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Jianjun Chen

Jianjun Chen appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record
Artificial Intelligenceastro-ph.COphysics.opticsastro-ph.GAastro-ph.SRDatabasesmath.APmath.OCphysics.comp-phphysics.soc-phSocial and Information Networks

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Published work

11 published item(s)

preprint2026arXiv

SCGNN: Semantic Consistency enhanced Graph Neural Network Guided by Granular-ball Computing

Capturing semantic consistency among nodes is crucial for effective graph representation learning. Existing approaches typically rely on $k$-nearest neighbors ($k$NN) or other node-level full search algorithms (FSA) to mine semantic relationships via exhaustive pairwise similarity computation, which suffer from high computational complexity and rigid neighbor selection, limiting scalability and introducing noisy connections. In this paper, we propose the Semantic Consistency enhanced Graph Neural Network (SCGNN), a novel plug-and-play framework that leverages granular-ball computing (GBC) to efficiently capture semantic consistency in a scalable manner. Unlike node-level FSA methods, SCGNN models group-level semantic structure by adaptively partitioning nodes into granular balls, significantly reducing computational cost while improving robustness to noise. To effectively utilize the discovered group-level semantic consistency, we design a dual enhancement strategy. Specifically, (1) a structure enhancement module constructs an anchor-based graph structure, where each anchor is a virtual node representing the group-level semantic carried by a granular ball, then injecting group-level semantic information into the graph structure; and (2) a supervision enhancement module performs label consistency checking (LCC) by combining GBC predictions with model-generated pseudo-labels, thereby producing more reliable supervision signals. SCGNN is compatible with various GNN backbones. During the forward propagation of SCGNN, the vanilla graph and the augment graph are jointly encoded, and their predictions are fused; during the backpropagation, the supervision enhancement module provides enhanced supervision signals to guide parameter updates.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning

Understanding time series is crucial for its application in real-world scenarios. Recently, large language models (LLMs) have been increasingly applied to time series tasks, leveraging their strong language capabilities to enhance various applications. However, research on multimodal LLMs (MLLMs) for time series understanding and reasoning remains limited, primarily due to the scarcity of high-quality datasets that align time series with textual information. This paper introduces ChatTS, a novel MLLM designed for time series analysis. ChatTS treats time series as a modality, similar to how vision MLLMs process images, enabling it to perform both understanding and reasoning with time series. To address the scarcity of training data, we propose an attribute-based method for generating synthetic time series with detailed attribute descriptions. We further introduce Time Series Evol-Instruct, a novel approach that generates diverse time series Q&As, enhancing the model's reasoning capabilities. To the best of our knowledge, ChatTS is the first TS-MLLM that takes multivariate time series as input for understanding and reasoning, which is fine-tuned exclusively on synthetic datasets. We evaluate its performance using benchmark datasets with real-world data, including six alignment tasks and four reasoning tasks. Our results show that ChatTS significantly outperforms existing vision-based MLLMs (e.g., GPT-4o) and text/agent-based LLMs, achieving a 46.0% improvement in alignment tasks and a 25.8% improvement in reasoning tasks. We have open-sourced the source code, model checkpoint and datasets at https://github.com/NetManAIOps/ChatTS.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Adaptive Multigrid Strategy for Geometry Optimization of Large-Scale Three Dimensional Molecular Mechanics

In this paper, we present an efficient adaptive multigrid strategy for the geometry optimization of large-scale three dimensional molecular mechanics. The resulting method can achieve significantly reduced complexity by exploiting the intrinsic low-rank property of the material configurations and by combining the state-of-the-art adaptive techniques with the hierarchical structure of multigrid algorithms. To be more precise, we develop a oneway multigrid method with adaptive atomistic/continuum (a/c) coupling, e.g., blended ghost force correction (BGFC) approximations with gradient-based a posteriori error estimators on the coarse levels. We utilize state-of-the-art 3D mesh generation techniques to effectively implement the method. For 3D crystalline defects, such as vacancies, micro-cracks and dislocations, compared with brute-force optimization, complexity with superior rates can be observed numerically, and the strategy has a five-fold acceleration in terms of CPU time for systems with $10^8$ atoms.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Self-similar solutions of the spherically symmetric Euler equations for general equations of state

The study of spherically symmetric motion is important for the theory of explosion waves. In this paper, we construct rigorously self-similar solutions to the Riemann problem of the spherically symmetric Euler equations for general equations of state. We used the assumption of self-similarity to reduce the spherically symmetric Euler equations to a system of nonlinear ordinary differential equations, from which we obtain detailed structures of solutions besides their existence.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Controlling Surface-plasmon-polariton Launching with Hot Spot Cylindrical Waves in a Metallic Slit Structure

Plasmonic nanostructures, which are used to generate surface plasmon polaritions (SPPs), always involve sharp corners where the charges can accumulate. This can result in strong localized electromagnetic fields at the metallic corners, forming hot spots. The influence of the hot spots on the propagating SPPs are investigated theoretically and experimentally in a metallic slit structure. It is found that the electromagnetic fields radiated from the hot spots, termed as the hot spot cylindrical wave (HSCW), can greatly manipulate the SPP launching in the slit structure. The physical mechanism behind the manipulation of the SPP launching with the HSCW is explicated by a semi-analytic model. By using the HSCW, unidirectional SPP launching is experimentally realized in an ultra-small metallic step-slit structure. The HSCW bridges the localized surface plasmons and the propagating surface plasmons in an integrated platform and thus may pave a new route to the design of plasmonic devices and circuits.

0 citations0 reviewsNo code linkedOpen access
preprint2015arXiv

Polarization-Independent and High-Efficiency Dielectric Metasurfaces Spanning 600-800 nm Wavelengths

Artificial metasurfaces are capable of completely manipulating the phase, amplitude, and polarization of light with high spatial resolutions. The emerging design based on high-index and low-loss dielectrics has led to the realization of novel metasurfaces with high transmissions, but these devices usually operate at the limited bandwidth, and are sensitive to the incident polarization. Here, for the first time we report experimentally the polarization-independent and high-efficiency dielectric metasurfaces spanning the visible wavelengths about 200 nm, which are of importance for novel flat optical devices operating over a broad spectrum. The diffraction efficiencies of the gradient metasurfaces consisting of the multi-fold symmetric nano-crystalline silicon nanopillars are up to 93% at 670 nm, and exceed 75% at the wavelengths from 600 to 800 nm for the two orthogonally polarized incidences. These dielectric metasurfaces hold great potential to replace prisms, lenses and other conventional optical elements.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Scalable Social Coordination using Enmeshed Queries

Social coordination allows users to move beyond awareness of their friends to efficiently coordinating physical activities with others. While specific forms of social coordination can be seen in tools such as Evite, Meetup and Groupon, we introduce a more general model using what we call enmeshed queries. An enmeshed query allows users to declaratively specify an intent to coordinate by specifying social attributes such as the desired group size and who/what/when, and the database returns matching queries. Enmeshed queries are continuous, but new queries (and not data) answer older queries; the variable group size also makes enmeshed queries different from entangled queries, publish-subscribe systems, and dating services. We show that even offline group coordination using enmeshed queries is NP-hard. We then introduce efficient heuristics that use selective indices such as location and time to reduce the space of possible matches; we also add refinements such as delayed evaluation and using the relative matchability of users to determine search order. We describe a centralized implementation and evaluate its performance against an optimal algorithm. We show that the combination of not stopping prematurely (after finding a match) and delayed evaluation results in an algorithm that finds 86% of the matches found by an optimal algorithm, and takes an average of 40 usec per query using 1 core of a 2.5 Ghz server machine. Further, the algorithm has good latency, is reasonably fair to large group size requests, and can be scaled to global workloads using multiple cores and multiple servers. We conclude by describing potential generalizations that add prices, recommendations, and data mining to basic enmeshed queries.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

The selection of LEGUE disk targets for LAMOST's pilot survey

We describe the target selection algorithm for the low latitude disk portion of the LAMOST Pilot Survey, which aims to test systems in preparation for the LAMOST spectroscopic survey. We use the PPMXL (Roeser et al. 2010) astrometric catalog, which provides positions, proper motions, B/R/I magnitudes (mostly) from USNO-B (Monet et al. 2003) and J/H/Ks from The Two Micron All Sky Survey (2MASS, see Skrutskie et al. 2006) as well. We chose 8 plates along the Galactic plane, in the region $0^\circ<α<67^\circ$ and $42^\circ<δ<59^\circ$, that cover 22 known open clusters with a range of ages. Adjacent plates may have small overlapping. Each plate covers an area $2.5^\circ$ in radius,with central star (for Shack-Hartmann guider) brighter than $\sim8^{\rm th}$ magnitude. For each plate, we create an input catalog in the magnitude range $11.3<Imag<16.3$ and $Bmag$ available from PPMXL. The stars are selected to satisfy the requirements of the fiber positioning system and have a uniform distribution in the $I$ vs. $B-I$ color-magnitude diagram. Our final input catalog consists of 12,000 objects on each of 8 plates that are observable during the winter observing season in Xinglong Station of the National Astronomical Observatory of China.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Automatic Determination of Stellar Atmospheric Parameters and Construction of Stellar Spectral Templates of the Guoshoujing Telescope (LAMOST)

A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to-noise ratios (SNR) on the measurement of the stellar atmospheric parameters (effective temperature Teff, surface gravity log g, and metallicity [Fe/H]). We show that ULySS is reliable to determine these parameters with medium-resolution spectra (R~2000). Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope (GSJT). The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline (SSPP), and we derived precisions of 167 K, 0.34 dex, and 0.16 dex for Teff, log g and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectra template library (Version 1.0) of GSJT, and will be deployed as basic ingredients for the GSJT automated parametrization pipeline.

0 citations0 reviewsNo code linkedOpen access
preprint2010arXiv

A very bright i=16.44 quasar in the `redshift desert' discovered by LAMOST

The redshift range from 2.2 to 3, is known as the 'redshift desert' of quasars because quasars with redshift in this range have similar optical colors as normal stars and are thus difficult to be found in optical sky surveys. A quasar candidate, SDSS J085543.40-001517.7, which was selected by a recently proposed criterion involving near-IR $Y-K$ and optical $g-z$ colors, was identified spectroscopically as a new quasar with redshift of 2.427 by the LAMOST commissioning observation in December 2009 and confirmed by the observation made with the NAOC/Xinglong 2.16m telescope in March 2010. This quasar was not targeted in the SDSS spectroscopic survey because it locates in the stellar locus of the optical color-color diagrams, while it is clearly separated from stars in the $Y-K$ vs. $g-z$ diagram. Comparing with other SDSS quasars we found this new quasar with $i$ magnitude of 16.44 is apparently the brightest one in the redshift range from 2.3 to 2.7. From the spectral properties we derived its central black hole mass as $(1.4\sim3.9) \times 10^{10} M_\odot$ and the bolometric luminosity as $3.7\times 10^{48}$ \ergs, which indicates that this new quasar is intrinsically very bright and belongs to the most luminous quasars in the universe. Our identification supports that quasars in the redshift desert can be found by the quasar selection criterion involving the near-IR colors. More missing quasars are expected to be recovered by the future LAMOST spectroscopic surveys, which is important to the study of the cosmological evolution of quasars at redshift higher than 2.2.

0 citations0 reviewsNo code linkedOpen access
preprint2010arXiv

Eight new quasars discovered by LAMOST in one extragalactic field

We report the discovery of eight new quasars in one extragalactic field (five degree centered at RA=$08^h58^m08.2^s$, Dec=$01^o32'29.7''$) with the LAMOST commissioning observations on December 18, 2009. These quasars, with $i$ magnitudes from 16.44 to 19.34 and redshifts from 0.898 to 2.773, were not identified in the SDSS spectroscopic survey, though six of them with redshifts less than 2.5 were selected as quasar targets in SDSS. Except one source without near-IR $Y$-band data, seven of these eight new quasars meet a newly proposed quasar selection criterion involving both near-IR and optical colors. Two of them were found in the 'redshift desert' for quasars ($z$ from 2.2 to 3), indicating that the new criterion is efficient for recovering the missing quasars with similar optical colors as stars. Although LAMOST met some problems during the commissioning observations, we were still able to identify other 38 known SDSS quasars in this field, with $i$ magnitudes from 16.24 to 19.10 and redshifts from 0.297 to 4.512. Our identifications imply that a substantial fraction of quasars may be missing in the previous quasar surveys. The implication of our results to the future LAMOST quasar survey is discussed.

0 citations0 reviewsNo code linkedOpen access