Optimal regularisation and pupil fragmentation for Pyramid wavefront sensing

For ELTs, pupil fragmentation is a source of concern for both missing wavefront information behind the spiders and for low-wind effect which amplitude is difficult to minimize by design. This project addresses this topic in the context of pyramid wave-front sensing in a SCAO case, with an optimal reconstruction algorithm using regularization (and in particular the Frim3D algorithm, already being used at ESO). 

After an initial benchmarking of existing pyramid wavefront sensing algorithms, the work will focus on improving the regularized reconstruction process, and adapting work done on the Shack-Hartmann sensor to the Pyramid. We will pay particular attention to the match between the priors to the external (turbulence + telescope environment) conditions.

We will start by adapting a Shack-Hartmann based algorithm to the Pyramid sensor, "pretending" the Pyramid sensor measures slopes (good 0-th order approximation). Then, if performance is too severely impacted by the differences between the two wavefront sensors,  a standard pre-processing step will be applied to the Pyramid measurements to make them look more like SH-measurements. If time remains, we may upgrade the reconstruction algorithm itself ("forward model").

Using these algorithms, we will investigate the performance to control and correct petaling, with or without external phase jumps ("low wind effect"), and compare with other available methods.

Supervisor: M. Le Louarn (Systems Engineering Department – Adaptive Optics Group)

Collaboration with Observatoire de Lyon (M. Tallon), and University of Linz.