arXiv subjects

Xiaowei Liu

Publications and source records attributed to Xiaowei Liu.

At least 19 recordsLinked to original sources

arXiv2026

Rapid Variability and Broadband Spectral Modeling in the Flaring Activity of BL Lacertae

We report a multi-wavelength study of two flaring episodes of the blazar BL Lacertae during MJD 60500-60800 (9 July 2024 - 5 May 2025). The source reached a daily-averaged $\gamma$-ray flux of $(1.03 \pm 0.05) \times 10^{-5} \, \mathrm{ph \, cm^{-2} \, s^{-1}}$ ($E > 100$ MeV) on MJD 60588 (5 October 2024). Using orbit-binned data from the Large Area Telescope (LAT) onboard the \textit{Fermi Gamma-ray Space Telescope}, we identify a minimum flux halving timescale of $\tau = 1.33 \pm 0.29$ hr. This constrains the upper limit on the $\gamma$-ray emitting region size to $R \le 2.0 \times 10^{15}$ cm, as well as its distance from the central supermassive black hole to $R_\mathrm{H} \le 5.9 \times 10^{16}$ cm, assuming a Doppler factor of $\delta = 14.8$ derived from the spectral energy distribution (SED) modeling. We find tentative evidence for sub-minute $\gamma$-ray variability with a minimum doubling time of $0.7 \pm 0.2$ min ($p$-value = 0.03). This may originate from an extremely compact region with a size of $R \le 1.8 \times 10^{13}$ cm, suggesting that the emission arises from magnetohydrodynamic substructures, such as plasmoids within a magnetic reconnection zone. Spectral analysis reveals a significant ``softer-when-brighter'' trend ($r = 0.96, p = 4.5 \times 10^{-4}$) during the minute-scale flare peaks, indicating a complex interplay between particle acceleration and radiative cooling. The SED is reproduced using a one-zone leptonic model, in which synchrotron self-Compton (SSC) and external Compton (EC) scattering effectively account for the high-energy emissions. The reduced magnetic field strengths and hard electron injection spectral indices observed during the flaring states suggest enhanced particle acceleration efficiency, possibly associated with relativistic magnetic reconnection.

astro-ph.HE↗

arXiv2026

Early Near-Infrared Excess and Rapid Disk-Corona Evolution in the Tidal Disruption Event 2024aepd

We present multi-wavelength observations of the tidal disruption event (TDE) 2024aepd, spanning primarily the first $\sim$300 days after discovery. The X-ray spectrum is initially dominated by a thermal disk component accompanied by a hard excess. From $\sim$178 days onward, the spectrum becomes power-law dominated and subsequently hardens, indicating the rapid emergence and strengthening of a hot corona. A prominent near-infrared (NIR) excess is detected as early as $\sim40$ days. Its nearly flat power-law spectrum strongly deviates from the Rayleigh-Jeans tail of the UV-optical blackbody. Although a conventional dust-echo origin cannot be completely ruled out, free-free emission from a reprocessing photospheric envelope provides a more plausible explanation. Moreover, the UV-optical-to-NIR break shifts to higher frequencies as the density-profile index remains nearly constant, implying evolving reprocessing conditions within a broadly unchanged density structure. Together with AT2019azh and TDE 2025abcr, TDE 2024aepd is the third TDE reported to exhibit an early-time NIR excess. A larger sample with early-time NIR coverage is needed to determine whether such excesses are common among TDEs.

astro-ph.HE↗

arXiv2026

Divergent Evolution of Radial Metallicity Gradients in the Thin and Thick Disks of the Milky Way

Using 200,388 red clump stars from LAMOST and APOGEE, we investigate the radial metallicity gradients of the Galactic disk as a function of vertical height and stellar age. The thin disk displays a pronounced negative radial metallicity gradient near the Galactic mid-plane that progressively flattens with increasing $|Z|$, following $\Delta \mathrm{[Fe/H]}/\Delta R$ = $-$0.0784 $+$ 0.0776 (1 $-$ exp ($-$ $|Z|$/1.42)). The thin disk also exhibits a clear age dependence in radial metallicity gradients, evolving smoothly from a strong gradient regime for young stars to a weak gradient regime for old stars, following $\Delta \mathrm{[Fe/H]}/\Delta R$ = $-$0.0438 $+$ 0.0233 tanh (($\tau$ $-$ 11.29)/4.21). The thick disk shows weakly positive radial metallicity gradients that remain statistically invariant with respect to both vertical height and stellar age, following respectively, $\Delta \mathrm{[Fe/H]}/\Delta R$ = 0.0038 $+$ 0.0009 $|Z|$ and $\Delta \mathrm{[Fe/H]}/\Delta R$ = 0.0146 $-$ 0.0007 $\tau$. These results indicate that the thin disk retains radial metallicity gradients shaped by relatively ordered inside-out growth and long-term secular evolution processes. The thick disk exhibits spatially and temporally homogeneous radial metallicity gradients, which are consistent with a formation environment characterized by mergers of gas-rich systems and/or the turbulent ISM.

astro-ph.GA↗

arXiv2026

JourneyFormer: Encoding Airbnb Guest Journey with Sequence Modeling

Sequence modeling has become increasingly popular in recommendation and ranking algorithms, owing to its capacity to model users' historical behaviors and infer user intentions. Despite its theoretical simplicity, the practical deployment of a sequence model in production is non-trivial due to complexity of the sequence and sparse labels. For example, in Airbnb, guest sequences are often long, exploratory and complex, and we focus on booking labels, which are sparse. As such, we are often required to make various design decisions regarding data and modeling to strike a balance between effectiveness and scalability. This work delved into these production challenges and deployed JourneyFormer, a sequence modeling solution for search ranking at Airbnb. We detail crucial design considerations, covering aspects such as guest event selection, ID embeddings, model architecture, and label attribution. Additionally, we describe several tailored strategies to accelerate model training and inference. JourneyFormer has been successfully deployed within Airbnb's production, where its effectiveness and impact have been evidenced not only by improved offline ranking metrics but also by significant gains in key business metrics through online A/B testing across 2 production surfaces.

cs.LG↗

arXiv2026

X-rays breaking out of pre-explosion ejecta mark a supernova's first light

Massive stars die as core-collapse supernovae, whose optical light emerges days after the implosion. Theory predicts that the initial collapse-driven shock, upon breaking through the star and dense circumstellar medium, emits a brief thermal flash of soft X-rays and ultraviolet. Yet these elusive first signals have remained largely undetected, owing to limited wide-field soft X-ray monitoring. Here we report the discovery of a soft X-ray flash, EP260321a, followed days later by a broad-lined supernova from an envelope-stripped progenitor. Its X-ray spectrum, best modeled with blackbody, establishes it as the long-sought archetypal shock breakout. The burst's duration and energetics place the breakout at a radius of 300 solar radii, tracing a dense surrounding shell and revealing abrupt mass ejection within the final month before collapse.

astro-ph.HE↗

arXiv2026

CASTLE: Contrastive and Seed-Guided Training for Cold-Start Natural Language Search

Deploying natural language search systems presents a critical cold-start challenge: no real user queries to learn linguistic patterns, and no relevance labels to train ranking models. We present CASTLE (Contrastive And Seed-guided Training for natural Language sEarch), an LLM-based framework for generating synthetic queries and relevance labels from structured catalog data, powering Airbnb's natural language search across its full lifecycle. CASTLE makes three contributions. First, we generate realistic queries by combining structure-guided prompting with seed queries from user research, using template, few-shot, and attribute-grounded prompt variants together with explicit variety mechanisms to prevent query collapse. Second, we produce relevance labels by construction via contrastive listing pairs derived from booking sessions, achieving near-zero false positives without LLM judgment. Third, CASTLE's structured input design is flexible: incorporating richer signals such as guest reviews and photo captions alongside listing attributes enables generation of niche, long-tail queries that reflect subjective user preferences (e.g., "cozy cabin with fireplace") beyond what catalog attributes alone can express. Compared against InPars-style, Promptagator, and contrastive-only baselines, CASTLE achieves KL 1.01 vs. real users -- a 9.2x improvement over the best baseline (9.33) -- and the lowest attribute-type KL divergence (0.08), outperforming even survey seed queries (0.09). A human evaluation on 200 sampled triplets confirms label quality: annotators agree with CASTLE labels at 91-93%. We deploy production pipelines generating synthetic examples daily for embedding-based retrieval and ranking evaluation. Synthetic data remains valuable beyond cold-start: it targets tail queries underrepresented in organic traffic and extends naturally to multi-turn conversational search.

cs.IR↗

arXiv2026

The Intermediate-Mass Black Hole Reverberation Mapping Project: Stable Optical Continuum Lags of an IMBH in the Dwarf Galaxy NGC 4395 Over Years

NGC 4395 is a nearby dwarf spiral galaxy hosting an active galactic nucleus (AGN) powered by an intermediate-mass black hole (IMBH, $M_{\rm BH} \sim 10^{4}$--$10^{5}\,M_\odot$). Recent optical continuum reverberation mapping studies have suggested potential lag variations between different epochs, offering important clues to the physical mechanisms governing variability in the vicinity of the central black hole. We present continuous intranight multi-band photometric monitoring of NGC 4395 based on five nights of observations, including three nights from the Faulkes Telescope North (two of which are archival) and two new nights from Mephisto. This represents the first systematic investigation of optical continuum lag stability in a galaxy hosting a robustly confirmed IMBH. By applying difference-imaging techniques to both the new observations and the reprocessed archival data, we detect statistically significant optical inter-band lags of $\sim 5$--15 minutes, which increase monotonically with increasing wavelength. No obvious $u$-band lag excess is observed, implying a negligible fractional contribution from diffuse continuum (DC) emission to the optical continuum, in agreement with our spectral decomposition results. The inter-band lags remain stable over multi-year baselines. We suggest that this long-term lag stability may be related to the minor DC contribution, a relatively steady disk-corona structure, and the unusually high X-ray-to-optical luminosity ratio characteristic of low-luminosity AGNs, which likely allows X-ray reprocessing to dominate over other potential variability mechanisms. Future facilities like Gemini/SCORPIO, with its simultaneous optical-to-near-infrared coverage, will be ideally suited to play an important role in advancing this field.

astro-ph.GA↗

arXiv2026

From Script to Stage: Automating Experimental Design for Social Simulations with LLMs

Multi-agent simulation based on LLMs has increasingly emerged as a new paradigm for exploring complex social phenomena and validating theoretical hypotheses. However, traditional experimental design in the social sciences relies heavily on interdisciplinary expert knowledge, involving cumbersome procedures and high technical barriers. While LLM-driven agents demonstrate broad prospects for designing experiments, their limitations regarding reliability and scientific rigor continue to significantly hinder their in-depth application in social science research. To address these challenges, this paper proposes FSTS, an automated framework for multi-agent experiment design based on script generation. Drawing on the concept of the "Decision Theater," the framework deconstructs experimental design into three core phases: Script Composition, Script Finalization, and Actor Generation. Tests across multiple scenarios indicate that the agents generated by this framework can enact the script within the "experimental theater", reproducing results consistent with real-world situations. The proposal of FSTS not only effectively lowers the barrier for social science experimental design but also provides scientifically grounded decision support for policy-making.

cs.HC↗

arXiv2026

Fitting the light curves of tidal disruption events with non-parabolic model

Tidal disruption events (TDEs) are powerful probes of supermassive black hole (SMBH) properties and accretion physics. The existing light curve fitting tools assume that the disrupted stars are on parabolic orbits, which may introduce systematic biases in derived parameters. In this work, we extend the model of Zhong (2025) to construct a non-parabolic TDE model that incorporates orbital energy of the disrupted star as a free parameter ($\tilde{\epsilon}_{\rm orb}$) to modify the debris mass distribution and mass fallback rate. We apply this model to 30 TDEs from the ZTF-I survey and compare the results with those from a standard parabolic model. We find that neglecting orbital energy leads to biased black hole mass estimates: for eccentric (hyperbolic) orbits, parabolic models systematically underestimate (overestimate) the black hole mass. Additionally, we measure orbital eccentricities ($e$) and penetration factors ($\beta$) of the disrupted stars in this sample, enabling an investigation of their origins via the $e$-$\beta$ parameter space. Most events (24/30) are consistent with production via two-body relaxation in spherical nuclear star clusters, but six outliers with high $\beta$ and $e<1$ suggest alternative mechanisms. Our results highlight the importance of accounting for orbital energy in TDE modeling to improve the accuracy of SMBH mass measurements and to better understand the dynamical origin of the disrupted stars.

astro-ph.HE↗

arXiv2026

Invariant Causal Routing for Governing Social Norms in Online Market Economies

Social norms are stable behavioral patterns that emerge endogenously within economic systems through repeated interactions among agents. In online market economies, such norms -- like fair exposure, sustained participation, and balanced reinvestment -- are critical for long-term stability. We aim to understand the causal mechanisms driving these emergent norms and to design principled interventions that can steer them toward desired outcomes. This is challenging because norms arise from countless micro-level interactions that aggregate into macro-level regularities, making causal attribution and policy transferability difficult. To address this, we propose \textbf{Invariant Causal Routing (ICR)}, a causal governance framework that identifies policy-norm relations stable across heterogeneous environments. ICR integrates counterfactual reasoning with invariant causal discovery to separate genuine causal effects from spurious correlations and to construct interpretable, auditable policy rules that remain effective under distribution shift. In heterogeneous agent simulations calibrated with real data, ICR yields more stable norms, smaller generalization gaps, and more concise rules than correlation or coverage baselines, demonstrating that causal invariance offers a principled and interpretable foundation for governance.

cs.LG↗

arXiv2026

Accurate Calibration and Robust LiDAR-Inertial Odometry for Spinning Actuated LiDAR Systems

Accurate calibration and robust localization are fundamental for downstream tasks in spinning actuated LiDAR applications. Existing methods, however, require parameterizing extrinsic parameters based on different mounting configurations, limiting their generalizability. Additionally, spinning actuated LiDAR inevitably scans featureless regions, which complicates the balance between scanning coverage and localization robustness. To address these challenges, this letter presents a targetless LiDAR-motor calibration (LM-Calibr) on the basis of the Denavit-Hartenberg convention and an environmental adaptive LiDAR-inertial odometry (EVA-LIO). LM-Calibr supports calibration of LiDAR-motor systems with various mounting configurations. Extensive experiments demonstrate its accuracy and convergence across different scenarios, mounting angles, and initial values. Additionally, EVA-LIO adaptively selects downsample rates and map resolutions according to spatial scale. This adaptivity enables the actuator to operate at maximum speed, thereby enhancing scanning completeness while ensuring robust localization, even when LiDAR briefly scans featureless areas. The source code and hardware design are available on GitHub: \textcolor{blue}{\href{https://github.com/zijiechenrobotics/lm_calibr}{github.com/zijiechenrobotics/lm\_calibr}}. The video is available at \textcolor{blue}{\href{https://youtu.be/cZyyrkmeoSk}{youtu.be/cZyyrkmeoSk}}

cs.RO↗

arXiv2026

A Tale of Two Dust Disks in Our Milky Way

Cosmic dust plays a vital role in stellar and galactic formation and evolution, but its three-dimensional structure in the Milky Way has remained unclear due to insufficient precise reddening and distance measurements. Although early studies typically adopted a single-disk model, we detect two distinct components at Galactocentric distances of 5-14 kpc, enabled by photometric, spectroscopic, and astrometric measurements of over 5 million stars. The thin dust disk's scale height increases radially from 60 to 200 pc, while the thick disk grows from 300 to 800 pc. For the first time, we find the thin and thick dust disk correlates spatially with molecular and atomic hydrogen disk, respectively. The thin, thick, and combined disks have scale lengths of 9.6+1.2-1.1 kpc, 4.2+0.4-0.3 kpc, and 6.6+0.3-0.3 kpc, respectively. The gas-to-dust ratio shows an exponential radial gradient, increasing from around 60 at 5 kpc to around 470 at 14 kpc. These findings provide new insights into dust morphology in the Galaxy and raise fundamental questions that require further investigation.

astro-ph.GA↗

arXiv2025

A Morpho-kinematic Study of Galactic High-ADF PNe Based on the VLT/UVES Deep Spectroscopy

We report detailed analyses of deep, high-resolution spectra of three Galactic planetary nebulae (PNe) with high abundance discrepancy factors (ADFs), Hf2-2, M1-42 and NGC6153, obtained with the Ultraviolet and Visual Echelle Spectrograph (UVES) on the 8.2m Very Large Telescope (VLT). These spectra were carefully reduced, including rigorous absolute flux calibration, yielding detections of ~410-800 emission lines in each PN. Plasma diagnostics and abundance calculations were critically performed using nebular lines. In all three PNe, the electron temperatures derived using the collisionally excited lines (CELs) are higher than those yielded by the HI Balmer and Paschen jumps, while the temperatures yielded by the OII and NII optical recombination lines (ORLs) are very low, <2000 K, indicating that the heavy-element ORLs probe cold nebular regions. The ORL abundances of N, O and Ne are systematically higher than the corresponding CEL values, confirming high ADFs in the three objects. Position-velocity (PV) diagrams were created, and spatio-kinematical studies show that CELs come from the outer nebular regions, while the ORL-emitting regions are close to nebular center. Additionally, the velocity indicated by CEL line-splitting decreases with ionization potential, which was not obvious in ORLs. These spatial and kinematic differences support two distinct components of ionized gas: a cold, metal-rich component and a warmer component with normal metallicity. Heavy elements are strongly enriched in the cold gas, while its H^+ fraction is low but still produces significant HI emission, affecting CEL abundance estimates.

astro-ph.SR↗

arXiv2025

Pressure-robust optimally convergent H(div) finite element method without the commuting diagram property for the steady Oseen equations

This work develops a convergence theory for H(div)-conforming finite element methods applied to the steady Oseen problem, focusing on cases where the exact finite element complex holds while the commuting diagram property may fail. The proposed method incorporates vorticity stabilization to ensure optimal-order convergence of the velocity error, especially for convection-dominated cases. As a crucial component of the analysis, exact de Rham and finite element complexes provide a framework whose utility includes establishing velocity error estimates independent of the discrete inf-sup constant. As a representative example, Stenberg finite elements demonstrate the framework's validity and offer several computational advantages: pressure robustness, fewer degrees of freedom than classical RT or BDM elements due to vertex continuity, and convergence without requiring the commuting diagram property. Moreover, the proposed methodology is applicable to a class of finite element pairs that violate the commuting diagram property, thereby offering new possibilities for efficient discretizations of incompressible fluid problems, particularly in high Reynolds number regimes.

math.NA↗

arXiv2025

SN 2024aecx: A double-peaked rapidly evolving Type IIb supernova at 11 Mpc

We present the results of low-resolution spectroscopic and densely sampled multi-band photometric follow-up of supernova (SN) 2024aecx. The SN was discovered in the spiral galaxy NGC 3521 (distance $\sim$11 Mpc) within a day after the explosion. The early spectra of SN 2024aecx show a weak signature of hydrogen lines, which disappeared in $\sim$30 days after the explosion. Light curves in all bands show a distinct feature of two peaks, and the first peak is likely due to the shock cooling emission. The early phase light curve evolution of SN 2024aecx has similarity with the typical Type IIb events, but the decay rate in different bands (e.g., $\rm Δm_{15}$ = 1.60 $\pm$ 0.05 mag, $g$-band) is significantly faster in the post-peak phase. It attained the secondary maximum in $\sim$19 days ($g$-band) with a peak absolute magnitude of M$_{g}$ = -17.94 $\pm$ 0.10 mag. SN 2024aecx colors trend redder in early epochs ($<$8 days), followed by a duration in which it grows bluer, then later gets redder again $>$20 days after explosion. The analytical model fitting to the light curves reveals an envelope mass and progenitor radii in the range of $\sim$0.03 - 0.24 $M_\odot$ and $\sim$169 - 200 $R_\odot$, respectively. Modeling of the pseudo-bolometric light curve suggests that synthesized $^{56}$Ni in the explosion was $\sim$0.15 M$_{\odot}$ with ejecta mass and kinetic energy of $\sim$0.7 M$_{\odot}$ and $\sim$0.16 $\times$ 10$^{51}$ erg, respectively. The observational properties and modeling indicate that the SN~2024aecx progenitor belongs to the extended progenitor category.

astro-ph.HE↗

arXiv2025

SN 2024gy: Multi-epoch Spectroscopic Features Suggestive of Delayed Detonation in a Type Ia Supernova

We present photometric and spectroscopic observations of SN 2024gy, a Type Ia supernova (SN Ia) exhibiting high-velocity features (HVFs) in its early-time spectra. This SN reaches a peak $B$-band magnitude of $-19.25 \pm 0.29$ mag and subsequently declines by $Δm_{15}(B) \approx 1.12$ mag, consistent with the luminosity-width relation characteristic of normal SNe Ia. Based on the peak thermal luminosity of $(1.2 \pm 0.3) \times 10^{43}$ erg s$^{-1}$, we estimate that $0.57 \pm 0.14~\rm M_{\odot}$ of $^{56}$Ni was synthesized during the explosion. Our dense early spectral monitoring revealed significant velocity disparities within the ejecta. Notably, absorption features from the Ca II near-infrared triplet were observed at velocities exceeding 25,000 km s$^{-1}$, while the Si II $λ$6355 line velocity at the same epoch was significantly lower at $\sim$ 16,000 km s$^{-1}$. This velocity disparity likely reflects distinct ionization states of intermediate-mass elements in the outermost layers. The prominent Ca II HVFs may originate from ionization suppression within the highest-velocity ejecta, potentially indicative of minimal hydrogen mixing in a delayed-detonation explosion scenario. Additionally, the Ni/Fe ratio derived from the nebular spectrum of SN 2024gy provides further support for this model.

astro-ph.HE↗

arXiv2025

On Generalization and Distributional Update for Mimicking Observations with Adequate Exploration

Learning from observations (LfO) replicates expert behavior without needing access to the expert's actions, making it more practical than learning from demonstrations (LfD) in many real-world scenarios. However, directly applying the on-policy training scheme in LfO worsens the sample inefficiency problem, while employing the traditional off-policy training scheme in LfO magnifies the instability issue. This paper seeks to develop an efficient and stable solution for the LfO problem. Specifically, we begin by exploring the generalization capabilities of both the reward function and policy in LfO, which provides a theoretical foundation for computation. Building on this, we modify the policy optimization method in generative adversarial imitation from observation (GAIfO) with distributional soft actor-critic (DSAC), and propose the Mimicking Observations through Distributional Update Learning with adequate Exploration (MODULE) algorithm to solve the LfO problem. MODULE incorporates the advantages of (1) high sample efficiency and training robustness enhancement in soft actor-critic (SAC), and (2) training stability in distributional reinforcement learning (RL). Extensive experiments in MuJoCo environments showcase the superior performance of MODULE over current LfO methods.

stat.ML↗

arXiv2025

ROFI: A Deep Learning-Based Ophthalmic Sign-Preserving and Reversible Patient Face Anonymizer

Patient face images provide a convenient mean for evaluating eye diseases, while also raising privacy concerns. Here, we introduce ROFI, a deep learning-based privacy protection framework for ophthalmology. Using weakly supervised learning and neural identity translation, ROFI anonymizes facial features while retaining disease features (over 98\% accuracy, $κ> 0.90$). It achieves 100\% diagnostic sensitivity and high agreement ($κ> 0.90$) across eleven eye diseases in three cohorts, anonymizing over 95\% of images. ROFI works with AI systems, maintaining original diagnoses ($κ> 0.80$), and supports secure image reversal (over 98\% similarity), enabling audits and long-term care. These results show ROFI's effectiveness of protecting patient privacy in the digital medicine era.

cs.CV↗