Data Characterization Using Artificial-Star Tests: Performance Evaluation

@article{Hu2011DataCU,
  title={Data Characterization Using Artificial-Star Tests: Performance Evaluation},
  author={Y. Hu and L. Deng and R. Grijs and Q. Liu},
  journal={Publications of the Astronomical Society of the Pacific},
  year={2011},
  volume={123},
  pages={107-112}
}
  • Y. Hu, L. Deng, +1 author Q. Liu
  • Published 2011
  • Physics
  • Publications of the Astronomical Society of the Pacific
  • Traditional artificial-star tests are widely applied to photometry in crowded stellar fields. However, to obtain reliable binary fractions (and their uncertainties) of remote, dense, and rich star clusters, one needs to recover huge numbers of artificial stars. Hence, this will consume much computation time for data reduction of the images to which the artificial stars must be added. In this article, we present a new method applicable to data sets characterized by stable, well-defined, point… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-5 OF 5 REFERENCES
    The Luminosity function and color - magnitude diagram of the globular cluster M12
    • 21
    • PDF
    The Binary Fraction of the Young Cluster NGC 1818 in the Large Magellanic Cloud
    • 22
    • PDF
    Photometry of the Globular Cluster NGC 5466: Red Giants and Blue Stragglers
    • 11
    • PDF
    3.— Standard deviations of the photometric uncertainties as a function of stellar magnitude (cf
    • 2010