Development of an ELT XAO testbed using a self referenced Mach-Zehnder wavefront sensor
- Author(s): Delacroix, Christian
- Loupias, Magali
- Langlois, Maud
- Tallon, Michel
- Thiébaut, Eric
- et al.
Published Web Locationhttps://doi.org/10.20353/K3T4CP1131619
Extreme adaptive optics (XAO) has severe difficulties meeting the high speed (>1kHz), accuracy and photon efficiency requirements for future extremely large telescopes. An innovative high order adaptive optics system using a self-referenced Mach-Zehnder wavefront sensor (MZWFS) allows counteracting these limitations. In addition to its very high accuracy, this WFS is the most robust alternative to segments gaps and telescope spiders which can result in strong wavefront artifacts. In particular in XAO systems when the size of these gaps in the wavefront measurement is comparable to the sub aperture size, loss in performance can be very high. The MZWFS estimates the wavefront phase by measuring intensity differences between two outputs, with a λ/4 path length difference between its two legs, but is limited in dynamic range. During the past few years, such an XAO system has been studied by our team in the framework of 8-meter class telescopes. In this paper, we report on our latest results with the XAO testbed recently installed in CRAL laboratory, and dedicated to high contrast imaging with 30m-class telescopes (such as the E-ELT or the TMT). A woofer-tweeter architecture is used in order to deliver the required high Strehl ratio (>95%). It consists of a 12x12 deformable mirror (DM) and a 512x512 Spatial Light Modulator (SLM) characterized both using monochromatic and polychromatic light. We present our latest experimental results, including components characterization, close loop performances and sensitivity to calibration errors. This work is carried out in synergy with the validation of fast iterative wavefront reconstruction algorithms and the optimal treatment of phase ambiguities in order to mitigate the dynamical range limitation of such a wavefront sensor.