Real-time Closed-loop Correction for Dynamic Wavefront Aberrations Using Deep Learning–based Focal-plane Wavefront Sensing
- 1National Key Laboratory of Adaptive Optics
- 2Chinese Academy of Sciences
- 3University of Chinese Academy of Sciences
Abstract
Traditional adaptive optics (AO) systems enable diffraction-limited imaging in astronomical observations, yet suffer under strong turbulence and faint guide stars. Focal-plane wavefront sensing (FPWFS) offers a promising alternative but is hindered by slow convergence and phase ambiguity in iteration or deep learning implementations, making it impractical for astronomical observations. Building upon our previously proposed nondeterministic estimation (ND-estimation) method that resolves the phase ambiguity in focal-plane wavefront estimation, we develop a new control strategy—the Single-frame Focal-plane Wavefront Correction ( SFWC ) algorithm—integrating ND-estimation into a deep learning–based closed-loop AO architecture. The SFWC algorithm introduces a direction-resolved feedback mechanism that converts the ambiguity in focal-plane estimation into a deterministic control process through bidirectional perturbation. Furthermore, an adaptive filter is incorporated to predict the wavefront direction of the subsequent frame based on previously determined wavefronts. By integrating this predicted direction with the estimated wavefront of the network, correction can be achieved using only a single measurement. Laboratory experiments demonstrate robust static aberration correction across various turbulence strengths, achieving an average Strehl ratio of 0.93 with only ∼8 iterations. In addition, to the best of our knowledge, this work provides the first experimental demonstration of real-time closed-loop correction at 1200 Hz for dynamic aberrations using only focal-plane images. This work transforms ND-estimation from a static estimation into an operational tool for high-speed AO control, and it is easy to implement without modifying the optical path, thereby establishing a direct path toward FPWFS application in astronomical telescopes.
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BibTeX
@article{zhang2026realtime,
title = {{Real-time Closed-loop Correction for Dynamic Wavefront Aberrations Using Deep Learning–based Focal-plane Wavefront Sensing}},
author = {Lingxiao Zhang and Nanfei Yan and Libo Zhong and Qianhan Zhou and Youming Guo and Lanqiang Zhang and Changhui Rao},
journal = {The Astrophysical Journal Supplement Series},
year = {2026},
month = oct,
doi = {10.3847/1538-4365/aea4ab},
url = {https://iopscience.iop.org/article/10.3847/1538-4365/aea4ab},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Real-time Closed-loop Correction for Dynamic Wavefront Aberrations Using Deep Learning–based Focal-plane Wavefront Sensing
AU - Lingxiao Zhang
AU - Nanfei Yan
AU - Libo Zhong
AU - Qianhan Zhou
AU - Youming Guo
AU - Lanqiang Zhang
AU - Changhui Rao
PY - 2026
DA - 2026/10/23
JO - The Astrophysical Journal Supplement Series
DO - 10.3847/1538-4365/aea4ab
UR - https://iopscience.iop.org/article/10.3847/1538-4365/aea4ab
AB - Traditional adaptive optics (AO) systems enable diffraction-limited imaging in astronomical observations, yet suffer under strong turbulence and faint guide stars. Focal-plane wavefront sensing (FPWFS) offers a promising alternative but is hindered by slow convergence and phase ambiguity in iteration or deep learning implementations, making it impractical for astronomical observations. Building upon our previously proposed nondeterministic estimation (ND-estimation) method that resolves the phase ambiguity in focal-plane wavefront estimation, we develop a new control strategy—the Single-frame Focal-plane Wavefront Correction ( SFWC ) algorithm—integrating ND-estimation into a deep learning–based closed-loop AO architecture. The SFWC algorithm introduces a direction-resolved feedback mechanism that converts the ambiguity in focal-plane estimation into a deterministic control process through bidirectional perturbation. Furthermore, an adaptive filter is incorporated to predict the wavefront direction of the subsequent frame based on previously determined wavefronts. By integrating this predicted direction with the estimated wavefront of the network, correction can be achieved using only a single measurement. Laboratory experiments demonstrate robust static aberration correction across various turbulence strengths, achieving an average Strehl ratio of 0.93 with only ∼8 iterations. In addition, to the best of our knowledge, this work provides the first experimental demonstration of real-time closed-loop correction at 1200 Hz for dynamic aberrations using only focal-plane images. This work transforms ND-estimation from a static estimation into an operational tool for high-speed AO control, and it is easy to implement without modifying the optical path, thereby establishing a direct path toward FPWFS application in astronomical telescopes.
SN - 0067-0049
SN - 1538-4365
ER -