Tempestas ex machina: a review of machine learning methods for wavefront control
J Fowler, R Landman - Techniques and Instrumentation for …, 2023 - spiedigitallibrary.org
As we look to the next generation of adaptive optics systems, now is the time to develop and
explore the technologies that will allow us to image rocky Earth-like planets; wavefront …
explore the technologies that will allow us to image rocky Earth-like planets; wavefront …
Image-based wavefront correction using model-free Reinforcement Learning
Y Gutierrez, J Mazoyer, LM Mugnier… - Optics …, 2024 - opg.optica.org
Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once
estimated, these aberrations can be compensated for using deformable mirrors in a closed …
estimated, these aberrations can be compensated for using deformable mirrors in a closed …
Making the unmodulated Pyramid wavefront sensor smart-Closed-loop demonstration of neural network wavefront reconstruction with MagAO-X
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 …
sensor (PWFS) as a primary or secondary wavefront sensor. The main issue with the PWFS …
[HTML][HTML] Reinforcement Learning Environment for Wavefront Sensorless Adaptive Optics in Single-Mode Fiber Coupled Optical Satellite Communications Downlinks
Optical satellite communications (OSC) downlinks can support much higher bandwidths
than radio-frequency channels. However, atmospheric turbulence degrades the optical …
than radio-frequency channels. However, atmospheric turbulence degrades the optical …
Image-to-image translation for wavefront and point spread function estimation
We develop and evaluate a new approach to phase estimation for observational astronomy
that can be used for accurate point spread function reconstruction. Phase estimation is …
that can be used for accurate point spread function reconstruction. Phase estimation is …
Integrating supervised and reinforcement learning for predictive control with an unmodulated pyramid wavefront sensor for adaptive optics
We propose a novel control approach that combines offline supervised learning to address
the challenges posed by non-linear phase reconstruction using unmodulated pyramid …
the challenges posed by non-linear phase reconstruction using unmodulated pyramid …
Reinforcement learning-based wavefront sensorless adaptive optics approaches for satellite-to-ground laser communication
Optical satellite-to-ground communication (OSGC) has the potential to improve access to
fast and affordable Internet in remote regions. Atmospheric turbulence, however, distorts the …
fast and affordable Internet in remote regions. Atmospheric turbulence, however, distorts the …
Integrating deep neural networks with COSMIC for real-time control
We present results on integrating Machine Learning (ML) methods for adaptive optics
control with a real-time control library: COmmon Scalable and Modular Infrastructure for real …
control with a real-time control library: COmmon Scalable and Modular Infrastructure for real …
[PDF][PDF] A Study of Network-based Wavefront Estimation with Noise
We provide an extended COMPASS simulation study of our existing Machine Learning
based approaches to wavefront estimation using Convolutional Neural Networks (CNN) …
based approaches to wavefront estimation using Convolutional Neural Networks (CNN) …
The future looks dark: improving high contrast imaging with hyper-parameter optimization for data-driven predictive wavefront control
J Fowler, R Jensen-Clem… - … Optics Systems IX, 2024 - spiedigitallibrary.org
The direct imaging and characterization of exoplanets requires extreme adaptive optics
(XAO), achieving exquisite wavefront correction (upwards of 90% Strehl) over a narrow field …
(XAO), achieving exquisite wavefront correction (upwards of 90% Strehl) over a narrow field …