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MICADO is the ELT first light instrument, an imager working at the diffraction limit of the telescope thanks to two adaptive optics (AO) modes: a single conjugate one (SCAO), available at the instrument first light and developed by the MICADO consortium, and a multi conjugate one (MCAO), developed by the MORFEO consortium.
This contribution presents an overview of the SCAO module while MICADO and its SCAO are in the last phase of their final design review. We focus on the SCAO architecture choices and present the final design of the SCAO subsystems: the Green Doughnut structure, the SCAO wavefront sensor, the SCAO calibration unit, the SCAO ICS (i.e. AOCS) and the SCAO RTC. We also present the SCAO global performance in terms of AO correction, obtained from an error budget that includes contributors estimated from AO end-to-end simulations as well as instrumental contributors. Finally, we present the current SCAO subsystems prototyping and the main milestones of the SCAO AIT plan.
In the context of the European Southern Observatory (ESO) Extremely Large Telescope (ELT), MICADO will be the first light near infrared imager planned to be on sky in 2027. The AO system for MICADO includes a Single Conjugate AO (SCAO) mode, developed by CNRS in France, to control ELT M4 and M5 mirrors from a pyramid wavefront sensor (PWFS).
The final design of the SCAO real-time computer (RTC) leverages the COSMIC platform for the hard-RTC (H-RTC) which implements the AO real-time operations, and the ESO RTC toolkit for the soft-RTC (S-RTC) which implements optimization operations, monitoring and command interfaces with the instrument. In this paper, we present the final design of the MICADO SCAO RTC which fully comply with ESO requirements and standards. We will show how both the COSMIC platform and the ESO RTC Toolkit are integrated together and we will provide the first performance results obtained in the prototyping activities.
MICADO is the ELT near-infrared first light imager. It will provide diffraction limited images thanks to single-conjugate adaptive optics (SCAO) mode provided inside the MAORY module. Numerical simulations were performed using COMPASS to assess the overall SCAO performance, exploring WFS design parameters and associated calibration procedures.
We present the optimizations developed to deal with pyramid wavefront sensor specific calibrations expected at the ELT (optimal modal basis, petalling, optical gains & NCPA management,). We then evaluate the impact of the AO loop frequency and RTC latency and others specific SCAO optimization parameters (modulation amplitude, number of controlled modes, etc) in various flux and turbulence conditions. We finally evaluate the impact of some of the ELT errors contributors such as M1 reflectivity errors, M1 phase aberrations, M1 missing segments, M4 mis-registration, telescope windshake & vibrations.
Tomography requires the knowledge of the statistical turbulence parameters, commonly recovered from the system telemetry using a dedicated profiling technique. For demonstration purposes with the MOAO pathfinder CANARY, this identification is performed thanks to the Learn & Apply (L&A) algorithm, that consists in model-fitting the covariance matrix of WFS measurements dependant on relevant parameters: Cn2(h) profile, outer scale profile and system mis-registration.
We explore an upgrade of this algorithm, the Learn 3 Steps (L3S) approach, that allows one to dissociate the identification of the altitude layers from the ground in order to mitigate the lack of convergence of the required empirical covariance matrices therefore reducing the required length of data time-series for reaching a given accuracy. For nominal observation conditions, the L3S can reach the same level of tomographic error in using five times less data frames than the L&A approach.
The L3S technique has been applied over a large amount of CANARY data to characterize the turbulence above the William Herschel Telescope (WHT). These data have been acquired the 13th, 15th, 16th, 17th and 18th September 2013 and we find 0.67"/8.9m/3.07m.s−1 of total seeing/outer scale/wind-speed, with 0.552"/9.2m/2.89m.s−1 below 1.5 km and 0.263"/10.3m/5.22m.s−1 between 1.5 and 20 km. We have also determined the high altitude layers above 20 km, missed by the tomographic reconstruction on CANARY , have a median seeing of 0.187" and have occurred 16% of observation time.
We present in the following the MICADO-MAORY SCAO specifications, the current SCAO prototyping activities at LESIA for E-ELT scale pyramid wavefront sensor (WFS) and real-time computer (RTC), our activities on end-to-end AO simulations and the current preliminary design of SCAO subsystems. We finish by presenting the implementation and current design studies for the high-contrast imaging mode of MICADO, which will make use of the SCAO correction offered to the instrument.
We have developed a Point Spread Function (PSF)-Reconstruction algorithm dedicated to MOAO systems using system telemetry to estimate the PSF potentially anywhere in the observed field, a prerequisite to deconvolve AO-corrected science observations in Integral Field Spectroscopy (IFS). Additionally the ability to accurately reconstruct the PSF is the materialization of the broad and fine-detailed understanding of the residual error contributors, both atmospheric and opto-mechanical.
In this paper we compare the classical PSF-r approach from Véran (1) that we take as reference on-axis using the truth-sensor telemetry to one tailored to atmospheric tomography by handling the off-axis data only.
We've post-processed over 450 on-sky CANARY data sets with which we observe 92% and 88% of correlation on respectively the reconstructed Strehl Ratio (SR)/Full Width at Half Maximum (FWHM) compared to the sky values. The reference method achieves 95% and 92.5% exploiting directly the measurements of the residual phase from the Canary Truth Sensor (TS).
Artificial intelligence system and optimized modal control for the ADONIS adaptive optics instrument
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