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LAMOST helps Gaia to achieve mmag precision in photometry

The ESA Gaia satellite is well known for its remarkable capabilities on astrometric observations. Meanwhile, as a result of getting rid of the earth atmosphere, repeated observations, and other reasons, it also delivers the most precise photometric data ever, with qualities much higher than ground-based telescopes.


Magnitudes and colors play an important role in characterizing stars. If you look at the sky in a clear starry night, you’ll see the relatively red Aldebaran and blue Rigel. Why? The answer is contained in their intrinsic physical properties. Measuring magnitudes and colors precisely helps to find the truth of things like these.


However, in order to cover a wide magnitude range from 6-22 mag, different observing modes were adopted for stars of different brightness during Gaia observations. Besides, the photometric data in the three bands come from different instruments and CCDs. Therefore, magnitude and color dependent systematic errors exist. In order to make full use of the powerful Gaia photometry, such systematic errors have to be corrected precisely.


A recently study work, led by Prof. Haibo Yuan from Beijing Normal University, PhD student Zexi Niu and Prof. Jifeng Liu from National Astronomical Observatories of Chinese Academy of Sciences (NAOC), announced the dedicated color corrections for Gaia Data Release 2 (DR2). The results have been published in The Astrophysical Journal.


The spectroscopy-based stellar color regression method was used, where the relations between the intrinsic colors and physical parameters of stars are the key points. (See Figure1)


By using a sample of about 500,000 stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and Gaia, color correction curves for the F/G/K stars are well derived. With an unprecedented precision of about 1 mmag, systematic trends with the G magnitude are revealed for both G-RP and BP-RP colors in great detail, reflecting changes in instrument configurations. It was successfully eliminated after corrections from these works. (See Figure 2)


"Especially, our work could be beneficial to studies where a high-precision color–color diagram is required, including the estimation of Gaia photometric metallicities, detection of peculiar objects, discrimination between binaries and single stars, and so on," said Zexi Niu, the lead author of these works.


"Our results are beneficial to exploit Gaia’s power on studying stars and the Milky Way to a great extent," said Prof. Yuan, the corresponding author of the research papers.


In addition, another paper of the researchers about the color corrections for Gaia Data Early Release 3 (EDR3) was published in The Astrophysical Journal Letters.



Figure 1: Schematic illustration of the spectroscopy-based stellar color regression method. (Credit: ZexiNiu)



Figure2: Color residuals versus the G magnitudes of the Gaia DR2 published data (left) and the data after corrections provided by this work (right). (Credit: Zexi Niu)


The paper can be accessed at https://doi.org/10.3847/1538-4357/abdbac.