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Neural networks for image-based wavefront sensing for astronomy

Andersen, Torben LU ; Owner-Petersen, Mette LU and Enmark, Anita LU (2019) In Optics Letters 44(18). p.4618-4621
Abstract
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.
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Optics Letters
volume
44
issue
18
pages
4 pages
publisher
Optical Society of America
external identifiers
  • scopus:85072106843
ISSN
0146-9592
DOI
10.1364/OL.44.004618
language
English
LU publication?
yes
id
da9ed7a8-4f39-4226-ae5d-27f4fb247997
date added to LUP
2019-09-28 22:31:47
date last changed
2019-10-15 07:17:17
@article{da9ed7a8-4f39-4226-ae5d-27f4fb247997,
  abstract     = {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.},
  author       = {Andersen, Torben and Owner-Petersen, Mette and Enmark, Anita},
  issn         = {0146-9592},
  language     = {eng},
  month        = {09},
  number       = {18},
  pages        = {4618--4621},
  publisher    = {Optical Society of America},
  series       = {Optics Letters},
  title        = {Neural networks for image-based wavefront sensing for astronomy},
  url          = {http://dx.doi.org/10.1364/OL.44.004618},
  volume       = {44},
  year         = {2019},
}