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Minimization of non common path aberrations at the Palomar telescope using a self-coherent camera

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 نشر من قبل Raphael Galicher Dr.
 تاريخ النشر 2019
  مجال البحث فيزياء
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The two main advantages of exoplanet imaging are the discovery of objects in the outer part of stellar systems -- constraining models of planet formation --, and its ability to spectrally characterize the planets -- information on their atmosphere. It is however challenging because exoplanets are up to 1e10 times fainter than their star and separated by a fraction of arcsecond. Current instruments like SPHERE/VLT or GPI/Gemini detect young and massive planets because they are limited by non-common path aberrations (NCPA) that are not corrected by the adaptive optics system. To probe fainter exoplanets, new instruments capable of minimizing the NCPA is needed. One solution is the self-coherent camera (SCC) focal plane wavefront sensor, whose performance was demonstrated in laboratory attenuating the starlight by factors up to several 1e8 in space-like conditions at angular separations down to 2L/D. In this paper, we demonstrate the SCC on the sky for the first time. We installed an SCC on the stellar double coronagraph (SDC) instrument at the Hale telescope. We used an internal source to minimize the NCPA that limited the vortex coronagraph performance. We then compared to the standard procedure used at Palomar. On internal source, we demonstrated that the SCC improves the coronagraphic detection limit by a factor between 4 and 20 between 1.5 and 5L/D. Using this SCC calibration, the on-sky contrast is improved by a factor of 5 between 2 and 4L/D. These results prove the ability of the SCC to be implemented in an existing instrument. This paper highlights two interests of the self-coherent camera. First, the SCC can minimize the speckle intensity in the field of view especially the ones that are very close to the star where many exoplanets are to be discovered. Then, the SCC has a 100% efficiency with science time as each image can be used for both science and NCPA minimization.



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