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    This study addresses quasi-static speckles (QSSs) that hinder exoplanet imaging by developing regression methods to simultaneously estimate non-common path aberrations (NCPAs) and exoplanet images. The research details ideal, naive, and bias-corrected estimators for improved high-contrast imaging.

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    Area of Science:

    • Astronomy
    • Astrophysics
    • Optical Engineering

    Background:

    • Directly imaging exoplanets and protoplanetary disks is challenged by quasi-static speckles (QSSs).
    • QSSs originate from uncorrected non-common path aberrations (NCPAs) in adaptive optics (AO) systems.
    • Distinguishing QSSs from faint exoplanets requires high-precision contrast, a significant hurdle in current technology.

    Purpose of the Study:

    • To develop and present regression methods for simultaneously estimating NCPAs and exoplanet images.
    • To provide regression equations for ideal, naive, and bias-corrected estimators.
    • To offer a technical discussion supporting the proposed regression techniques for high-contrast imaging.

    Main Methods:

    • Utilizing simultaneous millisecond telemetry from wavefront sensors (WFS) and science cameras.
    • Employing regression schemes to jointly estimate NCPAs and exoplanet images from AO residual (AOR) wavefront data.
    • Comparing three estimators: ideal (non-physical benchmark), naive (prone to bias), and bias-corrected (accounts for AOR errors).

    Main Results:

    • The study details the regression equations for the ideal, naive, and bias-corrected estimators.
    • Simulations in Part I demonstrated the performance of these estimators in joint regression.
    • The naive estimator can provide useful NCPA estimates, while the bias-corrected estimator requires knowledge of AOR error distributions.

    Conclusions:

    • Simultaneous WFS and science camera telemetry can be leveraged to estimate NCPAs and exoplanet images.
    • The presented regression techniques offer pathways to mitigate QSSs and improve high-contrast exoplanet detection.
    • Further development of bias-corrected estimators is crucial for accurate exoplanet imaging applications.