Successful application of PSF-R techniques to the case of the globular cluster NGC 6121 (M 4)

Context. Precise photometric and astrometric measurements on astronomical images require an accurate knowledge of the point spread function (PSF). When the PSF cannot be modelled directly from the image, PSF-reconstruction techniques become the only viable solution. So far, however, their performance on real observations has rarely been quantified. Aims. In this Letter, we test the performance of a novel hybrid technique, called PRIME, on Adaptive Optics-assisted SPHERE/ZIMPOL observations of the Galactic globular cluster NGC 6121. Methods. PRIME couples PSF-reconstruction techniques, based on control-loop data and direct image fitting performed on the only bright point-like source available in the field of view of the ZIMPOL exposures, with the aim of building the PSF model. Results. By exploiting this model, the magnitudes and positions of the stars in the field can be measured with an unprecedented precision, which surpasses that obtained by more standard methods by at least a factor of four for on-axis stars and by up to a factor of two on fainter, off-axis stars. Conclusions. Our results demonstrate the power of PRIME in recovering precise magnitudes and positions when the information directly coming from astronomical images is limited to only a few point-like sources and, thus, paving the way for a proper analysis of future Extremely Large Telescope observations of sparse stellar fields or individual extragalactic objects

Performance characterization and near-realtime monitoring of MUSE adaptive optics modes at Paranal

The Multi Unit Spectroscopic Explorer (MUSE) is an integral field spectrograph on the Very Large Telescope Unit Telescope 4, capable of laser guide star assisted and tomographic adaptive optics using the GALACSI module. Its observing capabilities include a wide field (1 square arcmin), ground layer AO mode (WFM-AO) and a narrow field (7.5"x7.5"), laser tomography AO mode (NFM-AO). The latter has had several upgrades in the 4 years since commissioning, including an optimisation of the control matrices for the AO system and a new sub-electron noise detector for its infra-red low order wavefront sensor. We set out to quantify the NFM-AO system performance by analysing $\sim$230 spectrophotometric standard star observations taken over the last 3 years. To this end we expand upon previous work, designed to facilitate analysis of the WFM-AO system performance. We briefly describe the framework that will provide a user friendly, semi-automated way for system performance monitoring during science operations. We provide the results of our performance analysis, chiefly through the measured Strehl ratio and full width at half maximum (FWHM) of the core of the point spread function (PSF) using two PSF models, and correlations with atmospheric conditions. These results will feed into a range of applications, including providing a more accurate prediction of the system performance as implemented in the exposure time calculator, and the associated optimization of the scientific output for a given set of limiting atmospheric conditions.Comment: SPIE proceedings (2022), Observatory Operations: Strategies, Processes, and Systems I

MAVIS: The adaptive optics module feasibility study

The Adaptive Optics Module of MAVIS is a self-contained MCAO module, which delivers a corrected FoV to the postfocal scientific instruments, in the visible. The module aims to exploit the full potential of the ESO VLT UT4 Adaptive Optics Facility, which is composed of the high spatial frequency deformable secondary mirror and the laser guide stars launching and control systems. During the MAVIS Phase A, we evaluated, with the support of simulations and analysis at different levels, the main terms of the error budgets aiming at estimating the realistic AOM performance. After introducing the current opto-mechanical design and AO scheme of the AOM, we here present the standard wavefront error budget and the other budgets, including manufacturing, alignment of the module, thermal behavior and noncommon path aberrations, together with the contribution of the upstream telescope system

Improved prior for adaptive optics point spread function estimation from science images: Application for deconvolution

Context . Access to knowledge of the point spread function (PSF) of adaptive optics(AO)-assisted observations is still a major limitation when processing AO data. This limitation is particularly important when image analysis requires the use of deconvolution methods. As the PSF is a complex and time-varying function, reference PSFs acquired on calibration stars before or after the scientific observation can be too different from the actual PSF of the observation to be used for deconvolution, and lead to artefacts in the final image. Aims . We improved the existing PSF-estimation method based on the so-called marginal approach by enhancing the object prior in order to make it more robust and suitable for observations of resolved extended objects. Methods . Our process is based on a two-step blind deconvolution approach from the literature. The first step consists of PSF estimation from the science image. For this, we made use of an analytical PSF model, whose parameters are estimated based on a marginal algorithm. This PSF was then used for deconvolution. In this study, we first investigated the requirements in terms of PSF parameter knowledge to obtain an accurate and yet resilient deconvolution process using simulations. We show that current marginal algorithms do not provide the required level of accuracy, especially in the presence of small objects. Therefore, we modified the marginal algorithm by providing a new model for object description, leading to an improved estimation of the required PSF parameters. Results . Our method fulfills the deconvolution requirement with realistic system configurations and different classes of Solar System objects in simulations. Finally, we validate our method by performing blind deconvolution with SPHERE/ZIMPOL observations of the Kleopatra asteroid

PRIME: Psf Reconstruction and Identification for Multiple sources characterization Enhancement. Application to Keck NIRC2 imager

International audienceIn order to enhance accuracy of astrophysical estimates obtained on Adaptive-optics (AO) images, such as photom-etry and astrometry, we investigate a new concept to constrain the Point Spread Function (PSF) model called PSF Reconstruction and Identification for Multi-sources characterization Enhancement (PRIME), that handles jointly the science image and the AO control loop data. We present in this paper the concept of PRIME and validate it on Keck II telescope NIRC2 images. We show that by calibrating the PSF model over the scientific image, PSF reconstruction achieves 1% and 3 mas of accuracy on respectively the Strehl-ratio and the PSF full width at half maximum. We show on NIRC2 binary images that PRIME is sufficiently robust to noise to retain photometry and astrometry precision below 0.005 mag and 100µas on a mH = 14 mag object. Finally, we also validate that PRIME performs a PSF calibration on the triple system Gl569BAB which provides a separation of 66.73±1.02 and a differential photometry of 0.538±0.048, compared to the reference values obtained with the extracted PSF which are 66.76 mas ± 0.94 and 0.532 mag ± 0.041

Pushing point-spread function reconstruction to the next level: application to SPHERE/ZIMPOL

International audiencePoint spread function (PSF) reconstruction (PSF-R) is a well established technique to determine reliably and accurately the PSF from Adaptive Optics (AO) control loop data. We have successfully applied this technique to improve the precision on photometry and astrometry to observation of NGC6121 obtained with SPHERE/ZIMPOL as it will be presented in a forthcoming letter. Firstly, we present the methodology we followed to reconstruct the PSF combining pupil-plane and focal-plane measurements using using our PSF-R method PRIME (Beltramo-Martin et al. 2019), with upgrade of both the model and best-fitting steps compared to previous papers. Secondly, we highlight that PRIME allows to maintain the PSF fitting residual below 0.2% over 2 hours of observation and using only 30 s of AO telemetry, which may have important consequences for telemetry storage for PSF-R purpose on future 30-40 m class telescopes. Finally, we deploy PRIME in a more realistic regime using faint stars so as to identify the precision needed on the initial guess parameters to ensure the convergence towards the optimal solution

PRIME ::PSF reconstruction and identification for multiple-source characterization enhancement – application to Keck NIRC2 imager

In order to enhance the scientific exploitation of adaptive optics (AO)-assisted observations, we investigate a novel hybrid concept to improve the parametric estimation of point spread function (PSF) called PSF Reconstruction and Identification for Multiple-source characterization Enhancement (PRIME). PRIME uses both focal and pupil-plane measurements to estimate jointly the model parameters related to the atmosphere [C2n(h)⁠, seeing] and the AO system (e.g. optical gains and residual low-order errors). Photometry and astrometry are provided as by-products. The parametric model in use is flexible enough to be scaled with field location and wavelength, making it a proper choice for optimized on-axis and off-axis data-reduction across the spectrum. Here, we present the methodology and validate PRIME on engineering and binary Keck II telescope NIRC2 images. We also present applications of PSF model parameters retrieval using PRIME: (i) calibrate the PSF model for observations void of stars on the acquired images, i.e. optimize the PSF reconstruction process, (ii) update the AO error breakdown mutually constrained by the telemetry and the images in order to speculate on the origin of the missing error terms and evaluate their magnitude, and (iii) measure photometry and astrometry with an application to the triple system Gl569 images