We propose a data reduction approach called global optimization-based reference star differential imaging (G-RDI), which can be used for exoplanet imaging survey, where large numbers of target stars from the… Click to show full abstract
We propose a data reduction approach called global optimization-based reference star differential imaging (G-RDI), which can be used for exoplanet imaging survey, where large numbers of target stars from the same young stellar association are imaged and where no field rotation is needed. One of the unique features of our G-RDI is that we select reference stars from other scientific target stars in the same stellar association to optimize for high-contrast imaging with a target star, which maximizes the observational efficiency and also delivers good performance to remove the speckle noise so that high contrast is achievable even at a small inner working angle (IWA) to the host star of being imaged. We proposed the G-RDI that is optimized for high-contrast exoplanet imaging at a small IWA and to provide a contrast that is significantly better than the current reference star differential imaging (RDI) method. In addition, we also propose the use of multiple reference stars and found that our G-RDI can further deliver better performance in that case. The result was compared with other exoplanet data reduction techniques, including the traditional RDI, and it indicated that our G-RDI with two reference stars can significantly improve the contrast performance at a small IWA with a high observational efficiency – two critical features that current data reduction techniques cannot offer. This approach could be used with both equatorial and alt-azimuth mount telescopes, and provides a new option for future exoplanet imaging surveys with high observational efficiency at a small IWA.
               
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