METIS

METIS, the Mid-infared ELT Imager and Spectrograph, is one of the three first light instruments for the ELT. One of its main goals is to directly detect Earth-like exoplanets with high-contrast imaging and high resolution spectroscopy. The project is now entering Phase C.

Within the METIS project, we are in charge of the development of the high-contrast imaging modes. This is a system-wide activity, that includes the design of the coronagraphic modes and of the related optical components, the development of dedicated observing strategies (including the correction of non-common path errors), as well as the performance simulation and validation of the high-contrast imaging modes. Some of the activities related to this project are described below.

Performance prediction of METIS high-contrast imaging. Description: In order to inform the main design choices of a high-contrast imaging instrument such as METIS, it is paramount to produce realistic performance predictions for various concepts or designs. In order to do so, we have developped an High-contrast End-to-End Performance Simulator (HEEPS), based on the PROPER optical propagation library.
Focal-plane wavefront sensing for METIS (in collaboration with Prof Matthew Kenworthy, Leiden Observatory). Description: This projet aims to adapt and implement a state-of-the-art technique for the measurement and control of non-common path aberrations (NCPA) within the METIS instrument, to be installed on the European ELT around 2027. We will focus on the Phase-Sorting Interferometry (PSI) technique (Codona & Kenworthy 2013), which uses the residual aberrations from the adaptive optics system as a source of diversity to reconstruct the pupil phase map from focal-plane images. In the longer term, we aim to adapt and implement the machine-learning algorithms developed within the EPIC/NNExI projects to the case of METIS.
Predictive control for METIS adaptive optics. Description: One of the main limitations to the performance of high-contrast imaging systems come from the lag between the adaptive optics wavefront measurement and the correction of the wavefront by the deformable mirror. Predictive control techniques have been proposed to mitigate this lag, and provide better HCI performance. Here, we are planning to adapt and implement these techniques in the context of the METIS project. We will also specifically investigate the use of machine-learning techniques to make predictive control more robust to variations in the atmospheric model used to feed the predictor.

This project received funding from the European Research Council under the European Union’s Seventh Framework Program (ERC Grant Agreement n. 337569), and under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 819155). This work is also supported by the Fonds de la Recherche Scientifique - FNRS under Grant n° F.4504.18.

updated on 9/21/22