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Shu Wang

Publications and source records attributed to Shu Wang.

At least 109 records · Page 6Linked to original sources
arXiv2024

Ultra-High-Definition Dynamic Multi-Exposure Image Fusion via Infinite Pixel Learning

With the continuous improvement of device imaging resolution, the popularity of Ultra-High-Definition (UHD) images is increasing. Unfortunately, existing methods for fusing multi-exposure images in dynamic scenes are designed for low-resolution images, which makes them inefficient for generating high-quality UHD images on a resource-constrained device. To alleviate the limitations of extremely long-sequence inputs, inspired by the Large Language Model (LLM) for processing infinitely long texts, we propose a novel learning paradigm to achieve UHD multi-exposure dynamic scene image fusion on a single consumer-grade GPU, named Infinite Pixel Learning (IPL). The design of our approach comes from three key components: The first step is to slice the input sequences to relieve the pressure generated by the model processing the data stream; Second, we develop an attention cache technique, which is similar to KV cache for infinite data stream processing; Finally, we design a method for attention cache compression to alleviate the storage burden of the cache on the device. In addition, we provide a new UHD benchmark to evaluate the effectiveness of our method. Extensive experimental results show that our method maintains high-quality visual performance while fusing UHD dynamic multi-exposure images in real-time (>40fps) on a single consumer-grade GPU.

cs.CV↗
arXiv2024

Classification of Periodic Variable Stars from TESS

The number of known periodic variable stars has increased rapidly in recent years. As an all-sky transit survey, the Transiting Exoplanet Survey Satellite (TESS) plays an important role in detecting low-amplitude variable stars. Using 2-minute cadence data from the first 67 sectors of TESS, we find 72,505 periodic variable stars. We used 19 parameters including period, physical parameters, and light curve (LC) parameters to classify periodic variable stars into 12 sub-types using random forest method. Pulsating variable stars and eclipsing binaries are distinguished mainly by period, LC parameters and physical parameters. GCAS, ROT, UV, YSO are distinguished mainly by period and physical parameters. Compared to previously published catalogs, 63,106 periodic variable stars (87.0$\%$) are newly classified, including 13 Cepheids, 27 RR Lyrae stars, $\sim$4,600 $δ$ Scuti variable stars, $\sim$1,600 eclipsing binaries, $\sim$34,000 rotational variable stars, and about 23,000 other types of variable stars. The purity of eclipsing binaries and pulsation variable stars ranges from 94.2$\%$ to 99.4$\%$ when compared to variable star catalogs of Gaia DR3 and ZTF DR2. The purity of ROT is relatively low at 83.3$\%$. The increasing number of variables stars is helpful to investigate the structure of the Milky Way, stellar physics, and chromospheric activity.

astro-ph.SR↗
arXiv2024

Optical Continuum Reverberation Mapping of a Candidate IMBH in a Nearby Seyfert 1 Galaxy

To investigate the short-term variability and determine the size of the optical continuum emitting region of intermediate-mass black holes (IMBHs), we carried out high-cadence, multiband photometric monitoring of a Seyfert 1 galaxy J0249-0815 across two nights, together with a one-night single-band preliminary test. The presence of the broad Ha component in our target was confirmed by recent Paloma spectroscopic observations, 23 years after the Sloan Digital Sky Survey, ruling out the supernovae origin of the broad Ha line. The photometric experiment was primarily conducted utilizing four-channel imagers MuSCAT 3 and 4 mounted on 2 m telescopes within the Las Cumbres Observatory Global Telescope Network. Despite the expectation of variability, we observed no significant variation (<1.4%) on timescales of 6 to 10 hr. This nondetection is likely due to substantial host galaxy light diluting the subtle active galactic nucleus (AGN) variability. Additionally, we cannot rule out that the target was in a relatively quiescent state without intranight variability during our monitoring, owing to the stochastic nature of AGN variations. To enhance the possibility of detecting subtle variability signals and lag in future IMBH reverberation campaigns, it may be beneficial to select targets with a higher AGN-to-host flux ratio, and conduct dual-band preliminary tests and tailored simulations.

astro-ph.GA↗
arXiv2024

Dormancy and Reawakening Over Years: Eight New Recurrent Changing-Look AGNs

We report the discovery of eight new recurrent changing-look (CL) active galactic nuclei (AGNs), including seven re-brightening turn-off AGNs and one fading turn-on AGN. These systems are valuable for placing constraints on the duration of dim and bright states, which may be linked to the AGN duty cycle or disk instability. Long-term optical light curve analysis reveals that many objects in our sample exhibit a prolonged plateau during the dim states lasting 4 to 7 years, with gradual turn-on/off process. We observe no significant difference between the turn-on and turn-off timescales, and this timescale is broadly consistent with the heating/cooling front propagation timescale. The comparison between optical and infrared variations supports that these transitions are driven by changes in accretion disk emission rather than dust obscuration. Our discovery significantly increases the previously identified recurrent CL AGN sample from eleven objects to nineteen, demonstrating that some AGNs can enter dormancy and reawaken on timescales of a few years, which provides useful information for understanding AGN episodic accretion.

astro-ph.GA↗
arXiv2024

Prior-Informed AGN-Host Spectral Decomposition Using PyQSOFit

We introduce an improved method for decomposing the emission of active galactic nuclei (AGN) and their host galaxies using templates from principal component analysis (PCA). This approach integrates prior information from PCA with a penalized pixel fitting mechanism which improves the precision and effectiveness of the decomposition process. Specifically, we have reduced the degeneracy and over-fitting in AGN-host decomposition, particularly for those with low signal-to-noise ratios (SNR), where traditional methods tend to fail. By applying our method to 76,565 SDSS Data Release 16 quasars with $z<0.8$, we achieve a success rate of $\approx$ 94%, thus establishing the largest host-decomposed spectral catalog of quasars to date. Our fitting results consider the impact of the host galaxy on the overestimation of the AGN luminosity and black hole mass ($M_{\rm BH}$). Furthermore, we obtained stellar velocity dispersion ($σ_*$) measurements for 4,137 quasars. The slope of the $M_{\rm BH}-σ_*$ relation in this subsample is generally consistent with previous quasar studies beyond the local universe. Our method provides a robust and efficient approach to disentangle the AGN and host galaxy components across a wide range of SNRs and redshifts.

astro-ph.GA↗
arXiv2024

Extinction of Taurus, Orion, Perseus and California Molecular Clouds Based on the LAMOST, 2MASS, and Gaia Surveys II: The Extinction Law

The extinction law from ultraviolet (UV) to infrared (IR) (0.2-24 $μ$m) is determined by relying on the blue-edge method and color excess ratios for some nearby molecular clouds, from low mass star forming region to massive star forming region. The observational data are collected from nine photometric surveys, along with stellar parameters from the APOGEE and LAMOST spectroscopic surveys. Within the uncertainties, the optical ratio of selective to total extinction ($R_{G_{BP}}$) does not vary substantially across the clouds, irrespective of the density, specifically $R_{G_{BP}} =2.302\pm0.027$, where $R_{G_{BP}} \equiv A_{G_{BP}}/E_{G_{BP},G_{RP}}$. The IR extinction law is consistent with \citet{Wang19_law}. The extinction law in the UV band is compromised by the shallow depth with $A_{V} \leq 2$ mag and is hard to describe by one parameter $R$. In addition, the extinction in the WISE/W1 band is significantly larger than in the Spitzer/IRAC1 band in the dense regions, which is attributed to the ice water absorption.

astro-ph.GA↗
arXiv2024

Physical Parameters and Properties of 20 Cold Brown Dwarfs in JWST

We present a comprehensive analysis of 20 T and Y dwarfs using spectroscopy from the NIRSpec CLEAR/PRISM and MIRI LRS instruments on the James Webb Space Telescope. To characterize the atmospheric parameters, we utilize two atmospheric model grids: the Sonora Elf Owl and ATMO2020++. The effective temperatures derived from the two models are relatively consistent, and metallicities are both close to solar values. However, significant discrepancies are found in other parameters, particularly in surface gravity, with the values obtained from the Sonora Elf Owl models typically being about 1 dex lower than those from the ATMO2020++ models. Further comparisons using the ATMO2020 models highlight that the adiabatic convective process introduced in the ATMO2020++ models has a significant impact on the determination of surface gravity. Using the fitted effective temperatures and absolute parallaxes from the literature, we derive radii for the brown dwarfs, which range from approximately 0.8 to 1.2 $R_{\mathrm{Jup}}$. The estimated masses and ages, derived using evolutionary tracks, indicate that most brown dwarfs in our sample have masses below 30 $M_{\mathrm{Jup}}$ and are younger than 6 Gyr. Specifically, Y dwarfs have masses ranging from 2 to 20 $M_{\mathrm{Jup}}$ and ages between 0.1 and 6.7 Gyr. In addition, We discuss the determination of atmospheric parameters using only NIRSpec or MIRI spectra. Comparisons with results from the combined spectra show that the effective temperatures and surface gravities derived solely from NIRSpec spectra are largely consistent with those obtained from the combined spectra.

astro-ph.SR↗
arXiv2024

FedGCA: Global Consistent Augmentation Based Single-Source Federated Domain Generalization

Federated Domain Generalization (FedDG) aims to train the global model for generalization ability to unseen domains with multi-domain training samples. However, clients in federated learning networks are often confined to a single, non-IID domain due to inherent sampling and temporal limitations. The lack of cross-domain interaction and the in-domain divergence impede the learning of domain-common features and limit the effectiveness of existing FedDG, referred to as the single-source FedDG (sFedDG) problem. To address this, we introduce the Federated Global Consistent Augmentation (FedGCA) method, which incorporates a style-complement module to augment data samples with diverse domain styles. To ensure the effective integration of augmented samples, FedGCA employs both global guided semantic consistency and class consistency, mitigating inconsistencies from local semantics within individual clients and classes across multiple clients. The conducted extensive experiments demonstrate the superiority of FedGCA.

cs.AI↗
arXiv2024

Mapping the nanoscale optical topological textures with a fiber-integrated plasmonic probe

Topologically protected quasiparticles in optics have received increasing research attention recently, as they provide novel degree of freedom to manipulate light-matter interactions and exhibiting excellent potential in nanometrology and ultrafast vector imaging. However, the characterization of the full three-dimensional vectorial structures of the topological texures at the nanoscale has remained a challenge. Here, we propose a novel probe based on the fiber taper-silver nanowire waveguide structure to achieve super-resolution mapping of the topological textures. Based on the mode selection rules, the three-dimensional decomposed electric fields in both the far-field and near-field are directly collected and reconstructed without postprocessing algorithms, clearly visualizing the topological texures formed in free space and evanescent waves respectively. The fiber-integrated probe is further demonstrated to be robust and broadband. This approach holds promise for the characterization of more sophisticated topology in optical field, which may allow for advance applications in optical information processing and data storage.

physics.optics↗
arXiv2024

Revisiting the H$β$ Size-Luminosity Relation Using a Uniform Reverberation-Mapping Analysis

We revisit the relation between active galactic nucleus (AGN) broad-line region (BLR) size and luminosity by conducting a uniform H$β$ reverberation-mapping analysis for 212 AGNs with archival light curves. Our analysis incorporates three different lag measurement methods, including the interpolated cross-correlation function (ICCF), JAVELIN, and PyROA, alongside a consistently defined lag searching window and an alias removal procedure. We find that ICCF, albeit with larger uncertainties compared to other methods, is the most reliable method based on our visual inspection of the matches between H$β$ and the shifted continuum light curves. Combining this sample with the 32 AGNs from the Seoul National University AGN Monitoring Project, we obtain the best-fit relation between the BLR size ($R_{\rm BLR}$) and the continuum luminosity at 5100$Å$ ($L_{5100}$) with a slope significantly flatter than 0.5. By selecting a subsample of 157 AGNs with the best-quality lag measurements using a set of quantitative criteria and visual inspection, we find a consistent slope and a slightly decreased intrinsic scatter. We further investigate the effect of luminosity tracers, including $L_{5100}$, H$β$ luminosity ($L_{\rm Hβ}$), ${\rm [O\,\mathrm{III}]}$ luminosity ($L_{\rm [O\,\mathrm{III}]}$), and 2 to 10 keV hard X-ray luminosity ($L_{\rm 2\unicode{x2013}10\,keV}$). We find that sub-Eddington and super-Eddington AGNs exhibit systematic offsets in both $R_{\rm BLR}$$\unicode{x2013}$$L_{5100}$ and $R_{\rm BLR}$$\unicode{x2013}$$L_{\rm Hβ}$ relation, but are comparable in the $R_{\rm BLR}$$\unicode{x2013}$$L_{\rm [O\,\mathrm{III}]}$ and $R_{\rm BLR}$$\unicode{x2013}$$L_{\rm 2\unicode{x2013}10\,keV}$ relation. We discuss the potential causes for these different deviations when employing different luminosity tracers.

astro-ph.GA↗
arXiv2024

LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning

Conventional Task and Motion Planning (TAMP) approaches rely on manually crafted interfaces connecting symbolic task planning with continuous motion generation. These domain-specific and labor-intensive modules are limited in addressing emerging tasks in real-world settings. Here, we present LLM^3, a novel Large Language Model (LLM)-based TAMP framework featuring a domain-independent interface. Specifically, we leverage the powerful reasoning and planning capabilities of pre-trained LLMs to propose symbolic action sequences and select continuous action parameters for motion planning. Crucially, LLM^3 incorporates motion planning feedback through prompting, allowing the LLM to iteratively refine its proposals by reasoning about motion failure. Consequently, LLM^3 interfaces between task planning and motion planning, alleviating the intricate design process of handling domain-specific messages between them. Through a series of simulations in a box-packing domain, we quantitatively demonstrate the effectiveness of LLM^3 in solving TAMP problems and the efficiency in selecting action parameters. Ablation studies underscore the significant contribution of motion failure reasoning to the success of LLM^3. Furthermore, we conduct qualitative experiments on a physical manipulator, demonstrating the practical applicability of our approach in real-world settings.

cs.RO↗
arXiv2024

Data-driven stellar intrinsic colors and dust reddenings for spectro-photometric data: From the blue-edge method to a machine-learning approach

Intrinsic colors (ICs) of stars are essential for the studies on both stellar physics and dust reddening. In this work, we developed an XGBoost model to predict the ICs with the atmospheric parameters $T_{\rm eff}$, ${\rm log}\,g$, and $\rm [M/H]$. The model was trained and tested for three colors at Gaia and 2MASS bands with 1,040,446 low-reddening sources. The atmospheric parameters were determined by the Gaia DR3 GSP-phot module and were validated by comparing with APOGEE and LAMOST. We further confirmed that the biases in GSP-phot parameters, especially for $\rm [M/H]$, do not present a significant impact on the IC prediction. The generalization error of the model estimated by the test set is 0.014 mag for $(G_{\rm BP}\,{-}\,G_{\rm RP})_0$, 0.050 mag for $(G_{\rm BP}\,{-}\,K_{\rm S})_0$, and 0.040 mag for $(J\,{-}\,K_{\rm S})_0$. The model was applied to a sample containing 5,714,528 reddened stars with stellar parameters from Andrae et al. (2023) to calculate ICs and reddenings. The high consistency in the comparison of $E(J\,{-}\,K_{\rm S})$ between our results and literature values further validates the accuracy of the XGBoost model. The variation of $E(G_{\rm BP}\,{-}\,K_{\rm S})/E(G_{\rm BP}\,{-}\,G_{\rm RP})$, a representation of the extinction law, with Galactic longitude is found on large scales. This work preliminarily presents the feasibility and the accuracy of the machine-learning approach for IC and dust reddening calculation, whose products could be widely applied to spectro-photometric data. The data sets and trained model can be accessed via \url{https://doi.org/10.5281/zenodo.12787594}. The models for more bands will be completed in the following works.

astro-ph.SR↗
arXiv2024

MBD-NODE: Physics-informed data-driven modeling and simulation of constrained multibody systems

We describe a framework that can integrate prior physical information, e.g., the presence of kinematic constraints, to support data-driven simulation in multi-body dynamics. Unlike other approaches, e.g., Fully-connected Neural Network (FCNN) or Recurrent Neural Network (RNN)-based methods that are used to model the system states directly, the proposed approach embraces a Neural Ordinary Differential Equation (NODE) paradigm that models the derivatives of the system states. A central part of the proposed methodology is its capacity to learn the multibody system dynamics from prior physical knowledge and constraints combined with data inputs. This learning process is facilitated by a constrained optimization approach, which ensures that physical laws and system constraints are accounted for in the simulation process. The models, data, and code for this work are publicly available as open source at https://github.com/uwsbel/sbel-reproducibility/tree/master/2024/MNODE-code.

cs.CE↗
arXiv2024

Dye4AI: Assuring Data Boundary on Generative AI Services

Generative artificial intelligence (AI) is versatile for various applications, but security and privacy concerns with third-party AI vendors hinder its broader adoption in sensitive scenarios. Hence, it is essential for users to validate the AI trustworthiness and ensure the security of data boundaries. In this paper, we present a dye testing system named Dye4AI, which injects crafted trigger data into human-AI dialogue and observes AI responses towards specific prompts to diagnose data flow in AI model evolution. Our dye testing procedure contains 3 stages: trigger generation, trigger insertion, and trigger retrieval. First, to retain both uniqueness and stealthiness, we design a new trigger that transforms a pseudo-random number to a intelligible format. Second, with a custom-designed three-step conversation strategy, we insert each trigger item into dialogue and confirm the model memorizes the new trigger knowledge in the current session. Finally, we routinely try to recover triggers with specific prompts in new sessions, as triggers can present in new sessions only if AI vendors leverage user data for model fine-tuning. Extensive experiments on six LLMs demonstrate our dye testing scheme is effective in ensuring the data boundary, even for models with various architectures and parameter sizes. Also, larger and premier models tend to be more suitable for Dye4AI, e.g., trigger can be retrieved in OpenLLaMa-13B even with only 2 insertions per trigger item. Moreover, we analyze the prompt selection in dye testing, providing insights for future testing systems on generative AI services.

cs.CR↗
arXiv2024

The Surprising Benefits of Base Rate Neglect in Robust Aggregation

Robust aggregation integrates predictions from multiple experts without knowledge of the experts' information structures. Prior work assumes experts are Bayesian, providing predictions as perfect posteriors based on their signals. However, real-world experts often deviate systematically from Bayesian reasoning. Our work considers experts who tend to ignore the base rate. We find that a certain degree of base rate neglect helps with robust forecast aggregation. Specifically, we consider a forecast aggregation problem with two experts who each predict a binary world state after observing private signals. Unlike previous work, we model experts exhibiting base rate neglect, where they incorporate the base rate information to degree $λ\in[0,1]$, with $λ=0$ indicating complete ignorance and $λ=1$ perfect Bayesian updating. To evaluate aggregators' performance, we adopt Arieli et al. (2018)'s worst-case regret model, which measures the maximum regret across the set of considered information structures compared to an omniscient benchmark. Our results reveal the surprising V-shape of regret as a function of $λ$. That is, predictions with an intermediate incorporating degree of base rate $λ<1$ can counter-intuitively lead to lower regret than perfect Bayesian posteriors with $λ=1$. We additionally propose a new aggregator with low regret robust to unknown $λ$. Finally, we conduct an empirical study to test the base rate neglect model and evaluate the performance of various aggregators.

cs.LG↗
arXiv2024

Optical biomarker of metabolism for breast tumor diagnosis: Insights from subcellular dynamics

Label-free metabolic dynamics contrast is highly appealing but difficult to achieve in biomedical imaging. Interference offers a highly sensitive mechanism for capturing the metabolic dynamics of the subcellular scatterers. However, traditional interference detection methods fail to isolate pure metabolic dynamics, as the dynamic signals are coupled with scatterer reflectivity and other uncontrollable imaging factors. Here, we demonstrate active phase modulation-assisted dynamic full-field optical coherence tomography (APMD-FFOCT) that decouples and quantifies the metabolic dynamics by adding a reference movement for all interferential scatterers. This novel technique enables imaging and dynamic analysis of subcellular structures along with their changes during the apoptotic process in tumor tissues. Furthermore, the nucleus-to-cytoplasm dynamic intensity ratio could serve as an optical biomarker for breast tumor grading, enhancing intraoperative diagnosis.

physics.med-ph↗
arXiv2024

Multi-mode delta Sct stars from the Zwicky Transient Facility Survey

We obtain the largest catalog of multi-mode $δ$ Sct stars in the northern sky to date using the Zwicky Transient Facility (ZTF) Data Release 20 (DR20). The catalog includes 2254 objects, of which 2181 are new to our study. Among these multi-mode $δ$ Sct stars, 2142 objects are double-mode $δ$ Sct, while 109 objects are triple-mode $δ$ Sct and 3 are quadruple-mode $δ$ Sct. By analyzing the light curves in the $r$ and $g$ bands of the ZTF, we determine the basic parameters of multi-mode $δ$ Sct stars, including the periods and amplitudes. Periods are checked by comparison with the OGLE catalog of double-mode $δ$ Sct stars. On the Petersen diagram, multi-mode $δ$ Sct stars form six sequences. We find that in Galactic coordinates, the periods of 1O/F double-mode $δ$ Sct stars at high latitudes are shorter than those of 1O/F double-mode $δ$ Sct stars in the disk, due to metallicity variations. In the future, our catalog can be used to establish the period--luminosity relation and the period--metallicity relation of double-mode $δ$ Sct stars, and to study the Galactic structure.

astro-ph.SR↗