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Chan Wang

Publications and source records attributed to Chan Wang.

15 recordsLinked to original sources
arXiv2026

Spatial mixed models for assessing environmental exposure effects on the microbiome

The influence of environmental exposures, such as air pollution, on human health has become increasingly recognized. A growing body of evidence suggests that the microbiome may mediate these effects, explaining the relationship between the environment and host biology. However, the impact of environmental exposures on the microbiome is not yet fully understood, and statistical modeling in this context is challenged by complex dependency structures. In particular, microbiome data exhibit spatial dependencies across sampling regions as well as ecological correlations among microbial taxa, which, if ignored, can substantially reduce detection power, leading to missed true signals. We introduce a novel spatial mixed modeling framework for microbiome data that accounts for both region-level spatial dependency and taxon-level ecological dependency using conditional autoregressive priors. Through simulations, we demonstrate that this framework outperforms existing methods that ignore such dependencies, by achieving high detection power in feature selection while maintaining low false positive rates and reduced mean squared error in estimation. Applied to two real studies-data from Food and Microbiome Longitudinal Investigation study and lung microbiome dataset-with fine particulate matter (PM_2.5) exposures, our model identified genera, which are known to be involved in pollution-related health outcomes, as well as novel taxa that may mediate host responses to air pollution. This novel approach offers a powerful and flexible tool for uncovering biologically meaningful associations in complex environmental data.

stat.ME↗
arXiv2025

Multi-Agent Conditional Diffusion Model with Mean Field Communication as Wireless Resource Allocation Planner

In wireless communication systems, efficient and adaptive resource allocation plays a crucial role in enhancing overall Quality of Service (QoS). Compared to the conventional Model-Free Reinforcement Learning (MFRL) scheme, Model-Based RL (MBRL) first learns a generative world model for subsequent planning. The reuse of historical experience in MBRL promises more stable training behavior, yet its deployment in large-scale wireless networks remains challenging due to high-dimensional stochastic dynamics, strong inter-agent cooperation, and communication constraints. To overcome these challenges, we propose the Multi-Agent Conditional Diffusion Model Planner (MA-CDMP) for decentralized communication resource management. Built upon the Distributed Training with Decentralized Execution (DTDE) paradigm, MA-CDMP models each communication node as an autonomous agent and employs Diffusion Models (DMs) to capture and predict environment dynamics. Meanwhile, an inverse dynamics model guides action generation, thereby enhancing sample efficiency and policy scalability. Moreover, to approximate large-scale agent interactions, a Mean-Field (MF) mechanism is introduced as an assistance to the classifier in DMs. This design mitigates inter-agent non-stationarity and enhances cooperation with minimal communication overhead in distributed settings. We further theoretically establish an upper bound on the distributional approximation error introduced by the MF-based diffusion generation, guaranteeing convergence stability and reliable modeling of multi-agent stochastic dynamics. Extensive experiments demonstrate that MA-CDMP consistently outperforms existing MARL baselines in terms of average reward and QoS metrics, showcasing its scalability and practicality for real-world wireless network optimization.

cs.AI↗
arXiv2025

Conditional Diffusion Model with OOD Mitigation as High-Dimensional Offline Resource Allocation Planner in Clustered Ad Hoc Networks

Due to network delays and scalability limitations, clustered ad hoc networks widely adopt Reinforcement Learning (RL) for on-demand resource allocation. Albeit its demonstrated agility, traditional Model-Free RL (MFRL) solutions struggle to tackle the huge action space, which generally explodes exponentially along with the number of resource allocation units, enduring low sampling efficiency and high interaction cost. In contrast to MFRL, Model-Based RL (MBRL) offers an alternative solution to boost sample efficiency and stabilize the training by explicitly leveraging a learned environment model. However, establishing an accurate dynamic model for complex and noisy environments necessitates a careful balance between model accuracy and computational complexity $\&$ stability. To address these issues, we propose a Conditional Diffusion Model Planner (CDMP) for high-dimensional offline resource allocation in clustered ad hoc networks. By leveraging the astonishing generative capability of Diffusion Models (DMs), our approach enables the accurate modeling of high-quality environmental dynamics while leveraging an inverse dynamics model to plan a superior policy. Beyond simply adopting DMs in offline RL, we further incorporate the CDMP algorithm with a theoretically guaranteed, uncertainty-aware penalty metric, which theoretically and empirically manifests itself in mitigating the Out-of-Distribution (OOD)-induced distribution shift issue underlying scarce training data. Extensive experiments also show that our model outperforms MFRL in average reward and Quality of Service (QoS) while demonstrating comparable performance to other MBRL algorithms.

cs.NI↗
arXiv2023

Self-Critical Alternate Learning based Semantic Broadcast Communication

Semantic communication (SemCom) has been deemed as a promising communication paradigm to break through the bottleneck of traditional communications. Nonetheless, most of the existing works focus more on point-to-point communication scenarios and its extension to multi-user scenarios is not that straightforward due to its cost-inefficiencies to directly scale the JSCC framework to the multi-user communication system. Meanwhile, previous methods optimize the system by differentiable bit-level supervision, easily leading to a "semantic gap". Therefore, we delve into multi-user broadcast communication (BC) based on the universal transformer (UT) and propose a reinforcement learning (RL) based self-critical alternate learning (SCAL) algorithm, named SemanticBC-SCAL, to capably adapt to the different BC channels from one transmitter (TX) to multiple receivers (RXs) for sentence generation task. In particular, to enable stable optimization via a nondifferentiable semantic metric, we regard sentence similarity as a reward and formulate this learning process as an RL problem. Considering the huge decision space, we adopt a lightweight but efficient self-critical supervision to guide the learning process. Meanwhile, an alternate learning mechanism is developed to provide cost-effective learning, in which the encoder and decoders are updated asynchronously with different iterations. Notably, the incorporation of RL makes SemanticBC-SCAL compliant with any user-defined semantic similarity metric and simultaneously addresses the channel non-differentiability issue by alternate learning. Besides, the convergence of SemanticBC-SCAL is also theoretically established. Extensive simulation results have been conducted to verify the effectiveness and superiorness of our approach, especially in low SNRs.

eess.SP↗
arXiv2023

Revisiting Emission-Line Measurement Methods for Narrow-Line Active Galactic Nuclei

Measuring broad emission-line widths in active galactic nuclei (AGN) is not straightforward owing to the complex nature of flux variability in these systems. Line-width measurements become especially challenging when signal-to-noise is low, profiles are narrower, or spectral resolution is low. We conducted an extensive correlation analysis between emission-line measurements from the optical spectra of Markarian 142 (Mrk 142; a narrow-line Seyfert galaxy) taken with the Gemini North Telescope (Gemini) at a spectral resolution of 185.6+\-10.2 km/s and the Lijiang Telescope (LJT) at 695.2+\-3.9 km/s to investigate the disparities in the measured broad-line widths from both telescope data. Mrk~142 posed a challenge due to its narrow broad-line profiles, which were severely affected by instrumental broadening in the lower-resolution LJT spectra. We discovered that allowing the narrow-line flux of permitted lines having broad and narrow components to vary during spectral fitting caused a leak in the narrow-line flux to the broad component, resulting in broader broad-line widths in the LJT spectra. Fixing the narrow-line flux ratios constrained the flux leak and yielded the Hydrogen-beta broad-line widths from LJT spectra $\sim$54\% closer to the Gemini Hydrogen-beta widths than with flexible narrow-line ratios. The availability of spectra at different resolutions presented this unique opportunity to inspect how spectral resolution affected emission-line profiles in our data and adopt a unique method to accurately measure broad-line widths. Reconsidering line-measurement methods while studying diverse AGN populations is critical for the success of future reverberation-mapping studies. Based on the technique used in this work, we offer recommendations for measuring line widths in narrow-line AGN.

astro-ph.GA↗
arXiv2023

Dipole-matter interactions governed by the asymmetry of Maxwell equations

Directionally molding the near-field and far-field radiation lies at the heart of nanophotonics and is crucial for applications such as on-chip information processing and chiral quantum networks. The most fundamental model for radiating structures is a dipolar source located inside a homogeneous matter. However, the influence of matter on the directionality of dipolar radiation is oftentimes overlooked, especially for the near-field radiation. We show that the dipole-matter interaction is intrinsically asymmetric and does not fulfill the duality principle, originating from the inherent asymmetry of Maxwell equations, i.e., electric charge and current are ubiquitous but their magnetic counterparts are non-existent to elusive. Moreover, we find that the asymmetric dipole-matter interaction could offer an enticing route to reshape the directionality of not only the near-field radiation but also the far-field radiation. As an example, both the near-field and far-field radiation directionality of Huygens dipole (located close to a dielectric-metal interface) would be reversed, if the dipolar position is changed from the dielectric region to the metal region.

physics.optics↗
arXiv2022

Low-velocity-favored transition radiation

When a charged particle penetrates through an optical interface, photon emissions emerge - a phenomenon known as transition radiation. Being paramount to fundamental physics, transition radiation has enabled many applications from high-energy particle identification to novel light sources. A rule of thumb in transition radiation is that the radiation intensity generally decreases with the particle velocity v; as a result, low-energy particles are not favored in practice. Here we find that there exist situations where transition radiation from particles with extremely low velocities (e.g. v/c<0.001) exhibits comparable intensity as that from high-energy particles (e.g. v/c=0.999), where c is light speed in free space. The comparable radiation intensity implies an extremely high photon extraction efficiency from low-energy particles, up to eight orders of magnitude larger than that from high-energy particles. This exotic phenomenon of low-velocity-favored transition radiation originates from the excitation of Ferrell-Berreman modes in epsilon-near-zero materials. Our findings may provide a promising route towards the design of integrated light sources based on low-energy electrons and specialized detectors for beyond-standard-model particles.

physics.optics↗
arXiv2022

A perspective on meta-boundaries

The judicious design of electromagnetic boundary provides a crucial route to control light-matter interactions, and it is thus fundamental to basic science and practical applications. General design approaches rely on the manipulation of bulk properties of superstrate or substrate and on the modification of boundary geometries. Due to the recent advent of metasurfaces and low-dimensional materials, the boundary can be flexibly featured with a surface conductivity, which can be rather complex but provide an extra degree of freedom to regulate the propagation of light. In this perspective, we denote the boundary with a non-zero surface conductivity as the meta-boundary. The meta-boundaries are categorized into four types, namely isotropic, anisotropic, biisotropic and bianisotropic meta-boundaries, according to the electromagnetic boundary conditions. Accordingly, the latest development for these four kinds of meta-boundaries are reviewed. Finally, an outlook on the research tendency of meta-boundaries is provided, particularly on the manipulation of light-matter interactions by simultaneously exploiting meta-boundaries and metamaterials.

physics.optics↗
arXiv2022

AoI-based Temporal Attention Graph Neural Network for Popularity Prediction and Content Caching

Along with the fast development of network technology and the rapid growth of network equipment, the data throughput is sharply increasing. To handle the problem of backhaul bottleneck in cellular network and satisfy people's requirements about latency, the network architecture like information-centric network (ICN) intends to proactively keep limited popular content at the edge of network based on predicted results. Meanwhile, the interactions between the content (e.g., deep neural network models, Wikipedia-alike knowledge base) and users could be regarded as a dynamic bipartite graph. In this paper, to maximize the cache hit rate, we leverage an effective dynamic graph neural network (DGNN) to jointly learn the structural and temporal patterns embedded in the bipartite graph. Furthermore, in order to have deeper insights into the dynamics within the evolving graph, we propose an age of information (AoI) based attention mechanism to extract valuable historical information while avoiding the problem of message staleness. Combining this aforementioned prediction model, we also develop a cache selection algorithm to make caching decisions in accordance with the prediction results. Extensive results demonstrate that our model can obtain a higher prediction accuracy than other state-of-the-art schemes in two real-world datasets. The results of hit rate further verify the superiority of the caching policy based on our proposed model over other traditional ways.

cs.LG↗
arXiv2020

The supermassive black hole masses of reverberation-mapped active galactic nuclei

Using different kinds of velocity tracers derived from the broad H$\beta$ profile (in the mean or rms spectrum) and the corresponding virial factors $f$, the central supermassive black hole (SMBH) masses ($M_{\rm BH}$) are calculated for a compiled sample of 120 reverberation-mapped (RM) AGNs. For its subsample of RM AGNs with measured stellar velocity dispersion ($\sigma_{\rm \ast}$), the multivariate linear regression technique is used to calibrate the mean value $f$, as well as the variable FWHM-based $f$. It is found that, whether excluding the pseudo-bulges or not, $M_{\rm BH}$ from the H$\beta$ line dispersion in the mean spectrum ($\sigma_{\rm H\beta,mean}$) has the smallest offset rms with respect to the $M_{\rm BH}-\sigma_{\ast}$ relation. For the total sample excluding SDSS-RM AGNs, with respect to $M_{\rm BH}$ from $\sigma_{\rm \ast}$ or that from the H$\beta$ line dispersion in the rms spectrum ($\sigma_{\rm H\beta,rms}$), it is found that we can obtain $M_{\rm BH}$ from the $\sigma_{\rm H\beta,mean}$ with the smallest offset rms of 0.38 dex or 0.23 dex, respectively. It implies that, with respect to the H$\beta$ FWHM, we prefer $\sigma_{\rm H\beta,mean}$ to calculate $M_{\rm BH}$ from the single-epoch spectrum. Using the FWHM-based $f$, we can improve $M_{\rm BH}$ calculation from FWHM(H$\beta$) and the mean $f$, with a decreased offset rms from 0.52 dex to 0.39 dex with respect to $M_{\rm BH}$ from $\sigma_{\rm \ast}$ for the subsample of 36 AGNs with $\sigma_{\rm \ast}$. The value of 0.39 dex is almost the same as that from $\sigma_{\rm H\beta,mean}$ and the mean $f$.

astro-ph.GA↗
arXiv2019

An extended size-luminosity relation for the reverberation-mapped AGNs: the role of the accretion rate

For a compiled sample of 120 reverberation-mapped AGNs, the bivariate correlations of the broad-line regions (BLRs) size ($R_{\rm BLR}$) with the continuum luminosity at 5100 \AA\ ($L_{5100}$) and the dimensionless accretion rates ($\dot{\mathscr{M}}$) are investigated. Using our recently calibrated virial factor $f$, and the velocity tracer from the H$\beta$ Full-width at half-maximum (FWHM(H$\beta$)) or the line dispersion ($\sigma_{\rm H\beta}$) measured in the mean spectra, three kinds of SMBH masses and $\dot{\mathscr{M}}$ are calculated. An extended \RL relation including $\dot{\mathscr{M}}$ is found to be stronger than the canonical $R_{\rm BLR}({\rm H\beta}) - L_{\rm 5100}$ relation, showing smaller scatters. The observational parameters, $R_{\rm Fe}$ (the ratio of optical Fe II to H$\beta$ line flux) and the line profile parameter $D_{\rm H\beta}$ ($D_{\rm H\beta}=\rm FWHM(H\beta)/\sigma_{\rm H\beta}$), have relations with three kinds of $\dot{\mathscr{M}}$. Using $R_{\rm Fe}$ and $D_{\rm H\beta}$ to substitute $\dot{\mathscr{M}}$, extended empirical $R_{\rm BLR}({\rm H\beta}) - L_{\rm 5100}$ relations are presented. $R_{\rm Fe}$ is a better "fix" for the $R_{\rm BLR}({\rm H\beta}) - L_{\rm 5100}$ offset than the H$\beta$ shape $D_{\rm H\beta}$. The extended empirical $R_{\rm BLR}({\rm H\beta}) - L_{\rm 5100}$ relation including $R_{\rm Fe}$ can be used to calculate $R_{\rm BLR}$, and thus the single-epoch SMBH mass $M_{\rm BH}$. Our measured accretion rate dependence is not consistent with the simple model of the accretion disk instability leading the BLRs formation. The BLR may instead form from the inner edge of the torus, or from some other means in which BLR size is positively correlated with accretion rate and the SMBH mass.

astro-ph.GA↗
arXiv2019

Calibration of the virial factor $f$ in supermassive black hole masses of reverberation-mapped AGNs

Using a compiled sample of 34 broad-line active galactic nuclei (AGNs) with measured H$\beta$ time lags from the reverberation mapping (RM) method and measured bulge stellar velocity dispersions $\sigma_*$, we calculate the virial factor $f$ by assuming that the RM AGNs intrinsically obey the same $M_{\rm BH}-\sigma_*$ relation as quiescent galaxies, where $M_{\rm BH}$ is the mass of the supermassive black hole (SMBH). Considering four tracers of the velocity of the broad-line regions (BLRs), i.e., the H$\beta$ line width or line dispersion from the mean or rms spectrum, there are four kinds of the factor $f$. Using the \hb Full-width at half-maximum (FWHM) to trace the BLRs velocity, we find significant correlations between the factor $f$ and some observational parameters, e.g., FWHM, the line dispersion. Using the line dispersion to trace the BLRs velocity, these relations disappear or become weaker. It implies the effect of inclination in BLRs geometry. It also suggests that the variable $f$ in $M_{\rm BH}$ estimated from luminosity and FWHM in a single-epoch spectrum is not negligible. Using a simple model of thick-disk BLRs, we also find that, as the tracer of the BLRs velocity, H$\beta$ FWHM has some dependence on the inclination, while the line dispersion $\sigma_{\rm H\beta }$ is insensitive to the inclination. Considering the calibrated FWHM-based factor $f$ from the mean spectrum, the scatter of the SMBH mass is 0.39 dex for our sample of 34 low redshift RM AGNs. For a high redshift sample of 30 SDSS RM AGNs with measured stellar velocity dispersions, we find that the SMBH mass scatter is larger than that for our sample of 34 low redshift RM AGNs. It implies the possibility of evolution of the $M_{\rm BH}-\sigma_*$ relation from high-redshift to low-redshift AGNs.

astro-ph.GA↗
arXiv2019

Hot Corona Properties of Swift/BAT detected AGN

Using a sample of 208 broad-line active galactic nuclei (AGNs) from Swift/BAT AGN Spectroscopic Survey in ultra-hard X-ray band ($14-195$ keV), the hot corona properties are investigated, i.e. the fraction of gravitational energy dissipated in the hot corona and the hard X-ray photon index. The bolometric luminosity, \lb, is calculated from host-corrected luminosity at 5100 \AA. Virial supermassive black hole masses (SMBH, \mbh) are calculated from the $\rm H\beta$ line width and the corresponding broad line region size-luminosity empirical relation at 5100 \AA. We find a strong anti-correlation between the fraction of energy released in corona ($F_x \equiv L_{14-195 keV}/L_{\rm Edd}$) and the Eddington ratio ($ \varepsilon \equiv L_{\rm Bol}/L_{\rm Edd}$), $F_x \propto \varepsilon^{-0.60\pm 0.1}$. It is found that this fraction also has a correlation with the SMBH mass, $F_x \propto \varepsilon^{-0.74\pm 0.14} M_{\rm BH}^{-0.30\pm 0.03}$. Assuming that magnetic buoyancy and feild reconnection lead to the formation of a hot corona, our result favours the shear stress tensor being a proportion of the gas pressure. For our entire sample, it is found that the hard X-ray photon index $\Gamma$ has a weak but significant correlation with the Eddington ratio, $ \Gamma=2.17+0.21\log \varepsilon$. However, this correlation is not robust because the relation is not statistically significant for its subsample of 32 RM AGNs with relatively reliable $M_{\rm BH}$ or its subsample of 166 AGNs with single-epoch $M_{\rm BH}$. We do not find a statistically significant relation between the photon index and the Eddington ratio taking into account an additional dependence on $F_x$.

astro-ph.HE↗