Publication details for Mr Oliver FarleyFarley, O J D, Osborn, J, Morris, T, Fusco, T, Neichel, B, Correia, C & Wilson, R W (2019). Identifying optical turbulence profiles for realistic tomographic error in adaptive optics. Monthly Notices of the Royal Astronomical Society 488(1): 213-221.
- Publication type: Journal Article
- ISSN/ISBN: 0035-8711 (print), 1365-2966 (electronic)
- DOI: 10.1093/mnras/stz1669
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
For extremely large telescopes, adaptive optics will be required to correct the Earth’s turbulent atmosphere. The performance of tomographic adaptive optics is strongly dependent on the vertical distribution (profile) of this turbulence. An important way in which this manifests is the tomographic error, arising from imperfect measurement and reconstruction of the turbulent phase at altitude. Conventionally, a small number of reference profiles are used to obtain this error in simulation; however these profiles are not constructed to be representative in terms of tomographic error. It is therefore unknown whether these simulations are providing realistic performance estimates. Here, we employ analytical adaptive optics simulation that drastically reduces computation times to compute tomographic error for 10 691 measurements of the turbulence profile gathered by the Stereo-SCIDAR instrument at ESO Paranal. We assess for the first time the impact of the profile on tomographic error in a statistical manner. We find, in agreement with previous work, that the tomographic error is most directly linked with the distribution of turbulence into discrete, stratified layers. Reference profiles are found to provide mostly higher tomographic error than expected, which we attribute to the fact that these profiles are primarily composed of averages of many measurements resulting in unrealistic, continuous distributions of turbulence. We propose that a representative profile should be defined with respect to a particular system, and that as such simulations with a large statistical sample of profiles must be an important step in the design process.