Data characterization using artificial-star tests: performance evaluation - Astrophysics > Instrumentation and Methods for AstrophysicsReport as inadecuate




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Abstract: Traditional artificial-star tests are widely applied to photometry in crowdedstellar fields. However, to obtain reliable binary fractions and theiruncertainties of remote, dense, and rich star clusters, one needs to recoverhuge numbers of artificial stars. Hence, this will consume much computationtime for data reduction of the images to which the artificial stars must beadded. In this paper, we present a new method applicable to data setscharacterized by stable, well-defined point-spread functions, in which we addartificial stars to the retrieved-data catalog instead of the raw images.Taking the young Large Magellanic Cloud cluster NGC 1818 as an example, wecompare results from both methods and show that they are equivalent, while ournew method saves significant computational time.



Author: Yi Hu, Licai Deng, Richard de Grijs, Qiang Liu

Source: https://arxiv.org/







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