Analytical expression of long-exposure adaptive-optics-corrected coronagraphic image. First application to exoplanet...

Area of Science:

• Astronomy and Astrophysics
• Optical Engineering

Background:

• Adaptive optics (AO) systems correct for atmospheric turbulence in astronomical imaging.
• Coronagraphy is crucial for detecting faint objects like exoplanets by suppressing starlight.
• Existing models often simplify or omit key factors affecting image quality.

Purpose of the Study:

• To derive a comprehensive analytical model for long-exposure star images in AO-corrected coronagraphy.
• To validate the model against simulations and compare it with existing coronagraph types.
• To assess the impact of model parameters on exoplanet detectability and introduce an inversion method.

Main Methods:

• Development of an analytical model incorporating static aberrations and turbulence residuals.
• Validation through simulations using the SPHERE instrument's parameters.
• Comparison with a simulated four-quadrant phase-mask coronagraph.
• Sensitivity analysis of model parameters and development of a preliminary inversion method.

Main Results:

• The analytical model accurately represents AO-corrected coronagraphic imaging.
• The model's sensitivity to miscalibration and aberrations was quantified, impacting exoplanet detection.
• A novel inversion method demonstrated a two-orders-of-magnitude increase in planet detectability from a single image.

Conclusions:

• The derived analytical model provides a powerful tool for coronagraphic imaging analysis.
• The model enhances understanding of factors limiting exoplanet detection.
• Potential applications include exoplanet direct detection and circumstellar disk observation.