arXiv subjects

Jiaying Xu

Publications and source records attributed to Jiaying Xu.

14 recordsLinked to original sources

arXiv2026

Non-Resonant Impulsively Stimulated Raman Scattering by a Terahertz Field: a Case Study of 1T-TaS2

Time-domain ultrafast and nonlinear terahertz spectroscopy techniques are recently applied to many condensed matter systems for investigating their collective excitations. In centrosymmetric systems, these collective modes are typically Raman-active and therefore do not couple directly to the terahertz electric field. The mechanism by which light-matter interaction realizes in these studies has not been explicitly discussed in detail. In this work, we perform terahertz pump - optical probe and terahertz third harmonic generation investigations on 1T-TaS2, a material exhibiting a rich charge-density-wave (CDW) phase diagram including the commensurate, nearly-commensurate and incommensurate CDW phases. The transition between these distinct states leaves a clear signature on the dynamical Raman response. We investigate how the Raman-active phonons couple to a broadband monocycle terahertz field as well as a narrowband multicycle terahertz field. Our results indicate that a modified impulsively stimulated Raman scattering mechanism involving two-photon absorption, also known as non-resonant Raman scattering, underlies the coherent excitation and observation of the lattice modes. These results are relevant for future spectroscopy investigation and coherent control of collective modes using low-energy terahertz field as well as cavity electrodynamical dressing of solids.

cond-mat.str-el↗

arXiv2026

Spectro-Polarimetric Properties of CHIME FRB Sources

Fast radio bursts (FRBs) are enigmatic millisecond-duration radio transients whose polarization properties offer crucial insights into their origins and environments. In particular, low-frequency depolarization---quantified by the parameter $\sigma_{\mathrm{RM}}$---probes the complex magneto-ionic medium surrounding the progenitor, and has been observed across a population of repeating FRBs. We present a systematic spectro-polarimetric analysis of repeating and non-repeating FRBs using observations from the Canadian Hydrogen Intensity Mapping Experiment (CHIME). For 28 repeating FRBs, we measure $\sigma_{\mathrm{RM}}$, expanding the known sample from 14 to 36 sources (an increase by a factor of 2.6). The kernel density estimate (KDE) of the repeating population peaks at $1.3\ \mathrm{rad\,m^{-2}}$, with approximately 70\% of the sources showing $\sigma_{\mathrm{RM}} \gtrsim 1\ \mathrm{rad\,m^{-2}}$, implying that most reside in complex magneto-ionic environments. For 70 non-repeating FRBs, we investigate four spectro-polarimetric models; no source exhibits significant depolarization with $\sigma_{\mathrm{RM}} \gtrsim 5\ \mathrm{rad\,m^{-2}}$. Roughly half of the non-repeaters are consistent with a constant linear polarization fraction across frequency. We caution, however, that these results may be affected by the limited frequency coverage of CHIME. Future ultra-wideband polarimetry, spanning widely separated frequencies, will overcome current observational biases, enable precise $\sigma_{\mathrm{RM}}$ measurements, and substantially deepen our understanding of FRB environments.

astro-ph.HE↗

arXiv2026

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In such an attack, a malicious actor uses Augmented Reality (AR) glasses to capture a target visual and vocal data. A Large Language Model (LLM) then analyzes this data to identify the individual and generate a detailed social profile. Subsequently, LLM-powered agents employ social engineering strategies, providing real-time conversation suggestions, to gain the target trust and ultimately execute phishing or other malicious acts. Despite its potential, the practical application of AR-LLM-SE faces two major bottlenecks, (1) Cold-start personalization, Current Retrieval-Augmented Generation (RAG) methods introduce critical delays in the earliest turns, slowing initial profile formation and disrupting real-time interaction, (2) Static Attack Strategies, Existing approaches rely on fixed-stage, handcrafted social engineering tactics that lack foundation in established psychological theory. To address these limitations, we propose PhySE, a novel framework with two core innovations, (1) VLM-Based SocialContext Training, To eliminate profiling delays, we efficiently pre-train a Visual Language Model (VLM) with social-context data, enabling rapid, on-the-fly profile generation, (2) Adaptive Psychological Agent, We introduce a psychological LLM that dynamically deploys distinct classes of psychological strategies based on target response, moving beyond static, handcrafted scripts. We evaluated PhySE through an IRB-approved user study with 60 participants, collecting a novel dataset of 360 annotated conversations across diverse social scenarios.

cs.AI↗

arXiv2026

The Real and Pseudo Dispersion Measures of FRB~20220912A

Fast radio bursts (FRBs) are millisecond-duration radio transients. As they propagate through the interstellar medium, they interact with free electrons, resulting in dispersion. The corresponding dispersion measure (DM) is referred to as the real DM (DM$_{\rm real}$). In practice, however, the dispersion measure derived from modeling (DM$_{\rm model}$) is often contaminated by intrinsic burst morphology, giving rise to a pseudo DM component (DM$_{\rm pseudo} = {\rm DM}_{\rm model} - {\rm DM}_{\rm real}$). In this work, we focus on the highly active repeating FRB~20220912A and utilize its microshots -- extremely short-duration (typically tens of microseconds), broadband emissions -- to investigate its DM$_{\rm real}$ and DM$_{\rm pseudo}$. We adopt two assumptions: first, that FRB~20220912A resides in a non-magneto-ionic environment and that its DM$_{\rm real}$ variation is smaller than $10^{-2}$\,pc\,cm$^{-3}$ over a few years; and second, that microshots have a negligible intrinsic morphological time delay. By identifying two new microshots and combining them with previously reported ones, we find that all four microshots exhibit remarkably consistent DM values over a one-month timescale, with an average of $219.380 \pm 0.004\,\mathrm{pc\,cm^{-3}}$. We define this value as the DM$_{\rm real}$ of FRB~20220912A. We further show that bright, narrow bursts with a width of less than 2\,ms also yield DM estimates consistent with the microshot-based DM$_{\rm real}$. A survey of five repeating FRBs reveals that DM$_{\rm pseudo}$ is a common phenomenon, with variations typically spanning a range of approximately $10\,\mathrm{pc\,cm^{-3}}$ at 1.2\,GHz. These findings highlight the importance of accounting for morphological contributions in DM interpretation and demonstrate that microshots and narrow bursts are powerful tools for probing DM$_{\rm real}$.

astro-ph.HE↗

arXiv2025

Revealing the Temporally Stable Bimodal Energy Distribution of FRB 20121102A with a Tripled Burst Set from AI Detections

Active repeating Fast Radio Bursts (FRBs), with their large number of bursts, burst energy distribution, and their potential energy evolution, offer critical insights into the FRBs emission mechanisms. Traditional pipelines search for bursts through conducting dedispersion trials and looking for signals above certain fluence thresholds, both of which could result in missing weak and narrow-band bursts. In order to improve the completeness of the burst set, we develop an End-to-end DedispersE-agnostic Nonparametric AI model (EDEN), which directly detect bursts from dynamic spectrum and is the first detection pipeline that operates without attempting dedispersion. We apply EDEN to archival FAST L-band observations during the extreme active phase of the repeating source FRB 20121102A, resulting in the largest burst set for any FRB to date, which contains 5,927 individual bursts, tripling the original burst set. The much enhanced completeness enables a refined analysis of the temporal behavior of energy distribution, revealing that the bimodal energy distribution remains stable over time. It is rather an intrinsic feature of the emission mechanisms than a consequence of co-evolving with burst rate.

astro-ph.HE↗

arXiv2025

Accelerating FRB Search: Dataset and Methods

Fast Radio Burst (FRB) is an extremely energetic cosmic phenomenon of short duration. Discovered only recently and with its origin still unknown, FRBs have already started to play a significant role in studying the distribution and evolution of matter in the universe. FRBs can only be observed through radio telescopes, which produce petabytes of data, rendering the search for FRB a challenging task. Traditional techniques are computationally expensive, time-consuming, and generally biased against weak signals. Various machine learning algorithms have been developed and employed, all of which require substantial datasets. We here introduce the FAST dataset for Fast Radio bursts EXploration (FAST-FREX), built upon the observations obtained by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Our dataset comprises 600 positive samples of observed FRB signals from three sources and 1000 negative samples of noise and Radio Frequency Interference (RFI). Furthermore, we provide a machine learning algorithm, Radio Single-Pulse Detection Algorithm Based on Visual Morphological Features (RaSPDAM), with significant improvements in efficiency and accuracy for FRB search. We also employed the benchmark comparison between conventional single-pulse search softwares, namely PRESTO and Heimdall, and RaSPDAM. RaSPDAMv2 achieves an average precision of 97% and an average recall of 83%, with notable enhancements in computational performance. Future machine learning algorithms can use this as a reference point to measure their performance and help the potential improvements. By enabling more accurate and efficient detection of transient radio events, our work facilitates the FRB and pulsars search pipeline, enhances the potential for discovering new astrophysical phenomena.

astro-ph.IM↗

arXiv2025

Refined Constraints on the Hubble Constant from Localized FRBs with Assessment of Systematic Effects

The dispersion measure-redshift relation of fast radio bursts (FRBs) provides a valuable cosmological probe for constraining the Hubble constant, offering an independent measurement that could help resolve the ongoing Hubble tension. In this paper, we begin with a sample of 117 localized FRBs and use 95 of them to constrain $H_0$ to $71.28^{+1.90}_{-2.08}$ km s$^{-1}$ Mpc$^{-1}$ within the standard Lambda Cold Dark Matter ($Λ$CDM) model. The resulting statistical uncertainty is below 2.8\%, improving previous FRB-based measurements and highlighting the promise of larger future samples. Beyond statistical improvements, we note that different parameter choices have been adopted in previous studies and some results show discrepancies in $H_0$. To address this issue, we perform a systematic assessment of modeling uncertainties that can affect the inferred value of $H_0$, including Galactic electron density models, the contribution of the Galactic halo, outliers such as FRB~20190520B located in extreme environments, and the other parameter selections. We also discuss possible approaches to mitigate these sources of uncertainty, emphasizing both the challenges and prospects of using FRBs as reliable cosmological tools.

astro-ph.CO↗

arXiv2025

Multi-year Polarimetric Monitoring of Four CHIME-Discovered Repeating Fast Radio Bursts with FAST

In this study, we report multi-year polarization measurements of four repeating FRBs initially discovered by CHIME: FRBs~20190117A, 20190208A, 20190303A, and 20190417A. We observed the four repeating FRBs with FAST, detecting a total of 66 bursts. Two bursts from FRB~20190417A exhibit a circular polarization signal-to-noise ratio greater than 7, with the highest circular polarization fraction recorded at 35.7%. While the bursts from FRBs 20190208A and 20190303A are highly linearly polarized, those from FRBs~20190117A and 20190417A show depolarization due to multi-path propagation, with σ_{\mathrm{RM}} = 2.78 \pm 0.05 rad m$^{-2}$ and 5.19 \pm 0.09 rad m$^{-2}$, respectively. The linear polarization distributions among five repeating FRB--FRBs~20190208A, 20190303A, 20201124A, 20220912A, and 20240114A--are nearly identical but show distinct differences from those of non-repeating FRBs. FRBs~20190117A, 20190303A, and 20190417A exhibit substantial rotation measure (RM) variations between bursts, joining other repeating FRBs in this behavior. Combining these findings with published results, 64% of repeating FRBs show RM variations greater than 50 rad m$^{-2}$, and 21\% exhibit RM reversals. A significant proportion of repeating FRBs reside in a dynamic magneto-ionic environment. The structure function of RM variations shows a power-law index of $γ\sim (0-0.8)$, corresponding to a shallow power spectrum $α= -(γ+ 2) \sim -(2.0-2.8)$ of turbulence, if the RM variations are attributed to turbulence. This suggests that the variations are dominated by small-scale RM density fluctuations. We perform K-S tests comparing the RMs of repeating and non-repeating FRBs, which reveal a marginal dichotomy in the distribution of their RMs.We caution that the observed dichotomy may be due to the small sample size and selection biases.

astro-ph.HE↗

arXiv2025

Topological Braiding of Bloch Eigenmodes Protected by Non-Abelian Quaternion Invariants

Braiding has attracted significant attention in physics because of its important role in describing the fundamental exchange of particles. Infusing the braiding with topological protection will make it robust against imperfections and perturbations, but such topological braiding is believed to be possible only in interacting quantum systems, e.g., topological superconductors. Here, we propose and demonstrate a new strategy of topological braiding that emerges from non-Abelian topological insulators, a class of recently discovered multi-band topological phase. We unveil a mathematical connection between braiding and non-Abelian quaternion invariants, by which Bloch eigenmodes under parallel transport produce braid sequences protected by the non-Abelian band topology. The braiding is also associated with geometric phases quantized over half the Brillouin zone. This new type of non-Abelian topological braiding is experimentally realized in acoustic systems with periodic synthetic dimensions. The results show that the principle discovered here is a new strategy towards topological braiding and can be extended for other types of classical waves and non-interacting quantum systems.

quant-ph↗

arXiv2025

Polarization Characteristics of the Hyperactive FRB 20240114A

Fast radio bursts (FRBs) are transient radio bursts of extragalactic origin characterized by millisecond durations and high luminosities. We report on observations of FRB 20240114A conducted with the Robert C. Byrd Green Bank Telescope (GBT) at frequencies ranging from 720 to 920 MHz. A total of 437 bursts were detected, with a single observation recording 365 bursts over 1.38 hours, corresponding to a burst rate of 264 bursts per hour. The average rotation measures (RMs) were $347.0 \pm 1.0$ rad m$^{-2}$ on February 23, 2024, and $353.7 \pm 0.6$ rad m$^{-2}$ on March 1, 2024. Of the 301 bursts with detected RMs, 81% have a linear polarization fraction greater than 90%, and 14% exhibit circular polarization with a signal-to-noise ratio $> 5$. Our sample also displayed polarization angle swings. We compared the linear polarization fraction of FRB~20240114A with those of the repeating sources FRB~20201124A and FRB~20220912A. Our analysis reveals that all three exhibit similar distributions in both linear and circular polarization fractions. These results indicate that the three sources share the same radiation mechanism. We analyze the fluence and waiting-time distributions of FRB~20240114A, revealing a right-skewed fluence distribution and a bimodal waiting-time structure, suggesting intrinsic emission timescales and potential multiple burst populations. Additionally, We present a novel method to determine the frequency range of bursts based on their spectral characteristics. This algorithm is independent of spectral models and remains unaffected by the removal of interference-affected channels in the data, ensuring robust performance.

astro-ph.HE↗

arXiv2025

To Share or Not to Share: Investigating Weight Sharing in Variational Graph Autoencoders

This paper investigates the understudied practice of weight sharing (WS) in variational graph autoencoders (VGAE). WS presents both benefits and drawbacks for VGAE model design and node embedding learning, leaving its overall relevance unclear and the question of whether it should be adopted unresolved. We rigorously analyze its implications and, through extensive experiments on a wide range of graphs and VGAE variants, demonstrate that the benefits of WS consistently outweigh its drawbacks. Based on our findings, we recommend WS as an effective approach to optimize, regularize, and simplify VGAE models without significant performance loss.

cs.LG↗

arXiv2024

An extremely active repeating fast radio burst source in a likely non-magneto-ionic environment

Fast radio bursts (FRBs) are bright radio bursts originating at cosmological distances. Only three repeating FRBs FRB 20121102A, FRB 20190520B and FRB 20201124A among $\sim$ 60 known repeating FRBs have circular polarization. We observed the FRB 20220912A with the Robert C. Byrd Green Bank Telescope (GBT) at L-band on 24 October 2022 and detected 128 bursts in 1.4 hours, corresponding to a burst rate of about 90 hr$^{-1}$, which is the highest yet for FRBs observed by the GBT. The average rotation measure (RM) was $-$0.4$\pm$0.3$\,$rad$\,$m$^{-2}$ with negligible intraday RM change, indicating a likely non-magneto-ionic environment. 61% bursts have linear polarization fraction greater than 90%. Approximately 56% of the bright bursts have circular polarization. A downward drift in frequency and polarization angle swings were found in our sample. The characterization of FRB 20220912A indicates that the circular polarization is unlikely to be caused by the magneto-ionic environment for at least some of the repeating FRB population.

astro-ph.HE↗

arXiv2023

Blinkverse: A Database of Fast Radio Bursts

The volume of research on fast radio bursts (FRBs) observation have been seeing a dramatic growth. To facilitate the systematic analysis of the FRB population, we established a database platform, Blinkverse (https://blinkverse.alkaidos.cn), as a central inventory of FRBs from various observatories and with published properties, particularly dynamic spectra from FAST, CHIME, GBT, Arecibo, etc. Blinkverse thus not only forms a superset of FRBCAT, TNS, and CHIME/FRB, but also provides convenient access to thousands of FRB dynamic spectra from FAST, some of which were not available before. Blinkverse is regularly maintained and will be updated by external users in the future. Data entries of FRBs can be retrieved through parameter searches through FRB location, fluence, etc., and their logical combinations. Interactive visualization was built into the platform. We analyzed the energy distribution, period analysis, and classification of FRBs based on data downloaded from Blinkverse. The energy distributions of repeaters and non-repeaters are found to be distinct from one another.

astro-ph.HE↗

arXiv2021

BlockGC: A Joint Learning Framework for Account Identity Inference on Blockchain with Graph Contrast

Blockchain technology has the characteristics of decentralization, traceability and tamper proof, which creates a reliable decentralized transaction mode, further accelerating the development of the blockchain platforms. However, with the popularization of various financial applications, security problems caused by blockchain digital assets, such as money laundering, illegal fundraising and phishing fraud, are constantly on the rise. Therefore, financial security has become an important issue in the blockchain ecosystem, and identifying the types of accounts in blockchain (e.g. miners, phishing accounts, Ponzi contracts, etc.) is of great significance in risk assessment and market supervision. In this paper, we construct an account interaction graph using raw blockchain data in a graph perspective, and proposes a joint learning framework for account identity inference on blockchain with graph contrast. We first capture transaction feature and correlation feature from interaction graph, and then perform sampling and data augmentation to generate multiple views for account subgraphs, finally jointly train the subgraph contrast and account classification task. Extensive experiments on Ethereum datasets show that our method achieves significant advantages in account identity inference task in terms of classification performance, scalability and generalization.

cs.CR↗