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Yujun Yao

Publications and source records attributed to Yujun Yao.

4 recordsLinked to original sources

Radio and X-ray flux rebrightening six years after outburst in a partially-obscured extreme changing-look AGN

SDSS J1548+2208 is a unique partially-obscured nuclear transient that exhibits multiwavelength outbursts in mid-infrared, X-ray and radio. We present the results from multiwavelength photometric and spectroscopic follow-up observations with a time span of ~2500 days since its discovery. We find that the mid-infrared and X-ray emission (with a hard X-ray spectrum) are still in a high flux level relative to the pre-flare state, suggesting a sudden increased, and possibly long-sustained accreting activity from central black hole. This is supported by the slowly-evolving high-ionization coronal lines. The mid-infrared color turns blue slowly in the rising phase, which is distinct from stellar tidal disruption events (TDEs). All these properties point to the origin of outbursts from an extreme changing-look AGN and the scenario with a normal TDE seems disfavored. The radio spectral energy distribution (SED) in ~0.65-15 GHz is unusual, displaying a double-peak feature with distinct variability characteristics. In addition, we find evidence for the late-time radio rebrightening more than six years since the initial outburst, as well as a possibly new X-ray flare, though the significance for the latter is not high. The peculiar radio flux and SED evolution could be explained by a nascent outflow expanding into and shocking circumnuclear diffuse medium filled by denser clouds. In this case, SDSS J1548+2208 represents a rare changing-look AGN which can launch radio outflows. Continued multiwavelength observations are required to map the dust and gas distribution on pc-scales, providing new insights into the environmental properties that could regulate AGN changing-look phenomenon.

astro-ph.HE

Rate of Repeating Tidal Disruption Events with 5--19 years interval

Statistics on tidal disruption events (TDEs) may be contaminated by repeating TDEs (rTDEs), which have been extensively discovered recently. However, the origin of rTDEs remains unclear. In addition, no statistical research on rTDEs with time intervals $>5$ years has been made yet. In this work, we searched for rTDEs with time intervals of 5--19 years using CRTS data in a sample of 16 ZTF BTS TDEs at $z<0.05$. We found 2 rTDE candidates, AT 2019azh and AT 2024pvu, with time intervals of 13.2 and 17.1 years, respectively. The peak luminosities of CRTS flares are close to those of ZTF flares. For the CRTS flare of AT 2024pvu, using GALEX UV observations near the peak, we measured a blackbody temperature of $\sim19500$ K, consistent with TDEs and higher than SNe. Moreover, we estimated the expected number of SNe in the sample to be $\lesssim0.08$, and hence the probability that both CRTS flares are SNe is only 0.3\%. Therefore, the possibility that both CRTS flares are SNe can be ruled out, and it is likely that both are TDEs. Using the two rTDEs, we inferred that the TDE rate is 2--3 orders of magnitude higher than the average over 5--19 years prior to TDE detection. Considering another two rTDEs with intervals of $\sim$2 years in the sample and possible rTDEs missed by CRTS, rTDEs with intervals of $<20$ years may account for 25\%--60\% of the TDE sample. We prefer to explain rTDEs as repeating partial TDEs. If so, the high fraction of rTDEs suggests that the observed optical TDE rate has been overestimated. However, the possibility of independent TDEs cannot be ruled out and requires future observational tests.

astro-ph.HE

EpiPlanAgent: Agentic Automated Epidemic Response Planning

Epidemic response planning is essential yet traditionally reliant on labor-intensive manual methods. This study aimed to design and evaluate EpiPlanAgent, an agent-based system using large language models (LLMs) to automate the generation and validation of digital emergency response plans. The multi-agent framework integrated task decomposition, knowledge grounding, and simulation modules. Public health professionals tested the system using real-world outbreak scenarios in a controlled evaluation. Results demonstrated that EpiPlanAgent significantly improved the completeness and guideline alignment of plans while drastically reducing development time compared to manual workflows. Expert evaluation confirmed high consistency between AI-generated and human-authored content. User feedback indicated strong perceived utility. In conclusion, EpiPlanAgent provides an effective, scalable solution for intelligent epidemic response planning, demonstrating the potential of agentic AI to transform public health preparedness.

cs.AI

Distinguishing Tidal Disruption Events and Changing-look Active Galactic Nuclei via Variation of Mid-infrared Color

At present, there is a lack of effective probes to distinguish between mid-infrared (MIR) outbursts induced by tidal disruption events (TDEs) and changing-look active galactic nuclei (CLAGNs) based on only MIR data. Here, we propose that the time variation of MIR color (K-corrected W1-W2 after subtracting the quiescent fluxes) is a promising probe. With an optically selected sample containing TDEs, ambiguous nuclear transients (ANTs), and CLAGNs, we studied the MIR color variation of their MIR counterparts using NEOWISE-R data. We found that the MIR color of TDEs and ANTs turns red faster than CLAGNs during the rising phase, and TDEs have a redder color than ANTs at the earliest phase. The former may be caused by the difference between the ultraviolet light curves of TDEs/ANTs and CLAGNs, or be related to no or relatively weak underlying AGN in TDEs/ANTs, while the latter may be related to the difference in the dust geometry. Based on color variation rate, we selected high-probability TDE, ANT, and CLAGN candidates from MIR outbursts in samples of Jiang et al. (2021) and Masterson et al. (2024). We found that both samples are mixtures of TDEs/ANTs and CLAGNs. For MIR outbursts whose hosts are not Seyfert galaxies, we estimated that $\sim50\%-80\%$ are TDEs and inferred a rate of infrared TDEs of $1.5-2.8\times10^{-5}$ galaxy$^{-1}$ yr$^{-1}$, comparable with that of optical TDEs. The rest are CLAGNs, suggesting the presence of weak AGNs that cannot be identified using common diagnoses. We predicted that with our method, a large amount of dust-obscured TDEs could be selected from future infrared surveys with higher data quality and cadence.

astro-ph.HE