Overview of AO calibration strategies in the ELT context

The scientific potential of the ELT will rely on the performance of its AO systems that will require to be perfectly calibrated before and during the operations. The actual design of the ELT will provide a constraining environment for the calibration and new strategies have to be developed to overcome these constraints. This will be particularly true concerning the Interaction Matrix of the system with no calibration source upward M4 and moving elements in the telescope. After a brief presentation of the ELT specificities for the calibration, this communication focuses on the different strategies that have already been developed to get/measure the Interaction Matrix of the system, either based on synthetic models or using on-sky measurements. First tests of these methods have been done using numerical simulations for a simple AO system and a proposition for a calibration strategy of the ELT will be presented

Including the pyramid optical gains into analytical models

International audienceFourier-filtering wavefront sensors (WFS), such as the pyramid of Zernike WFS, are shown to be highly sensitive.They are becoming the baseline for future adaptive optics (AO) systems for astronomy. The next generationExtremely Large Telescopes (ELTs) will be equipped with such sensitive WFS. However the main drawback ofthese sensors is a quick loss of linearity when subject to strong turbulence residuals.Two major methods can be identified to simulate the AO point-spread-function (PSF): the end-to-endsimulation and the analytical model. The first one propagates random samples of phase screens through a fullysimulated AO loop, it can thus reproduce fine spatial and temporal effects, inlcuding the WFS non linearities.The second method is based on analytical formulas that provide a quick simulation with a good understanding ofthe AO system (separation of the AO error terms) but require a linear response of the system.We develop here a method to include the non linearities of the WFS into analytical formulas. It consequentlyimproves the accuracy of the simulation and enables to describe with good accuracy Fourier-filtering WFS. We testour method against end-to-end simulations, and derive possible applications for AO system design or performanceestimation

OOPAO: Object Oriented Python Adaptive Optics

International audienceOOPAO: Object Oriented Python Adaptive Optic

PAPYRUS at OHP: Predictive control with reinforcement learning for improved performance

International audiencePAPYRUS at OHP: Predictive control with reinforcement learning for improved performanc

Toward the full control of NCPA with the pyramid wavefront sensor: mastering the optical gains

International audienceThe pyramid wavefront sensor is an asset for an AO system thanks to its sensitivity. However, because itsa nonlinear sensor it comes with operational challenges. A convolutional method and a gain sensing cameraallow to track the optical gains, which encode the sensitivity variations due to the nonlinearities. Tracking andcompensating the optical gains is necessary to perform extreme adaptive optics and to operate the pyramidoff-zero to compensate for the NCPA.This study focuses on the reliability of this method. A numerical twinof the bench PAPYRUS, developed for this study, shows a improvement of the performance by a factor 2.7 onthe Strehl Ratio when compensating for the optical gains. The convolutional method is implemented for thePAPYRUS bench, allowing the first on-sky tracking of optical gains. The next main steps are to compensate forthe optical gains in real-time, then to offset the pyramid in order to optimise fiber-injection, to compensate forNCPA and to provide AO generated dark hole for high-contrast imaging

Toward the full control of NCPA with the pyramid wavefront sensor: mastering the optical gains

International audienceThe pyramid wavefront sensor is an asset for an AO system thanks to its sensitivity. However, because itsa nonlinear sensor it comes with operational challenges. A convolutional method and a gain sensing cameraallow to track the optical gains, which encode the sensitivity variations due to the nonlinearities. Tracking andcompensating the optical gains is necessary to perform extreme adaptive optics and to operate the pyramidoff-zero to compensate for the NCPA.This study focuses on the reliability of this method. A numerical twinof the bench PAPYRUS, developed for this study, shows a improvement of the performance by a factor 2.7 onthe Strehl Ratio when compensating for the optical gains. The convolutional method is implemented for thePAPYRUS bench, allowing the first on-sky tracking of optical gains. The next main steps are to compensate forthe optical gains in real-time, then to offset the pyramid in order to optimise fiber-injection, to compensate forNCPA and to provide AO generated dark hole for high-contrast imaging

Phase A study of the GNAO bench

International audiencePhase A study of the GNAO benc

PAPYRUS: one year of on-sky operations

International audienceThe PAPYRUS adaptive optics (AO) bench has been developed to test and maturate new concepts of wavefrontsensors (WFS), control strategies and dedicated hardware such as cameras and deformable mirrors. The benchwill serve as a pathfinder to the challenging AO systems for the upcoming Extremely Large Telescopes (ELTs).Moreover the bench has already been used as a pedagogical tool to teach adaptive optics to PhD and masterstudents.PAPYRUS is made of a modulated pyramid WFS working in the visible band, an EMCCD wavefront sensingcamera and a 17 × 17 deformable mirror. The bench is installed on the T152 (1.52 m diameter) telescope atObservatoire de Haute Provence (OHP, France) since June 2022. Here we summarise the performance of thebench and the lessons learnt after one year of on-sky operations with the pyramid WF