Abstract

Context.Adaptive optics (AO) systems greatly increase the resolution of large telescopes, but produce complex point spread function (PSF) shapes, varying in time and across the field of view. The PSF must be accurately known since it provides crucial information about optical systems for design, characterization, diagnostics, and image post-processing.Aims.We develop here a model of the AO long-exposure PSF, adapted to various seeing conditions and any AO system. This model is made to match accurately both the core of the PSF and its turbulent halo.Methods.The PSF model we develop is based on a parsimonious parameterization of the phase power spectral density, with only five parameters to describe circularly symmetric PSFs and seven parameters for asymmetrical ones. Moreover, one of the parameters is the Fried parameterr0of the turbulence’s strength. This physical parameter is an asset in the PSF model since it can be correlated with external measurements of ther0, such as phase slopes from the AO real time computer (RTC) or site seeing monitoring.Results.We fit our model against end-to-end simulated PSFs using the OOMAO tool, and against on-sky PSFs from the SPHERE/ZIMPOL imager and the MUSE integral field spectrometer working in AO narrow-field mode. Our model matches the shape of the AO PSF both in the core and the halo, with a relative error smaller than 1% for simulated and experimental data. We also show that we retrieve ther0parameter with sub-centimeter precision on simulated data. For ZIMPOL data, we show a correlation of 97% between ourr0estimation and the RTC estimation. Finally, MUSE allows us to test the spectral dependency of the fittedr0parameter. It follows the theoreticalλ6/5evolution with a standard deviation of 0.3 cm. Evolution of other PSF parameters, such as residual phase variance or aliasing, is also discussed.

Highlights

  • Optical systems suffer from aberrations and diffraction effects that limit their imaging performance

  • One of the parameters is the Fried parameter r0 of the turbulence’s strength. This physical parameter is an asset in the point spread function (PSF) model since it can be correlated with external measurements of the r0, such as phase slopes from the Adaptive optics (AO) real time computer (RTC) or site seeing monitoring

  • We fit our model against end-to-end simulated PSFs using the Object-Oriented Matlab Adaptive Optics (OOMAO) tool, and against on-sky PSFs from the Spectro Polarimetric High-contrast Exoplanet REsearch (SPHERE)/ZIMPOL imager and the MUSE integral field spectrometer working in AO narrow-field mode

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Summary

Introduction

Optical systems suffer from aberrations and diffraction effects that limit their imaging performance. The AO correction is limited by technical issues such as sensor noise, limited number of actuators, or loop delay (Martin et al 2017; Rigaut et al 1998) This results in a peculiar shape of the PSF made of a sharp peak due to. The model must have as few parameters as possible without damaging its versatility or accuracy. To the best of our knowledge, these PSF models rely only on mathematical parameters without direct physical meaning or units. We propose a long-exposure PSF model for AO-corrected telescopes that describes accurately the shape of the PSF; this model is made of a small number of parameters with physical meaning whenever possible.

Description of the PSF model
Review of the usual Moffat PSF model
Image formation theory
Parameterization of the phase PSD
PSF fitting method
OOMAO end-to-end simulations
AO residual variance σ2AO estimation
Constant C estimation
High performance imager ZIMPOL
MUSE integral field spectrograph
Findings
Conclusions
Full Text
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