Instrument Modes:

The Gemini South Adaptive Optics Imager (GSAOI) is a near-IR camera designed for use with the Gemini Multi-conjugate Adaptive Optics System (GeMS). GeMS is a multi-conjugate AO system and GSAOI provides diffraction limited images through various filters spanning the 0.9 -2.4 micron wavelength range.

Instrument design and use:

The Gemini GSAOI web pages provide an instrument description. References to the design are given on the GSAOI web page under the heading Documents. An overview of GSAOI was presented by R. Carrasco et al. at the 2011 South American Gemini Data Reduction Workshop.

System Verification data:

In 2012 the Gemini observatory selected science projects for system verification. This data is now public.

Data reduction:

The Science Operations link on the Gemini Science web page leads via Data and Results to the useful page Getting Started. Under the topic GSAOI links are provided to the GSAOI Gemini IRAF documentation gsaoiinfo. In gsaoinfo there are some basic descriptions of the detector array, size, and layout, data format, read modes, and available reduction tasks. The IRAF command “help gsaoi” is also useful. An example of a GSAOI data reduction script can be found at “gsaoiexamples”. In gsaoiexamples there is a very minimal data reduction outline. Some additional information is available at the GSAOI Data Format and Reduction link.

The above examples do not deal with geometric distortions. Both static and dynamic distortions are critically important to most GSAOI projects. Geometric distortions are mentioned in a talk by R. Carrasco given at the 2014 workshop in Guarujá. In addition to an overview of the reduction process there is also a discussion of how to correct distortions and how to stack the images. A more recent package has been developed called Disco-Stu. Disco-Stu (Distortion Correction and Stacking Utility) is standalone Python that aligns and stacks images already processed by the Gemini IRAF gareduce task. To download Disco-Stu see

Click here for SV and engineering data.


There are a number of papers that discuss data reduction techniques with GSAOI. A sample includes:

Bernard, A., Maugnier, L., Neichel, B. et al. 2016, SPIE, 9909 "Corrections of distortion ..."

Massari, D., Fiorentino, G., McConnachie, A., et al. 2016, AA, 595, L2 "Astrometry with MCAO ..."

Neichel, B., Lu, J., Rigaut, F. et al. 2014, MNRAS, 445, 500 "Astrometric performance ..."

Schirmer, M., Garrrel, V., Sivo, G., et al. 2017, MNRAS, 472, 217 "MCAO imaging of distant galaxies ..."

Last updated or reviewed September 28, 2018.

Updated on July 1, 2021, 6:16 am