English

SAXO+ upgrade : second stage AO system end-to-end numerical simulations

Instrumentation and Methods for Astrophysics 2023-10-25 v1

Abstract

SAXO+ is a proposed upgrade to SAXO, the AO system of the SPHERE instrument on the ESO Very Large Telescope. It will improve the capabilities of the instrument for the detection and characterization of young giant planets. It includes a second stage adaptive optics system composed of a dedicated near-infrared wavefront sensor and a deformable mirror. This second stage will remove the residual wavefront errors left by the current primary AO loop (SAXO). This paper focuses on the numerical simulations of the second stage (SAXO+) and concludes on the impact of the main AO parameters used to build the design strategy. Using an end-to-end AO simulation tool (COMPASS), we investigate the impact of several parameters on the performance of the AO system. We measure the performance in minimizing the star residuals in the coronagraphic image. The parameters that we study are : the second stage frequency, the photon flux on each WFS, the first stage gain and the DM number of actuators of the second stage. We show that the performance is improved by a factor 10 with respect to the current AO system (SAXO). The optimal second stage frequency is between 1 and 2 kHz under good observing conditions. In a red star case, the best SAXO+ performance is achieved with a low first stage gain of 0.05, which reduces the first stage rejection.

Keywords

Cite

@article{arxiv.2310.15765,
  title  = {SAXO+ upgrade : second stage AO system end-to-end numerical simulations},
  author = {Charles Goulas and Fabrice Vidal and Raphaël Galicher and Johan Mazoyer and Florian Ferreira and Arnaud Sevin and Anthony Boccaletti and Éric Gendron and Clémentine Béchet and Michel Tallon and Maud Langlois and Caroline Kulcsár and Henri-François Raynaud and Nicolas Galland and Laura Schreiber and Gaël Chauvin and Julien Milli},
  journal= {arXiv preprint arXiv:2310.15765},
  year   = {2023}
}

Comments

10 pages, 8 figures. Submitted to AO4ELT7 conference proceedings

R2 v1 2026-06-28T13:00:10.798Z