Cunshi Wang
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View article: StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations
StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations Open
The exponential growth of large-scale telescope arrays has boosted time-domain astronomy development but introduced operational bottlenecks, including labor-intensive observation planning, data processing, and real-time decision-making. He…
View article: Unveiling the power of multimodal large language models for radio astronomical image understanding and question answering
Unveiling the power of multimodal large language models for radio astronomical image understanding and question answering Open
Although multimodal large language models (MLLMs) have shown remarkable achievements across various scientific domains, their applications in radio astronomy remain largely unexplored. In this paper, we investigate the potential of MLLMs f…
View article: Artificial Satellite Trails Detection Using U-Net Deep Neural Network and Line Segment Detector Algorithm
Artificial Satellite Trails Detection Using U-Net Deep Neural Network and Line Segment Detector Algorithm Open
With the rapid increase in the number of artificial satellites, astronomical imaging is experiencing growing interference. When these satellites reflect sunlight, they produce streak-like artifacts in photometry images. Such satellite trai…
View article: StarWhisper Telescope: Agent-Based Observation Assistant System to Approach AI Astrophysicist
StarWhisper Telescope: Agent-Based Observation Assistant System to Approach AI Astrophysicist Open
The exponential growth of large-scale telescope arrays has boosted time-domain astronomy but introduced operational bottlenecks, including labor-intensive observation planning, data processing, and real-time decision-making. Here we presen…
View article: The Mini-SiTian Array: First-two-year Operation
The Mini-SiTian Array: First-two-year Operation Open
The SiTian project, designed to utilize 60 telescopes distributed across multiple sites in China, is a next-generation time-domain survey initiative. As a pathfinder for the SiTian project, the Mini-SiTian (MST) has been proposed and imple…
View article: Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification
Deep Learning and Methods Based on Large Language Models Applied to Stellar Light Curve Classification Open
Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, they can be effectively processed to extract astronomical patterns and information. In th…
View article: StarWhisper Telescope: An AI framework for automating end-to-end astronomical observations
StarWhisper Telescope: An AI framework for automating end-to-end astronomical observations Open
The exponential growth of large-scale telescope arrays has boosted time-domain astronomy development but introduced operational bottlenecks, including labor-intensive observation planning, data processing, and real-time decision-making. He…
View article: Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification
Deep Learning and LLM-based Methods Applied to Stellar Lightcurve Classification Open
Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processed to extract astronomical patterns and information. In this…
View article: LightCurve MoE: A Dynamic Sparse Routing Mixture-of-Experts Architecture for Efficient Stellar Light Curve Classification
LightCurve MoE: A Dynamic Sparse Routing Mixture-of-Experts Architecture for Efficient Stellar Light Curve Classification Open
The classification of stellar light curves has become a key task in modern time-domain astronomy, fueled by the rapid growth of data from large-scale surveys such as Kepler and TESS. Although deep learning models have achieved high accurac…
View article: J-PLUS: Support vector regression to measure stellar parameters
J-PLUS: Support vector regression to measure stellar parameters Open
Context. Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral obse…
View article: J-PLUS: Support vector machine applied to STAR-GALAXY-QSO classification
J-PLUS: Support vector machine applied to STAR-GALAXY-QSO classification Open
Context. In modern astronomy, machine learning has proved to be efficient and effective in mining big data from the newest telescopes. Aims. In this study, we construct a supervised machine-learning algorithm to classify the objects in the…
View article: THE BOOTES NETWORK IN THE GRAVITATIONAL WAVE ERA
THE BOOTES NETWORK IN THE GRAVITATIONAL WAVE ERA Open
The Burst Optical Observer and Transient Exploring System (BOOTES) is a world-wide automatic telescope network which aims to repaid follow-up of transient and astrophysical sources in the sky for which the first station was installed in 19…
View article: Machine Learning Applied to STAR-GALAXY-QSO Classification of The Javalambre-Photometric Local Universe Survey
Machine Learning Applied to STAR-GALAXY-QSO Classification of The Javalambre-Photometric Local Universe Survey Open
In modern astronomy, machine learning as an raising realm for data analysis, has proved to be efficient and effective to mine the big data from the newest telescopes. By using support vector machine (SVM), we construct a supervised machine…
View article: Early optical follow-up of the nearby active star DG CVn during its 2014 superflare
Early optical follow-up of the nearby active star DG CVn during its 2014 superflare Open
DG Canum Venaticorum (DG CVn) is a binary system in which one of the components is an M-type dwarf ultrafast rotator, only three of which are known in the solar neighbourhood. Observations of DG CVn by the Swift satellite and several groun…