Adaptive optics for array telescopes using neural-network techniques

Details Adaptive optics for array telescopes using neural-network techniques Adaptive optics for array telescopes using neural-network techniques

Nov 1990

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1990natur.348..221a&link_type=abstract

Nature (ISSN 0028-0836), vol. 348, Nov. 15, 1990, p. 221-224. Research supported by USAF.

Physics

Optics

41

Adaptive Optics, Image Enhancement, Infrared Telescopes, Neural Nets, Phased Arrays, Angular Resolution, Focusing, Imaging Techniques, Mirrors

Scientific paper

For multiple-telescope arrays, the biggest errors caused by seeing at IR wavelengths are the variations in pathlength and wavefront tilt between array elements. It is shown here that these errors can be derived by an artificial neural network, given only a pair of simultaneous in-focus and out-of-focus images of a reference star formed at the combined focus of all the array elements. A neural network appropriate for 2.2 micron wavelength imaging at the Multiple Mirror telescope in Arizona has been optimized. Corrections made by moving the beam-combining mirrors will largely recover the diffraction-limited profile, with a resolution of 0.06 arcsec.

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