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. This PSF must be accurately known since it provides crucial information about optical systems for design, characterisation, 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 directly the Fried parameter r0 of the turbulence s strength. This physical parameter is an asset in the PSF model since it can be correlated with external measurements of the r0, such as phase slopes from the AO real time computer (RTC) or site seeing monitoring. Results. We fit our model against endtoend simulated PSFs using OOMAO tool, and against on sky PSFs from the SPHERE ZIMPOL imager and the MUSE integral field spectrometer working in AO narrowfield mode. Our model matches the shape of the AO PSF both in the core and the halo, with a sub 1 percent relative error for simulated and experimental data. We also show that we retrieve the r0 parameter with subcentimeter precision on simulated data. For ZIMPOL data, we show a correlation of 97 percent between our r0 estimation and the RTC estimation. Finally, MUSE allows us to test the spectral dependency of the fitted r0 parameter. It follows the theoretical $λ^{6/5}$ evolution with a standard deviation of 0.3 cm. Evolution of other PSF parameters, such as residual phase variance or aliasing, is also discussed.
We investigate the focal plane wavefront sensing technique, known as Phase Diversity, at the scientific focal plane of a segmented mirror telescope with an adaptive optics (AO) system. We specifically consider an optical system imaging a point source in the context of (i) an artificial source within the telescope structure and (ii) from AO-corrected images of a bright star. From our simulations, we reliably disentangle segmented telescope phasing errors from non-common path aberrations (NCPA) for both a theoretical source and on-sky, AO-corrected images where we have simulated the Keck/NIRC2 s…
AnisoCADO is a Python package for generating images of the point spread function (PSF) for the european extremely large telescope (ELT). The code allows the user to set many of the most important atmospheric and observational parameters that influence the shape and strehl ratio of the resulting PSF, including but not limited to: the atmospheric turbulence profile, the guide star position for a single conjugate adaptive optics (SCAO) solution, differential telescope pupil transmission, etc. Documentation can be found at https://anisocado.readthedocs.io/en/latest/
Modern Giant Segmented Mirror Telescopes (GSMT) like the Extremely Large Telescope (ELT), currently under construction depend heavily on Adaptive Optics (AO) systems to correct for atmospheric turbulence. To be able to correct wider fields of view (FoV), Multi-Conjugate Adaptive Optics (MCAO) systems were introduced, which use multiple guide stars to obtain an almost uniform correction over the FoV. However, a residual blur remains in the astronmical images due to the time delay stemming from the wavefront sensor (WFS) integration time and temporal response of the deformable mirror(s) (DM). Th…
High quality, repeatable point-spread functions are important for science cases like direct exoplanet imaging, high-precision astrometry, and high-resolution spectroscopy of exoplanets. For such demanding applications, the initial on-sky point-spread function delivered by the adaptive optics system can require further optimization to correct unsensed static aberrations and calibration biases. We investigated using the Fast and Furious focal-plane wavefront sensing algorithm as a potential solution. This algorithm uses a simple model of the optical system and focal plane information to measure …
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. 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. We gathered 4812 on-sky PSFs obtained from seven AO systems and used the same fitti…
Astrometric precision and knowledge of the point spread function are key ingredients for a wide range of astrophysical studies including time-delay cosmography in which strongly lensed quasar systems are used to determine the Hubble constant and other cosmological parameters. Astrometric uncertainty on the positions of the multiply-imaged point sources contributes to the overall uncertainty in inferred distances and therefore the Hubble constant. Similarly, knowledge of the wings of the points spread function (PSF) is necessary to disentangle light from the background sources and the foregroun…
Adaptive optics images from the W. M. Keck Observatory have delivered numerous influential scientific results, including detection of multi-system asteroids, the supermassive black hole at the center of the Milky Way, and directly imaged exoplanets. Specifically, the precise and accurate astrometry these images yield was used to measure the mass of the supermassive black hole using orbits of the surrounding star cluster. Despite these successes, one of the major obstacles to improved astrometric measurements is the spatial and temporal variability of the point-spread function delivered by the …
We describe a rapid and direct method for regularizing, post-facto, the point-spread function (PSF) of a telescope or other imaging instrument, across its entire field of view. Imaging instruments in general blur point sources of light by local convolution with a point-spread function that varies slowly across the field of view, due to coma, spherical aberration, and similar effects. It is possible to regularize the PSF in post-processing, producing data with a homogeneous ``effective PSF'' across the entire field of view. In turn, the method enables seamless wide-field astronomical mosaics at…
Images obtained with single-conjugate adaptive optics (AO) show spatial variation of the point spread function (PSF) due to both atmospheric anisoplanatism and instrumental aberrations. The poor knowledge of the PSF across the field of view strongly impacts the ability to take full advantage of AO capabilities. The AIROPA project aims to model these PSF variations for the NIRC2 imager at the Keck Observatory. Here, we present the characterization of the instrumental phase aberrations over the entire NIRC2 field of view and we present a new metric for quantifying the quality of the calibration,…
A Cross-Band (X-ray $\times$ Optical) Periodicity Search for Supermassive Black Hole Binaries: A Null Result and the First Completeness-Corrected Constraint
AIM（天体物理与方法研究所）；CEA（法国原子能和替代能源委员会）；CNRS（法国国家科学研究中心）；Université Paris-Saclay（巴黎萨克雷大学）；Université de Paris（巴黎大学）
In astronomy, upcoming space telescopes with wide-field optical instruments have a spatially varying point spread function (PSF). Specific scientific goals require a high-fidelity estimation of the PSF at target positions where no direct measurement of the PSF is provided. Even though observations of the PSF are available at some positions of the field of view (FOV), they are undersampled, noisy, and integrated into wavelength in the instrument's passband. PSF modeling represents a challenging ill-posed problem, as it requires building a model from degraded observations that can infer a super-…
Towards Autodifferentiable Point Spread Function Modelling for the VLT/ERIS Vortex Coronagraph
STAR Institute, Université de Liège（列日大学STAR研究所）；European Southern Observatory（欧洲南方天文台）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Université Paris-Saclay, Université Paris Cité, CEA, CNRS, AIM（巴黎萨克雷大学、巴黎西岱大学、法国原子能和替代能源委员会、法国国家科学研究中心、天体物理学与信息研究所）；Université Paris-Saclay, CNRS, Institut d’Astrophysique Spatiale（巴黎萨克雷大学、法国国家科学研究中心、空间天体物理研究所）
