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      Treating Wavefront Measurement Error in Estimation of Non-Common Path Aberration for Direct Imaging of Exoplanets

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          Abstract

          One of the major difficulties limiting ground-based direct imaging of exoplanets with adaptive optics is quasi-static speckles in the science camera (SC) that obscure the planetary image. These speckles are caused by aberrations, called non-common path aberrations (NCPA), that are not corrected in the adaptive optics loop, and all attempts to subtract them in post-processing have been problematic. The method of Frazin (2013) (F13) uses simultaneous millisecond telemetry from wavefront sensor (WFS) and the SC to estimate the both the NCPA and the exoplanet image in a self-consistent manner. Rodack et al. (2018) proposed correcting for the NCPA in real-time while on-sky using the F13 estimation method, and called this procedure the "Real-Time Frazin Algorithm." The original regression model underlying the F13 method did not account for uncertainty in the WFS measurements, and this cannot be done with standard statistical methodology since these uncertainties manifest themselves in the independent variables (i.e., they cannot be treated as another source of noise in the SC data). Further, simulations show that simply using the noisy wavefront measurements without accounting for their uncertainties leads to estimates of the NCPA with unacceptably large bias. Here, the source of this bias is explained in terms of an "errors in variables" statistical model. Then, the method of F13 is generalized to account for WFS measurement error using a new sequential estimation technique that treats the nonlinear coupling between NCPA, WFS measurements and the error covariance of the WFS measurements. This new technique keeps a running estimate of the NCPA, the exoplanet image and their joint covariance matrix. The sequential implementation of the method should make it computationally efficient enough to be suitable for on-sky correction of the NCPA as well as off-line analysis.

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          Image reconstruction and restoration: overview of common estimation structures and problems

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            Ground-Based Coronagraphy with High Order Adaptive Optics

            We summarize the theory of coronagraphic optics, and identify a dimensionless fine-tuning parameter, F, which we use to describe the Lyot stop size in the natural units of the coronagraphic optical train and the observing wavelength. We then present simulations of coronagraphs matched to adaptive optics (AO) systems on the Calypso 1.2m, Palomar Hale 5m and Gemini 8m telescopes under various atmospheric conditions, and identify useful parameter ranges for AO coronagraphy on these telescopes. Our simulations employ a tapered, high-pass filter in spatial frequency space to mimic the action of adaptive wavefront correction. We test the validity of this representation of AO correction by comparing our simulations with recent K-band data from the 241-channel Palomar Hale AO system and its dedicated PHARO science camera in coronagraphic mode.
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              Statistics of intensity in adaptive-optics images and their usefulness for detection and photometry of exoplanets

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                Author and article information

                Journal
                12 November 2018
                Article
                1811.05096
                20279db3-837e-4a7c-b854-acf25020161b

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                12 pages, no figures
                astro-ph.IM

                Instrumentation & Methods for astrophysics
                Instrumentation & Methods for astrophysics

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