arXiv subjects

Xian Chen

Publications and source records attributed to Xian Chen.

At least 37 records · Page 2Linked to original sources

arXiv2026

A Novel Method to Construct Frequency-Domain Gravitational Waveform for Accelerating Sources

Accurately modeling the inspiral-merger-ringdown (IMR) signal of coalescing compact objects is essential for the test of general relativity. However, it is known that astrophysical environments can distort gravitational-wave (GW) signal and, if ignored, may bias parameter estimation or even our understanding of gravity. Previous studies suggest that various astrophysical environmental effects can be modeled in a unified way by introducing an effective acceleration. However, such models are based on stationary phase approximation (SPA) and post-Newtonian (PN) formalism, which are inconsistent with the fast orbital evolution and strong gravity in the final merger-ringdown phase. To overcome this limit, we introduce frequency-domain spectral differentiation (FSD), which maps the time shift of the signal caused by acceleration into a differentiation in the frequency domain. The mapping does not rely on SPA or PN formalism, therefore can be used to construct the accelerated waveform across the entire IMR phases. We compare the FSD waveforms with the conventional SPA+PN ones, and find that the former more faithfully match the simulated signals of accelerating sources, especially in the merger-ringdown phase and when higher-order FSD corrections are included. A Fisher information matrix analysis suggests that FSD waveforms can achieve higher precision than SPA+PN waveforms in measuring effective acceleration. Therefore, the FSD method offers a more self-consistent treatment of various astrophysical environmental effects in the final merger-ringdown phase of binary GW sources.

astro-ph.HE↗

arXiv2026

Towards Realistic Detection Pipelines of Taiji: New Challenges in Data Analysis and High-Fidelity Simulations of Space-Based Gravitational Wave Antenna

Taiji, a Chinese space-based gravitational wave (GW) detection project, aims to explore the millihertz GW universe with unprecedented sensitivity. By observing astrophysical and cosmological sources, including Galactic binaries, massive black hole binaries, extreme mass-ratio inspirals, and stochastic gravitational wave backgrounds, etc., Taiji is expected to deliver transformative insights into astrophysics, cosmology, and fundamental physics. However, Taiji's data analysis faces unique challenges compared to ground-based detectors like LIGO-Virgo-KAGRA, such as the overlap of numerous signals, extended data durations, more rigorous accuracy requirements for the waveform templates, incompletely characterized noise spectra, non-stationary noises, and various data anomalies. Taking Taiji as a representative example, this paper reviews the data characteristics and data analysis challenges of space-based GW detection, and introduces the second round of Taiji Data Challenge, a collection of simulation datasets designed as a shared platform for resolving these critical issues. This platform distinguishes itself from previous works by the systematic integration of orbital dynamics based on a full drag-free and attitude control simulation, extended noise sources, more complicated and overlapping GW signals, second-generation time-delay interferometry, and the coupling effect of time-varying arm-lengths, etc. Concurrently released is the open-source toolkit Triangle, which offers the capabilities for customized simulation of signals, noises, and other instrumental effects. By taking a step further towards realistic detection, Taiji Data Challenge II and Triangle altogether serve as a new testbed, supporting the development of Taiji's global analysis and end-to-end pipelines, and ultimately bridging the gaps between observation and scientific objectives.

gr-qc↗

arXiv2026

Constraining the Fraction of LIGO/Virgo/KAGRA Binary Black Hole Merger Events Associated with Active Galactic Nucleus Flares

The formation channels of binary black hole (BBH) mergers detected by the LIGO/Virgo/KAGRA (LVK) network remain uncertain. While BBH mergers occurring inside active galactic nucleus (AGN) disks may interact with surrounding gas and generate observable optical flares. We test this scenario by quantifying the spatial and temporal correlation between BBH events in GWTC-4.0 and AGN flares identified from six years of the Zwicky Transient Facility (ZTF) DR23 data. Using 80 BBH mergers selected for adequate localization, redshift reach, observing-epoch overlap, and ZTF sky coverage, we construct a likelihood for the flare-associated fraction, $f_{\rm flare}$, that combines each event's 3D localization with a locally estimated flare number density derived from a 3D Voronoi tessellation, while explicitly accounting for survey boundaries and incomplete catalog coverage. Adopting a 200-day post-merger time window for potential counterparts, we infer $f_{\rm flare} = 0.07_{-0.05}^{+0.24}$ (90\% confidence level). This non-zero maximum-likelihood value is driven primarily by GW190412, for which a single flare candidate (J143041.67+355703.8) is consistent in both time and spatial position. The candidate's light curve is limited to two data points during its peak, so it remains classified only as a candidate AGN flare. Excluding GW190412 yields results consistent with no association and an upper limit of $f_{\rm flare} < 0.17$ at 90\% confidence level. The intrinsic properties of GW190412 and the characteristics of the candidate host AGN are broadly consistent with theoretical expectations for the AGN-disk formation channel, motivating continued, targeted electromagnetic follow-up of well-localized and highly asymmetric BBH mergers in current and upcoming time-domain surveys.

astro-ph.HE↗

arXiv2026

Super amplification of lunar response to gravitational waves driven by thick crust

The Moon has been long regarded as a natural resonator of gravitational waves (GWs) since 1960, showing great potential to fill the frequency gap left behind GW detections by ground- or space-based laser interferometry. However, the spatial variation of this amplification capacity on the Moon remains unclear. Here, we numerically simulate the lunar response to GWs by fully considering the fluctuant topography and laterally heterogeneous interior structures. Our results show that most regions on the Moon can amplify GWs with a ratio over 2, a finding significantly higher than previous estimations. Particularly, the amplification ratio can even reach factors of tens at the resonant frequency of ~0.015 Hz on the highlands surrounding the South Pole-Aitken (SPA) basin, where the regional crust is the thickest. Our findings establish the thick-crust regions as critical zones of GW amplification, which is essential for future landing site selection and instrumental setting for GW detection on the Moon.

astro-ph.EP↗

arXiv2025

Numerical simulation of lunar response to gravitational waves and its 3D topographic effect using the spectral-element method

The Moon has been regarded as a natural Weber bar capable of amplifying gravitational waves (GWs) for detecting events across a wide range of frequencies. However, accurately determining the amplification effects remains challenging due to the absence of 3D numerical simulation methods. In this study, we develop a high-order 3D finite element method (spectral-element method, SEM) to numerically simulate the lunar response to GWs below 20 mHz. We verify the accuracy of our method by comparing the resonant peaks of our results with those from semi-analytical solutions and find that the frequency deviation is less than 3% for the first peak at about 1 mHz and less than 0.8% for the subsequent peaks up to 10 mHz. Using this method, we evaluate the amplification of GW signals due to 3D topographic effects of the Moon, and we find enhancements at a series of specific frequency components. These results highlight the non-negligible effect of surface topography on the lunar response to GWs, as a fundamental factor that holds significant implications across both global and regional analyses. Our work paves the way for a comprehensive evaluation of the Moon's resonant response to GWs, helpful for the strategic planning of lunar GW detections.

astro-ph.EP↗

arXiv2025

Impact of mass transfer on the orbital evolution of a white dwarf close to an intermediate-mass black hole

Extreme mass ratio inspirals (EMRIs) of low-mass white dwarfs (WDs, 0.1 - 0.3 Msun) around spinning intermediate-mass black holes (IMBHs, 10^3 - 10^5 Msun) offer unique opportunities for multi-messenger astronomy, emitting both gravitational waves (GWs) and electromagnetic (EM) signals. Yet, despite their astrophysical relevance, theoretical models often omit key interactions between relativistic dynamics and phase-dependent mass transfer (MT). In this study, we integrate a perturbed Keplerian formalism with post-Newtonian (PN) corrections to simulate the relativistic orbit of a WD around a rotating IMBH, explicitly resolving the narrow phase near pericentre where Roche-lobe overflow initiates MT. We find that GW emission and MT exert competing influences on the orbit: MT episodes can increase both orbital period and eccentricity, potentially enabling the WD to avoid complete tidal disruption and even escape. We further quantify the GW phase evolution induced by MT, identifying parameter regimes in which GW detectors could observe a one-radian phase shift over observational timescales. Finally, we propose that the orbital expansion driven by MT may lead to the disappearance of quasi-periodic eruptions (QPEs). Our results underscore the necessity of jointly modeling relativistic effects and dynamic mass transfer in WD-IMBH systems.

astro-ph.HE↗

arXiv2025

Bayesian online collective anomaly and change point detection in fine-grained time series

Fine-grained time series data are crucial for accurate and timely online change detection. While both collective anomalies and change points can coexist in such data, their joint online detection has received limited attention. In this research, we develop a Bayesian framework capturing time series with collective anomalies and change points, and introduce a recursive online inference algorithm to detect the most recent collective anomaly and change point jointly. For scaling, we further propose an algorithm enhanced with collective anomaly removal that effectively reduces the time and space complexity to linear. We demonstrate the effectiveness of our approach via extensive experiments on simulated data and two real-world applications.

stat.ME↗

arXiv2025

Evidence of a fraction of LIGO/Virgo/KAGRA events coming from active galactic nuclei

The formation channels of the gravitational-wave (GW) sources detected by LIGO/Virgo/KAGRA (LVK) remain poorly constrained. Active galactic nucleus (AGN) has been proposed as one of the potential hosts, but the fraction of GW events originating from AGNs has not been quantified. Here, we constrain the AGN-origin fraction $f_{\rm agn}$ by analyzing the spatial correlation between GW source localizations ($O1\!-\!O4$a) and AGNs (SDSS DR16). We report preliminary evidence of an excess of lower-luminosity ($10^{44.5} \lesssim L_{\rm bol} \le 10^{45}~\!\mathrm{erg~s}^{-1}$) as well as lower-Eddington ratio ($0.01 \lesssim λ_{\rm Edd} \le 0.05$) AGNs around the LVK events, the explanation of which requires $f_{\rm agn} = 0.39^{+0.41}_{-0.32}$ and $0.29^{+0.40}_{-0.25}$ (90\% confidence level) of the LVK events originating from these respective AGN populations. Monte Carlo simulations confirm that this correlation is unlikely to arise from random coincidence, further supported by anomalous variation of the error of $f_{\rm agn}$ with GW event counts. These results support the theoretical speculation that some LVK events come from lower-luminosity or lower-accretion-rate AGNs, offering critical insights into the environmental dependencies of the formation of GW sources.

astro-ph.HE↗

arXiv2025

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation

Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommendation model can bring significant performance improvement. However, with a larger model scale, such prior studies have a significantly increasing gap from industry as they often neglect two fundamental challenges in industrial-scale applications. First, training and inference budgets are restricted for the model to be served, exceeding which may incur latency and impair user experience. Second, large-volume data arrive in a streaming mode with data distributions dynamically shifting, as new users/ads join and existing users/ads leave the system. We propose the External Large Foundation Model (ExFM) framework to address the overlooked challenges. Specifically, we develop external distillation and a data augmentation system (DAS) to control the computational cost of training/inference while maintaining high performance. We design the teacher in a way like a foundation model (FM) that can serve multiple students as vertical models (VMs) to amortize its building cost. We propose Auxiliary Head and Student Adapter to mitigate the data distribution gap between FM and VMs caused by the streaming data issue. Comprehensive experiments on internal industrial-scale applications and public datasets demonstrate significant performance gain by ExFM.

cs.IR↗

arXiv2025

Detecting Intermediate-mass Black Holes Using Miniature Pulsar Timing Arrays in Globular Clusters

Theoretical models predict that intermediate-mass black holes (IMBHs) exist in globular clusters (GCs), but observational evidence remains elusive. Millisecond pulsars (MSPs), which are abundant in GCs and have served as precise probes for gravitational waves (GWs), offer a unique opportunity to detect potential IMBH binaries in GCs. Here, we consider the possibility of using multiple MSPs in a GC to form a miniature pulsar timing array (PTA), so as to take advantage of their correlated timing residuals to search for potential IMBH binaries in the same cluster. Our semi-analytical calculations reveal that nearby IMBH binaries around MSPs in GCs could induce microsecond-level timing residuals. In GCs like $ω$ Centauri and M15, favorable configurations are found which could lead to the detection of binaries with mass ratios $q\gtrsim0.1$ and orbital periods of a few days. We estimate that future higher-precision timing programs could achieve $100$-nanosecond sensitivity, substantially expanding the searchable parameter space and establishing mini-PTAs as powerful detectors of IMBHs.

astro-ph.HE↗

arXiv2025

Physics-informed Machine Learning Analysis for Nanoscale Grain Mapping by Synchrotron Laue Microdiffraction

Understanding the grain morphology, orientation distribution, and crystal structure of nanocrystals is essential for optimizing the mechanical and physical properties of functional materials. Synchrotron X-ray Laue microdiffraction is a powerful technique for characterizing crystal structures and orientation mapping using focused X-rays. However, when grain sizes are smaller than the beam size, mixed peaks in the Laue pattern from neighboring grains limit the resolution of grain morphology mapping. We propose a physics-informed machine learning (PIML) approach that combines a CNN feature extractor with a physics-informed filtering algorithm to overcome the spatial resolution limits of X-rays, achieving nanoscale resolution for grain mapping. Our PIML method successfully resolves the grain size, orientation distribution, and morphology of Au nanocrystals through synchrotron microdiffraction scans, showing good agreement with electron backscatter diffraction results. This PIML-assisted synchrotron microdiffraction analysis can be generalized to other diffraction-based probes, enabling the characterization of nanosized structures with micron-sized probes.

cond-mat.mtrl-sci↗

arXiv2025

FerroAI: A Deep Learning Model for Predicting Phase Diagrams of Ferroelectric Materials

Composition-temperature phase diagrams are crucial for designing ferroelectric materials, however predicting them accurately remains challenging due to limited phase transformation data and the constraints of conventional methods. Here, we utilize natural language processing (NLP) to text-mine 41,597 research articles, compiling a dataset of 2,838 phase transformations across 846 ferroelectric materials. Leveraging this dataset, we develop FerroAI, a deep learning model for phase diagram prediction. FerroAI successfully predicts phase boundaries and transformations among different crystal symmetries in Ce/Zr co-doped BaTiO$3$ (BT)-$x$Ba${0.7}$Ca$_{0.3}$TiO$_3$ (BCT). It also identifies a morphotropic phase boundary in Zr/Hf co-doped BT-$x$BCT at $x = 0.3$, guiding the discovery of a new ferroelectric material with an experimentally measured dielectric constant of 9535. These results establish FerroAI as a powerful tool for phase diagram construction, guiding the design of high-performance ferroelectric materials.

cond-mat.mtrl-sci↗

arXiv2025

From First Draft to Final Insight: A Multi-Agent Approach for Feedback Generation

Producing large volumes of high-quality, timely feedback poses significant challenges to instructors. To address this issue, automation technologies-particularly Large Language Models (LLMs)-show great potential. However, current LLM-based research still shows room for improvement in terms of feedback quality. Our study proposed a multi-agent approach performing "generation, evaluation, and regeneration" (G-E-RG) to further enhance feedback quality. In the first-generation phase, six methods were adopted, combining three feedback theoretical frameworks and two prompt methods: zero-shot and retrieval-augmented generation with chain-of-thought (RAG_CoT). The results indicated that, compared to first-round feedback, G-E-RG significantly improved final feedback across six methods for most dimensions. Specifically:(1) Evaluation accuracy for six methods increased by 3.36% to 12.98% (p<0.001); (2) The proportion of feedback containing four effective components rose from an average of 27.72% to an average of 98.49% among six methods, sub-dimensions of providing critiques, highlighting strengths, encouraging agency, and cultivating dialogue also showed great enhancement (p<0.001); (3) There was a significant improvement in most of the feature values (p<0.001), although some sub-dimensions (e.g., strengthening the teacher-student relationship) still require further enhancement; (4) The simplicity of feedback was effectively enhanced (p<0.001) for three methods.

cs.HC↗

arXiv2025

Relativistic model of binary extreme-mass-ratio inspiral systems and their gravitational radiation

A binary extreme-mass-ratio inspiral (b-EMRI) is a hierarchical triple system consisting of a stellar-mass binary black hole (BBH) orbiting a central Kerr supermassive black hole (SMBH). Although predicted by several astrophysical models, b-EMRIs pose a challenge in waveform modeling due to their complex three-body dynamics and strong relativistic effects. Here we take advantage of the hierarchical nature of b-EMRI systems to transform the internal motion of the small binary into global trajectories around the SMBH. This allows us to use black hole perturbation theory to calculate both the low-frequency gravitational waveform due to its EMRI nature and the high-frequency waveform generated by the inner motion of the BBH. When the inner binary's separation vanishes, our calculation recovers the standard relativistic adiabatic EMRI waveform. Furthermore, by including the high-frequency perturbation, we find a correction to the waveform as large as the adiabatic order when the frequency matches the quasinormal modes (QNMs) of the SMBH, therefore supporting an earlier proof-of-concept study claiming that the small BBH can resonantly excite the QNMs of the SMBH. More importantly, we find that b-EMRIs can evolve faster than regular EMRIs due to this resonant dissipation through the high-frequency modes. These characteristics distinguish b-EMRI waveform templates from regular EMRI templates for future space-based gravitational-wave detectors.

gr-qc↗

arXiv2025

A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English

The dissemination of online hate speech can have serious negative consequences for individuals, online communities, and entire societies. This and the large volume of hateful online content prompted both practitioners', i.e., in content moderation or law enforcement, and researchers' interest in machine learning models to automatically classify instances of hate speech. Whereas most scientific works address hate speech classification as a binary task, practice often requires a differentiation into sub-types, e.g., according to target, severity, or legality, which may overlap for individual content. Hence, researchers created datasets and machine learning models that approach hate speech classification in textual data as a multi-label problem. This work presents the first systematic and comprehensive survey of scientific literature on this emerging research landscape in English (N=46). We contribute with a concise overview of 28 datasets suited for training multi-label classification models that reveals significant heterogeneity regarding label-set, size, meta-concept, annotation process, and inter-annotator agreement. Our analysis of 24 publications proposing suitable classification models further establishes inconsistency in evaluation and a preference for architectures based on Bidirectional Encoder Representation from Transformers (BERT) and Recurrent Neural Networks (RNNs). We identify imbalanced training data, reliance on crowdsourcing platforms, small and sparse datasets, and missing methodological alignment as critical open issues and formulate ten recommendations for research.

cs.CL↗

arXiv2025

A Recent Supermassive Black Hole Binary in the Galactic Center Unveiled by the Hypervelocity Stars

When a binary of early-type stars from the young stellar populations in the Galactic center (GC) region is scattered to the vicinity of the supermassive black hole (SMBH) Sgr~$\rm{A}^{*}$, one of the components would be tidally ejected as an early-type hypervelocity star (HVS) and the counterpart would be captured on a tight orbit around Sgr~$\rm{A}^{*}$. Dozens of B-type HVSs moving faster than the Galactic escape speed have been discovered in the Galactic halo and are produced most likely by the SMBH Sgr~$\rm{A}^{*}$. However, the velocity distribution and in particular the deficit of the HVSs above $700\, \rm{km\, s^{-1}}$ is seriously inconsistent with the expectations of the present models. Here we show that the high-velocity deficit is due to the deficiency in close interactions of stars with the SMBH Sgr~$\rm{A}^{*}$, because an orbiting intermediate-mass black hole (IMBH) of about 15,000 Solar mass kicked away slowly approaching stars 50--250 million years ago. The SMBH-IMBH binary formed probably after the merger of the Milky Way with the Gaia-Sausage-Enceladus dwarf galaxy, and coalesced about 10 million years ago, leading to a gravitational recoil of Sgr~$\rm{A}^{*}$ at a velocity of 0.3--0.5$\, \rm{km\, s^{-1}}$ and to a change of the HVS ejection scenarios. The SMBH-IMBH binary scenario predicts the formation of the S-star cluster at the GC with the distribution of the orbital size and stellar ages that are well consistent with the observations.

astro-ph.HE↗

arXiv2025

2D numerical simulation of lunar response to gravitational waves using finite element method

Previous studies of the response of the Moon to gravitational waves have been carried out using analytical or semi-analytical models assuming ideal lunar structures. Such models are advantageous for their high-speed calculation but fail to account for the extremely heterogeneous subsurface and/or interior structures of the Moon. Numerical calculations are needed, but it is challenging to model the topography and lateral heterogeneity of the Moon. In addition, the computational cost is great especially when performing the GW simulation for a long time. As a first step towards overcoming the above difficulties, we employ a two-dimensional finite element method to numerically simulate the lunar response to gravitational waves. We verify our method by comparing our numerical results with those semi-analytical solutions. Based on such comparison, we also analyze the limitation of the two-dimensional simulation. Our work breaks a new way towards the precise simulation of realistic lunar response to gravitational waves in the future and lays down a solid foundation for three-dimensional numerical simulations.

astro-ph.EP↗

arXiv2025

Probing intermediate-mass black hole binaries with the Lunar Gravitational-wave Antenna

New concepts for observing the gravitational waves (GWs) using a detector on the Moon, such as the Lunar Gravitational-wave Antenna (LGWA), have gained increasing attention. By utilizing the Moon as a giant antenna, the LGWA is expected to detect GWs in the frequency range from 1 millihertz (mHz) to several hertz, with optimal sensitivity in the decihertz band. Despite the debated formation and evolution channel of intermediate-mass black holes (IMBHs) with masses in the range of $[10^2, 10^5]\ {\rm M_\odot}$, binary systems containing at least one IMBH are widely believed to generate GWs spanning from mHz to a few Hz, making them a key scientific target for the LGWA. We explore the detectability of IMBH binaries with the LGWA in this work. The LGWA is more sensitive to nearby binaries (i.e. with redshift $z\lesssim0.5$) with the primary mass $m_1 \in [10^4, 10^5] \ {\rm M_\odot}$, while it prefers distant binaries (i.e. $z \gtrsim 5$) with $m_1 \in [10^3, 10^4] \ {\rm M_\odot}$. Considering a signal-to-noise ratio threshold of 10, our results imply that the LGWA can detect IMBH binaries up to $z \sim \mathcal{O}(10)$. We further show that the LGWA can constrain the primary mass with relative errors $\lesssim 0.1\%$ for binaries at $z \lesssim 0.5$. Furthermore, we show that the IMBH binaries at $z \lesssim 0.1$ can be used to constrain redshift with relative errors $\lesssim 10\%$, and those with $m_1 \in [10^4, 10^5] \ {\rm M_\odot}$ can be localized by the LGWA to be within $\mathcal{O} (10)$ $\rm deg^2$.

astro-ph.HE↗