YFYue-Dong Fang

Yue-Dong Fang

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Yue-Dong Fang has a total of 33 co-authors. Here are the top co-authors by number of shared publications:

  • De-Zi Liu

    South-Western Institute for Astronomy Research, Yunnan University, Kunming 650500, China

    2 shared publications
  • Guo-Liang Li

    Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China

    2 shared publications
  • Jing Tang

    National Astronomical Observatories, Chinese Academy of Sciences, Beijing 100101, China

    2 shared publications
  • Jing-Tian Xian

    Space Optics Department, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

    2 shared publications
  • Lei Wang

    Purple Mountain Observatory, Chinese Academy of Sciences, Nanjing 210023, China

    2 shared publications
  • Lin Nie

    Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China

    2 shared publications

Latest Publications

  • Top Cited Papers

    Mock Observations for the CSST Mission: Main Surveys–An Overview of Framework and Simulation Suite

    by Cheng-Liang Wei, Guo-Liang Li, Yue-Dong Fang, Xin Zhang, Yu Luo, Hao Tian, De-Zi Liu, Xian-Ming Meng, Zhang Ban, Xiao-Bo Li, et al.

    The Chinese Space Station Survey Telescope (CSST) is a flagship space-based observatory. Its main survey camera is designed to conduct high spatial resolution near-ultraviolet to near-infrared imaging and low-resolution spectroscopic surveys. To maximize the scientific output of CSST, we have developed a comprehensive, high-fidelity simulation pipeline for reproducing both imaging and spectroscopic observations. This paper presents an overview of the simulation framework, detailing its implementation and components. Built upon the GalSim package and incorporating the latest CSST instrumental specifications, our pipeline generates pixel-level mock observations that closely replicate the expected instrumental and observational conditions. The simulation suite integrates realistic astrophysical object catalogs, instrumental effects, point-spread function modeling, and observational noises to produce accurate synthetic data. We describe the key processing stages of the simulation, from constructing the input object catalogs to modeling the telescope optics and detector responses. Furthermore, we introduce the most recent release of simulated datasets, which provide a crucial testbed for data processing pipeline developments, calibration strategies, and scientific analyses, ensuring that CSST will meet its stringent requirements. Our pipeline serves as a vital tool for optimizing CSST main survey strategies and ensuring robust cosmological measurements.


  • Open Access

    Mock Observations for the CSST Mission: Main Surveys--An Overview of Framework and Simulation Suite

    by Cheng-Liang Wei, Guo-Liang Li, Yue-Dong Fang, Xin Zhang, Yu Luo, Hao Tian, De-Zi Liu, Xian-Ming Meng, Zhang Ban, Xiao-Bo Li, et al.

    The Chinese Space Station Survey Telescope (CSST) is a flagship space-based observatory. Its main survey camera is designed to conduct high spatial resolution near-ultraviolet to near-infrared imaging and low-resolution spectroscopic surveys. To maximize the scientific output of CSST, we have developed a comprehensive, high-fidelity simulation pipeline for reproducing both imaging and spectroscopic observations. This paper presents an overview of the simulation framework, detailing its implementation and components. Built upon the GalSim package and incorporating the latest CSST instrumental specifications, our pipeline generates pixel-level mock observations that closely replicate the expected instrumental and observational conditions. The simulation suite integrates realistic astrophysical object catalogs, instrumental effects, point spread function (PSF) modeling, and observational noises to produce accurate synthetic data. We describe the key processing stages of the simulation, from constructing the input object catalogs to modeling the telescope optics and detector responses. Furthermore, we introduce the most recent release of simulated datasets, which provide a crucial testbed for data processing pipeline developments, calibration strategies, and scientific analyses, ensuring that CSST will meet its stringent requirements. Our pipeline serves as a vital tool for optimizing CSST main survey strategies and ensuring robust cosmological measurements.