Making the unmodulated Pyramid wavefront sensor smart

Closed-loop demonstration of neural network wavefront reconstruction with MagAO-X^★

¹ Leiden Observatory, Leiden University, PO Box 9513, 2300 RA Leiden, The Netherlands
e-mail: rlandman@strw.leidenuniv.nl
² Steward Observatory, The Unversity of Arizona, 933 North Cherry Avenue, Tucson, AZ, USA
³ Wyant College of Optical Sciences, The University of Arizona, 1630 E University Blvd, Tucson, AZ, USA
⁴ Subaru Telescope, National Observatory of Japan, National Institutes of Natural Sciences, 650 N. A’ohoku Place, Hilo, Hawaii, USA
⁵ Astrobiology Center, National Institutes of Natural Sciences, 2-21-1 Osawa, Mitaka, Tokyo, Japan
⁶ Northrop Grumman Corporation, 600 South Hicks Road, Rolling Meadows, IL, USA
⁷ Center for Computational Astrophysics, Flatiron Institute, 162 5th Avenue, New York, NY, USA
⁸ Draper Laboratory, 555 Technology Square, Cambridge, MA, USA
⁹ Starfire Optical Range, Kirtland Air Force Base, Albuquerque, NM, USA

Received: 11 December 2023
Accepted: 22 January 2024

Abstract

Almost all current and future high-contrast imaging instruments will use a Pyramid wavefront sensor (PWFS) as a primary or secondary wavefront sensor. The main issue with the PWFS is its nonlinear response to large phase aberrations, especially under strong atmospheric turbulence. Most instruments try to increase its linearity range by using dynamic modulation, but this leads to decreased sensitivity, most prominently for low-order modes, and makes it blind to petal-piston modes. In the push toward high-contrast imaging of fainter stars and deeper contrasts, there is a strong interest in using the PWFS in its unmodulated form. Here, we present closed-loop lab results of a nonlinear reconstructor for the unmodulated PWFS of the Magellan Adaptive Optics extreme (MagAO-X) system based on convolutional neural networks (CNNs). We show that our nonlinear reconstructor has a dynamic range of >600 nm root-mean-square (RMS), significantly outperforming the linear reconstructor that only has a 50 nm RMS dynamic range. The reconstructor behaves well in closed loop and can obtain >80% Strehl at 875 nm under a large variety of conditions and reaches higher Strehl ratios than the linear reconstructor under all simulated conditions. The CNN reconstructor also achieves the theoretical sensitivity limit of a PWFS, showing that it does not lose its sensitivity in exchange for dynamic range. The current CNN’s computational time is 690 µs, which enables loop speeds of >1 kHz. On-sky tests are foreseen soon and will be important for pushing future high-contrast imaging instruments toward their limits.