Neural networks for image-based wavefront sensing for astronomy

Torben Andersen, Mette Owner-Petersen, Anita Enmark

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13 Citeringar (SciVal)

Sammanfattning

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.
Originalspråkengelska
Sidor (från-till)4618-4621
Antal sidor4
TidskriftOptics Letters
Volym44
Utgåva18
DOI
StatusPublished - 2019 sep 13

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Ämnesklassifikation (UKÄ)

  • Astronomi, astrofysik och kosmologi

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