results motivate a dedicated cluster-lensing pipeline for GW lensing searches.

astro-ph.GA↗

arXiv2026

From Stars to Waves: Non-deterministic Inference of Microlensed Gravitational Waves

Strongly lensed gravitational waves may pass through the stellar field of a lensing galaxy with additional modulations (on both phase and amplitude) due to gravitational microlensing effect of stars/remnants near the line of sight. These microlensed waveforms depend on the mass and location of thousands or more most relevant stars, so that their deterministic reconstruction from the data is computationally prohibitive. We classify the detection and parameter estimation of such events as non-deterministic inference problem and propose a solution with the implementation of normalizing flows. As a first step, we show that $8\%$ of microlensed events can be detected with significance $\ge 3 σ$ in the third generation era, with the chosen microlensing parameters correlated with the density of the underlying stellar field. This approach opens the door to probing microlensing effects and the properties of the underlying stellar fields. A similar construction may also be applied to other non-deterministic inference problems, such as detecting post-merger gravitational waves from binary neutron star coalescence and signals from core-collapse supernovae.

gr-qc↗

arXiv2026

Modified Teukolsky Formalism for Extreme Mass-Ratio Inspirals in Higher-Derivative Gravity

In this work, we study a model problem involving a point particle spiraling into a non-rotating black hole in higher-derivative theories of gravity. In such theories, both the background spacetime and the generation and propagation of gravitational waves differ from those in General Relativity. We develop a modified Teukolsky formalism to describe gravitational waves sourced by the point particle and, as an illustrative example, compute the resulting fluxes to the black hole horizon and null infinity for a cubic gravity theory. The formalism is constructed in a way that can be naturally extended to rotating black holes. These results represent essential steps to build extreme mass-ratio-inspiral waveforms in modified gravity theories, which may also be rescaled to approximate waveforms from comparable-mass binary black hole systems, analogous to existing approaches in General Relativity.

gr-qc↗

arXiv2026

From the Test-Mass Limit to Binary Black-Hole Waveforms in Higher-Derivative Gravity

Many higher-derivative theories predict stronger deviations from General Relativity for lower-mass black holes, while their nonlinear field equations often prevent reliable simulations of the full binary evolution. Here we develop a route from controlled black hole perturbation theory based on the modified Teukolsky formalism to comparable-mass waveforms, using parity-even cubic gravity as a representative example. We find that the tidal response of the secondary black hole enters at the same perturbative order as the direct higher-curvature correction and is therefore essential for a consistent leading-order waveform. The resulting strong-field fluxes and conservative dynamics produce an accumulated inspiral dephasing that grows toward merger. Embedding this test-mass information into an effective-one-body model, we construct inspiral-merger-ringdown waveforms for comparable-mass binaries and find coupling-dependent dephasing and waveform-peak shifts. Our results demonstrate how strong-field test-mass calculations can anchor waveform models for higher-derivative gravity when theory-specific numerical-relativity simulations are unavailable.

gr-qc↗

arXiv2026

Gamma-ray Emission from the S147 Region: Indication of Escaping Cosmic Rays Interacting with Molecular Clouds

We present a detailed analysis of $γ$-ray emission from the middle-aged supernova remnant (SNR) S147 (G180.0$-$1.7) using approximately 16.5 years of Fermi-LAT data. Spatially, a new extended $γ$-ray component distinct from the emission associated with the H$α$ filaments of the SNR shell is identified. This new component exhibits a strong spatial correlation with dense molecular clouds (MCs) identified in CO emission at Local Standard of Rest velocities of $0$--$5\,\mathrm{km\,s^{-1}}$. Spectrally, the cloud-associated emission implies an underlying cosmic-ray (CR) proton population described by a hard power-law with an index of $Γ\approx 2.1$, compatible with the standard diffusive shock acceleration prediction. We interpret the $γ$-ray emission in this region with a hadronic scenario involving two distinct CR populations: trapped CRs reaccelerated within the radiative SNR shell as proposed in previous work, and escaping CRs illuminating the nearby MCs. The derived CR proton intensity in the MC region significantly exceeds the local Galactic background measured by AMS-02, consistent with the interpretation that the cloud is illuminated by particles accelerated by S147. These findings provide observational support for a CR-escape scenario during the earlier evolutionary phases of this middle-aged SNR and highlight the S147 MC component as a potential candidate for detection at TeV energies by LHAASO.

astro-ph.HE↗

arXiv2026

Imaging Stars at the Quantum Compatibility Limit

Imaging astrophysical sources with a multi-station interferometer is intrinsically a multiparameter quantum-estimation problem. {Using tools from multiparameter quantum metrology,} we show that time-resolved repetitive or adaptive measurements in an $N$-station array suffer a fundamental array-level incompatibility among visibility estimators. Collective measurements, {which coherently process the received starlight across multiple time bins in a single joint readout}, remove the array-size penalty up to an order-unity factor, yielding an asymptotic $O(\sqrt{N})$ enhancement for the {directional-averaged} SNR of visibility measurement. We then propose a memory-assisted interferometric architecture designed to implement collective readout through coherent storage and joint quantum processing. Imaging simulations and Fisher-information analyses demonstrate that collective measurements improve image reconstruction in near-term arrays and enhance the resolving power of future long-baseline architectures, with pronounced benefits for representative AGN targets such as NGC~4151 and 3C~273. These results highlight collective measurement as a promising building block for future quantum-assisted interferometric arrays for stellar imaging.

quant-ph↗

arXiv2026

Gravitational Waves from Green's Function Decomposition for a Kerr black hole: I. Equatorial ISCO Plunge

We present a decomposition of the Kerr Green's function in the time domain, motivated by the frequency-domain split previously studied in the Schwarzschild limit. We show that the identification of a quasinormal-mode contribution, a direct part, and a late-time tail is still available, where the split times are determined by the black hole spin and positions of the emitter and receiver. We have checked this Green's function with time-domain Teukolsky numerical simulations and find excellent agreement. We also apply this decomposed Green's function in the time domain to a model problem with a test particle plunging into a Kerr black hole. The dynamically excited direct wave and quasinormal modes are obtained by convoluting the Green's function with the particle's source term, which may be viewed as the first order in mass ratio of a spinning black hole ringdown.

gr-qc↗

arXiv2026

SpatialDiff: 3D-Aware Object Movement via Implicit Spatial Modeling

Recent advances in image editing allow impressive manipulation of objects, existing methods still struggle to handle spatial movement in complex scenes, such as objects span different depth layers or are partially occluded. Most image editing methods focus solely on prior information from 2D datasets, emphasizing planar features while lacking support for spatial structures. Even approaches that incorporate explicit positional information fail to capture true 3D spatial relationships, thus limiting accurate object movement in complex scenes. In this paper, we present SpatialDiff, a method that effectively captures 3D spatial structures, enabling precise and consistent object movements in complex scenes. Our core innovations are twofold: (1) Implicit 3D Spatial Modeling, which introduces 3D prior knowledge and enables the model to internally build a comprehensive understanding of the three-dimensional spatial structure; and (2) Global Spatial Supervision, which constrains the latent spatial features to enable the model to perceive changes in object spatial positions caused by editing operations. Experimental results demonstrate that our method significantly improves the accuracy and fidelity of spatial movement in complex scenes.

cs.CV↗

arXiv2026

Probing Intrinsic Ellipticity in Compact Star Binaries

We present a novel resonance mechanism that can occur in {compact-star} binaries: a spin-orbit resonance. This resonance locks the binary into a unique state where {the spin of one component} evolves alongside the orbit. The resonance requires this component to possess a finite ellipticity $ε$, and we find that the locking probability is proportional to $\sqrtε$. We show that resonance locking and its subsequent breaking produce a characteristic phase signature in the gravitational waveform, opening a new observational channel for probing intrinsic ellipticity in compact-star binaries, including exotic compact objects. In addition, as an illustrative astrophysical scenario, we discuss magnetars, whose strong internal fields can source the required ellipticity and may place the signal in the ground-based low-frequency band, although their abundance at merger remains uncertain. We have also conducted a search in all neutron star binaries up to the O4a gravitational-wave catalog, with no positive event found so far.

astro-ph.HE↗

arXiv2026

Black hole spectroscopy: from theory to experiment

The "ringdown" radiation emitted by oscillating black holes has great scientific potential. By carefully predicting the frequencies and amplitudes of black hole quasinormal modes and comparing them with gravitational-wave data from compact binary mergers we can advance our understanding of the two-body problem in general relativity, verify the predictions of the theory in the regime of strong and dynamical gravitational fields, and search for physics beyond the Standard Model or new gravitational degrees of freedom. We summarize the state of the art in our understanding of black hole quasinormal modes in general relativity and modified gravity, their excitation, and the modeling of ringdown waveforms. We also review the status of LIGO-Virgo-KAGRA ringdown observations, data analysis techniques, and the bright prospects of the field in the era of LISA and next-generation ground-based gravitational-wave detectors.

gr-qc↗

arXiv2026

NormGuard: Reward-Preserving Norm Constraints in Flow-Matching Reinforcement Learning

Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that are not captured by the reward proxy. We identify a simple structural signature of this drift: across three post-training methods (NFT, AWM, DPO), RL fine-tuning inflates the per-step velocity norm $\|v_θ\|$ by $5\%$ to $15\%$ relative to the reference. A form of norm inflation has been studied in classifier-free guidance (CFG), where rescaling the velocity back to a reference norm at inference time can mitigate the resulting artifacts. However, this inference-time correction does not transfer cleanly to RL: rescaling $v_θ$ to match $\|v_{\text{ref}}\|$ at inference time neither improves reward nor fixes the quality degradation, because the inflation is co-adapted into the model weights. Furthermore, an adjoint sensitivity analysis shows that velocity magnitude rescaling carries no coherent first-order reward signal at the batch level, indicating that suppressing norm inflation is unlikely to remove a consistently reward-carrying component. Since inference-time renormalization fails while norm suppression carries no reward cost, training-time intervention is the appropriate strategy. Together, these findings motivate NormGuard, a hinge penalty that activates only when $\|v_θ\|$ exceeds $\|v_{\text{ref}}\|$ and composes additively with any velocity-local base loss. Across two base models, three post-training methods, and two reward proxies, NormGuard consistently improves MLLM-judged image quality and forensic realism while preserving reward, with gains that amplify under few-step inference and are not explained by early stopping.

cs.LG↗

arXiv2026

Torsional-X Seismometer for Lunar Decihertz Gravitational-Wave Detection

The lunar gravitational-wave antenna concept uses the Moon as a resonant detector instrumented with precision seismometers, targeting the decihertz band between ground- and space-based observatories. We propose a compact monolithic fused-silica torsional-X seismometer that re-engineers garden-gate acceleration-to-rotation transduction for this regime through a high-tension dual-fiber suspension. Its designed millihertz-scale resonance and ultra-low mechanical dissipation enable a nearly order-of-magnitude improvement around $0.1\,\mathrm{Hz}$ compared with existing lunar seismometer concepts. Achieving this performance requires room-temperature operation, where fused-silica exhibits low mechanical loss, together with subdominant actuation noise. We demonstrate a room-temperature vacuum prototype validating the operating principle and core mechanical design, and derive requirements for a future lunar implementation capable of approaching the target sensitivity.

astro-ph.IM↗

arXiv2026

Making Image Editing Easier via Adaptive Task Reformulation with Agentic Executions

Instruction guided image editing has advanced substantially with recent generative models, yet it still fails to produce reliable results across many seemingly simple cases. We observe that a large portion of these failures stem not from insufficient model capacity, but from poorly formulated editing tasks, such as those involving small targets, implicit spatial relations, or under-specified instructions. In this work, we frame image editing failures as a task formulation problem and propose an adaptive task reformulation framework that improves editing performance without modifying the underlying model. Our key idea is to transform the original image-instruction pair into a sequence of operations that are dynamically determined and executed by a MLLM agent through analysis, routing, reformulation, and feedback-driven refinement. Experiments on multiple benchmarks, including ImgEdit, PICA, and RePlan, across diverse editing backbones such as Qwen Image Edit and Nano Banana, show consistent improvements, with especially large gains on challenging cases. These results suggest that task reformulation is a critical but underexplored factor, and that substantial gains can be achieved by better matching editing tasks to the effective operating regime of existing models.

cs.CV↗

arXiv2026

A UAV-Based Multi-Modal Vision System for Automated Sideslope Deformation Monitoring and Hazard Detection

Slope hazards constitute a major safety threat to expressway infrastructure, and their evolution is typically manifested as slow surface deformation. Conventional manual inspection suffers from low efficiency and inadequate operational safety, especially on severely deteriorated slopes. Accordingly, there is an urgent need for an automated, high-precision solution capable of large-area slope observation and analysis. This study aims to develop a highly automated workflow for slope hazard detection using Unmanned Aerial Vehicle (UAV)-borne Light Detection and Ranging (LiDAR). The proposed workflow consists of a shared data-acquisition and ground-surface extraction stage, a single-observation hazard-screening branch based on RandLA-Net, and a multi-epoch deformation-monitoring branch based on grid-wise elevation differencing. To validate the effectiveness of the proposed system, we conducted multiple UAV-borne LiDAR data-acquisition flights in real expressway slope environments. The results show that the workflow can extract usable ground-surface point clouds under vegetation cover, identify potential hazard zones from single-observation point clouds, and quantify centimeter-level elevation changes using multi-epoch grid differencing. This study establishes an end-to-end UAV-borne LiDAR-based workflow for slope inspection and demonstrates its feasibility through controlled experiments, field tests, and simulation-based validation, thereby providing an implementable solution for automated slope-hazard monitoring and intelligent early warning.

cs.CV↗

arXiv2026

Towards Efficient and Secure Cloud-Assisted Autonomous Systems: A Review of Architectures, Algorithms, Security, and Deployment Challenges

Networked Control Systems (NCSs) have been instrumental in realizing fully connected and responsive intelligent environments within the context of real-time virtual control and management. However, traditional NCSs face considerable challenges in handling the vast amounts of data generated by large-scale control applications, particularly in terms of data acquisition, storage, and computational processing. To address these challenges, the emergence of cloud computing and advancements in control theory have empowered the new paradigm known as Cloud Control Systems (CCSs). Recently, CCSs have received substantial attention from industries for their potential properties, such as large-scale data management, complex computations, and data-centric optimized decisions. This study presents an extensive review of recent progress in CCSs spanning over multiple studies published between 2012 and 2025. Specifically, the focus is on providing a taxonomy of the current findings in CCS research, encompassing various perspectives, such as its efficient implementations in industrial automation, security and privacy considerations, and cloud-based control techniques. Each category is examined in depth through selected state-of-the-art analyses of different approaches and contrasting methodologies. Furthermore, we discuss future directions aimed at designing more efficient and practical CCSs. The insights gained from this study can help researchers, practitioners, and decision-makers in their domain for effective CCS design and deployment.

eess.SY↗