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Lin Jiaben

Publications and source records attributed to Lin Jiaben.

3 recordsLinked to original sources

JW-FD: A Long Horizon Multimodal Solar Flare Forecasting Dataset

Solar flares drive severe space weather hazards, and forecasting their occurrence remains a central challenge for both heliophysics and operational space weather services. Data driven methods require long horizon datasets in which images, magnetic features, and flare labels are coregistered in space and time. We present JW-FD (JW-Flare Dataset), a 15 year multimodal release spanning 1 January 2011 through 31 December 2025, constructed from SDO/HMI line of sight magnetograms, NOAA Solar Region Summary reports, and NOAA X-ray flare event lists. The dataset comprises 3,064 independent active regions and 1,991,247 coregistered magnetogram crops, together with FITS, PNG, CSV, and MP4 modalities. Each sample provides 29 magnetic features linked to configurable flare labels under a strict pre-eruption window spanning seven forecast horizons and four GOES intensity thresholds. An 8:1:1 split at the active region level is adopted to prevent temporal leakage between partitions. PNG branches are released at six magnetic saturation thresholds, and internal Transformer experiments on >=C1.0 forecasting suggest Bth=1000 G as a preliminary default, although the optimal saturation is model and task dependent. The open source construction pipeline is available at https://github.com/Xiaoxuan-1/JW-FD.

astro-ph.SR

Scientific-Intention Driven Embodied Intelligent Solar Telescope: Conceptual Design

Artificial Intelligence (AI) is profoundly transforming the paradigms of scientific research. Cutting-edge technologies such as Large Language Models (LLMs) and embodied intelligence are continuously pushing the boundaries of scientific instrumentation. Against this backdrop, this paper proposes a novel conceptual system: the Scientific-Intention Driven Embodied Intelligent Solar Telescope (SIDEST). The system is designed with three core layers to achieve three types of intelligent scientific research closed loops. First, the Scientific Intent Research and Demonstration Layer parses the research objectives and intents of scientists (e.g., solar physicists) through natural language interaction, achieving a closed loop for the generation and optimization of executable observation plans aligned with scientific intent via in-depth research. Subsequently, the Observation Realization Layer schedules embodied intelligent solar telescopes to implement a closed loop for the execution of scientific observation plans. Finally, the Evaluation and Evolution Layer coordinates intelligent agents for data processing and scientific analysis to analyze observation data, generate research reports, and iteratively optimize observation strategies and model methods based on results, thereby realizing a self-evolving closed loop for the entire system. During the research process, we constructed a minimal prototype system based on a precision temperature control device for solar telescope birefringent filters to validate the core principles of SIDEST. This prototype successfully implemented all key steps of intention-driven automated research, demonstrating the feasibility of the technical pathways for the three types of intelligent research closed loops. SIDEST redefines telescopes through cutting-edge AI methods.

astro-ph.IM

Dispersal of G-band bright points at different longitudinal magnetic field strengths

G-band bright points (GBPs) are thought to be the foot-points of magnetic flux tubes. The aim of this paper is to investigate the relation between the diffusion regimes of GBPs and the associated longitudinal magnetic field strengths. Two high resolution observations of different magnetized environments were acquired with the Hinode/Solar Optical Telescope. Each observation was recorded simultaneously with G-band filtergrams and Narrow-band Filter Imager (NFI) Stokes I and V images. GBPs are identified and tracked automatically, and then categorized into several groups by their longitudinal magnetic field strengths, which are extracted from the calibrated NFI magnetograms using a point-by-point method. The Lagrangian approach and the distribution of diffusion indices approach are adopted separately to explore the diffusion regime of GBPs for each group. It is found that the values of diffusion index and diffusion coefficient both decrease exponentially with the increasing longitudinal magnetic field strengths whichever approach is used. The empirical formulas deduced from the fitting equations are proposed to describe these relations. Stronger elements tend to diffuse more slowly than weak elements, independently of the magnetic flux of the surrounding medium. This may be because the magnetic energy of stronger elements is not negligible compared with the kinetic energy of the gas, and therefore the flows cannot perturb them so easily.Yang

astro-ph.SR