arXiv subjects

J. Nousiainen

Publications and source records attributed to J. Nousiainen.

2 recordsLinked to original sources

arXiv2026

Cascade adaptive optics with a second stage based on a Zernike wavefront sensor for exoplanet observations II. Validation in broadband light on the ESO/GHOST testbed

Current high-contrast facilities on the ground use extreme adaptive optics (XAO) systems to achieve contrasts down to $10^{-6}$ at 200\,mas for exoplanet observations. This performance is mainly limited by the XAO residuals due to the temporal errors in the XAO control loop. To overcome this issue, a promising solution consists in using cascade adaptive optics with a fast second stage. This approach was recently validated for a control loop based on a Zernike wavefront sensor (ZWFS) in monochromatic light. As wavefront sensors operate in broadband light to maximise photon sensitivity, this work aims to validate the ZWFS-based control loop in polychromatic light and assess its performance over a wide range of seeings, wind speeds, and stellar fluxes. Experiments were conducted on the ESO's GPU-based High-order adaptive OpticS Testbench (GHOST) testbed to probe our scheme in polychromatic light. Residual aberrations from a first-stage XAO system were simulated and our approach was evaluated in narrowband and broadband light through contrast in Lyot coronagraphic images. Closing the ZWFS-based control loop consistently improves contrast within its correction region in most tested conditions. After subtraction of quasi-static aberrations, our loop reaches a contrast gain up to one order of magnitude, independently of bandwidth and turbulence strength. The broadband and narrowband cases match in performance for bright sources, while narrowband remains slightly preferable for faint targets. These results demonstrate the feasibility of broadband ZWFS-based control loop and underline promising avenues with achromatic masks and an accurate calibration of quasi-static aberrations for future high-contrast imaging on Extremely Large Telescopes.

astro-ph.IM↗

arXiv2022

Towards on-sky adaptive optics control using reinforcement learning

The direct imaging of potentially habitable Exoplanets is one prime science case for the next generation of high contrast imaging instruments on ground-based extremely large telescopes. To reach this demanding science goal, the instruments are equipped with eXtreme Adaptive Optics (XAO) systems which will control thousands of actuators at a framerate of kilohertz to several kilohertz. Most of the habitable exoplanets are located at small angular separations from their host stars, where the current XAO systems' control laws leave strong residuals.Current AO control strategies like static matrix-based wavefront reconstruction and integrator control suffer from temporal delay error and are sensitive to mis-registration, i.e., to dynamic variations of the control system geometry. We aim to produce control methods that cope with these limitations, provide a significantly improved AO correction and, therefore, reduce the residual flux in the coronagraphic point spread function. We extend previous work in Reinforcement Learning for AO. The improved method, called PO4AO, learns a dynamics model and optimizes a control neural network, called a policy. We introduce the method and study it through numerical simulations of XAO with Pyramid wavefront sensing for the 8-m and 40-m telescope aperture cases. We further implemented PO4AO and carried out experiments in a laboratory environment using MagAO-X at the Steward laboratory. PO4AO provides the desired performance by improving the coronagraphic contrast in numerical simulations by factors 3-5 within the control region of DM and Pyramid WFS, in simulation and in the laboratory. The presented method is also quick to train, i.e., on timescales of typically 5-10 seconds, and the inference time is sufficiently small (< ms) to be used in real-time control for XAO with currently available hardware even for extremely large telescopes.

astro-ph.IM↗