Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

Wagner, Roland; Hofer, Christoph; Ramlau, Ronny

doi:10.1117/1.jatis.4.4.049003

Cited by 12 publications

(9 citation statements)

References 48 publications

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“…[28,29] The need to include the statistical properties of the AO residual wavefronts has long been recognized in the literature on PSF reconstruction. [30][31][32][33] In the authors' view, the direct imaging of exoplanets has much in common with a completely different observational astronomy problem: the detection of gravitation waves with the LIGO experiment. The precision underlying the success of LIGO has depended on removing systematic effects where possible, modeling them when not possible, and state-of-the art statistical analysis.…”

Section: Discussionmentioning

confidence: 99%

Millisecond exoplanet imaging: II. regression equations and technical discussion

Frazin

Rodack

2021

J. Opt. Soc. Am. A

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The leading difficulty in achieving the contrast necessary to directly image exoplanets and associated structures (e.g., protoplanetary disks) at wavelengths ranging from the visible to the infrared are quasistatic speckles, and they are hard to distinguish from planets at the necessary level of precision. The source of the quasi-static speckles is hardware aberrations that are not compensated by the adaptive optics (AO) system. These aberrations are called non-common path aberrations (NCPA) by the community. In 2013, Frazin showed how, in principle, simultaneous millisecond (ms) telemetry from the wavefront sensor (WFS) and the science camera behind a stellar coronagraph can be used as input into a regression scheme that simultaneously and self-consistently estimates the NCPA and the sought-after image of the planetary system (the exoplanet image). The physical principle underlying the regression method is rather simple: the wavefronts, which are measured by the WFS, modulate the speckles caused by the NCPA and therefore can be used as probes of the optical system. The simulations in the Part I article provide results on the joint regression on the NCPA and the exoplanet image from three different methods, called the ideal, the naïve, and the bias-corrected estimators. The ideal estimator is not physically realizable but is a useful as a benchmark for simulation studies, but the other two are, at least in principle. This article provides the regression equations for all three of these estimators as well as a supporting technical discussion. Briefly, the naïve estimator simply uses the noisy WFS measurements without any attempt to account for the errors, and the bias-corrected estimator uses statistical knowledge of the wavefronts to treat errors in the WFS measurements.

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Section: Discussionmentioning

confidence: 99%

Millisecond exoplanet imaging: II. regression equations and technical discussion

Frazin

Rodack

2021

J. Opt. Soc. Am. A

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“…where D is the structure function of the residual incoming phase (i.e., a time average of the spatial correlation 14 ) and, thus, wavelength dependent, and OTF tel is the OTF of the telescope computed from the pupil mask. D is split into two components that are independent as they describe the part corrected by the AO system, D k (lower order structure function), and the part perpendicular to the AO corrected one, D ⊥ (higher order structure function).…”

Section: Psf-r Methodsmentioning

confidence: 99%

“…As detailed in Ref. 14, the adopted method takes as input the reconstructed residual phases φ REC,t , which are recovered from the applied updates of the deformable mirror, to compute D REC . Any WFS-specific issues have to be solved already when setting up the AO system control algorithm.…”

Section: Psf-r Methodsmentioning

confidence: 99%

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Point spread function reconstruction for SOUL + LUCI LBT data

Simioni

Arcidiacono

Wagner

et al. 2022

J. Astron. Telesc. Instrum. Syst.

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Here, we present the status of an ongoing project aimed at developing a point spread function (PSF) reconstruction software for adaptive optics (AO) observations. In particular, we test for the first time the implementation of pyramid wave-front sensor data on our algorithms. As a first step in assessing its reliability, we applied the software to bright, on-axis, point-like sources using two independent sets of observations, acquired with the single-conjugated AO upgrade for the Large Binocular Telescope. Using only telemetry data, we reconstructed the PSF by carefully calibrating the instrument response. The accuracy of the results has been first evaluated using the classical metric: specifically, the reconstructed PSFs differ from the observed ones by <2% in Strehl ratio and 4.5% in full-width at half maximum. Moreover, the recovered encircled energy associated with the PSF core is accurate at 4% level in the worst case. The accuracy of the reconstructed PSFs has then been evaluated by considering an idealized scientific test-case consisting in the measurements of the morphological parameters of a compact galaxy. In the future, our project will include the analysis of anisoplanatism, low signal-to-noise ratio regimes, and the application to multi-conjugated AO observations.

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“…Nevertheless, the PSF is not systematically straightforward to determine from the focal-plane image, particularly for observations made with a small field of view (FOV), or of extended objects, crowded populations or with a low signal-to-noise ratio (S/N). Alternative methods exist, such as PSF reconstruction (Beltramo-Martin et al 2019b,a;Wagner et al 2018;Gilles et al 2018;Ragland et al 2018;Martin et al 2016a;Ragland et al 2016;Jolissaint et al 2015;Exposito 2014;Clénet et al 2008;Gendron et al 2006;Veran et al 1997), which is potentially very accurate (1% error level). However, this process lacks science verification and requires years to be fully implemented and op-erational as a stand-alone pipeline.…”

Section: Introductionmentioning

confidence: 99%

Joint estimation of atmospheric and instrumental defects using a parsimonious point spread function model

Beltramo-Martin

Fétick

Neichel

et al. 2020

A&A

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Context. Modeling the optical point spread function (PSF) is particularly challenging for adaptive optics (AO)-assisted observations owing to the its complex shape and spatial variations. Aims. We aim to (i) exhaustively demonstrate the accuracy of a recent analytical model from comparison with a large sample of imaged PSFs, (ii) assess the conditions for which the model is optimal, and (iii) unleash the strength of this framework to enable the joint estimation of atmospheric parameters, AO performance and static aberrations. Methods. We gathered 4812 on-sky PSFs obtained from seven AO systems and used the same fitting algorithm to test the model on various AO PSFs and diagnose AO performance from the model outputs. Finally, we highlight how this framework enables the characterization of the so-called low wind effect on the Spectro-Polarimetic High contrast imager for Exoplanets REsearch (LWE; SPHERE) instrument and piston cophasing errors on the Keck II telescope. Results. Over 4812 PSFs, the model reaches down to 4% of error on both the Strehl-ratio (SR) and full width at half maximum (FWHM). We particularly illustrate that the estimation of the Fried’s parameter, which is one of the model parameters, is consistent with known seeing statistics and follows expected trends in wavelength using the Multi Unit Spectroscopic Explorer instrument (λ6/5) and field (no variations) from Gemini South Adaptive Optics Imager images with a standard deviation of 0.4 cm. Finally, we show that we can retrieve a combination of differential piston, tip, and tilt modes introduced by the LWE that compares to ZELDA measurements, as well as segment piston errors from the Keck II telescope and particularly the stair mode that has already been revealed from previous studies. Conclusions. This model matches all types of AO PSFs at the level of 4% error and can be used for AO diagnosis, post-processing, and wavefront sensing purposes.

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Point spread function reconstruction for single-conjugate adaptive optics on extremely large telescopes

Cited by 12 publications

References 48 publications

Millisecond exoplanet imaging: II. regression equations and technical discussion

Millisecond exoplanet imaging: II. regression equations and technical discussion

Point spread function reconstruction for SOUL + LUCI LBT data

Joint estimation of atmospheric and instrumental defects using a parsimonious point spread function model

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