
Torben Andersen
Professor emeritus (Leave of Absence)

Neural networks for image-based wavefront sensing for astronomy
Author
Summary, in English
We study the possibility of using convolutional neural networks for wavefront sensing from a guide star image in astronomical telescopes. We generated a large number of artificial atmospheric wavefront screens and determined associated best-fit Zernike polynomials. We also generated in-focus and out-of-focus point-spread functions. We trained the well-known “Inception” network using the artificial data sets and found that although the accuracy does not permit diffraction-limited correction, the potential improvement in the residual phase error is promising for a telescope in the 2–4 m class.
Department/s
- Lund Observatory - Undergoing reorganization
Publishing year
2019-09-13
Language
English
Pages
4618-4621
Publication/Series
Optics Letters
Volume
44
Issue
18
Document type
Journal article
Publisher
Optical Society of America
Topic
- Astronomy, Astrophysics and Cosmology
Status
Published
ISBN/ISSN/Other
- ISSN: 0146-9592