Paper
29 July 2010 Characterization of the mid-IR image quality at Gemini South
Author Affiliations +
Abstract
To help the prospective observer take full advantage of the mid-IR capability of Gemini South, we characterize a key aspect of the mid-IR performance of the 8-meter telescope at Gemini-S, namely, the appearance and stability of its delivered mid-IR image profiles, with the goal of demonstrating that it can be used with a level of precision not used before. About 2000 images obtained with T-ReCS (a facility mid-IR camera at Gemini-S) between late 2003 and early 2009 were used for our image quality analysis. All targets are flux standards and recorded at one or more of the four bands Si-2 (8.74 μm), N (10.36 μm), Si-5 (11.66 μm), and Qa (18.3 μm). A non-linear least squares fitting of three profile models (Lorentzian, Gaussian, and Moffat) was performed on each image, and key parameters such as FWHM, ellipticity, position angle and Strehl-ratio were measured from the fitted profile. We find that the long-time-scale image quality is quite stable in terms of profile width or ellipticity, though short-time-scale variation is evident. We also examined the correlation between image quality and many ambient parameters and confirmed the interdependence between the image quality in the Qa band and the ambient humidity. The ellipticity of the profile was analyzed statistically as well. The average profiles for different filters can be used as important references in the future when a high-quality profile reference is not available during an observation.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan Li, Charles M. Telesco, and Frank Varosi "Characterization of the mid-IR image quality at Gemini South", Proc. SPIE 7737, Observatory Operations: Strategies, Processes, and Systems III, 77372F (29 July 2010); https://doi.org/10.1117/12.856627
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KEYWORDS
Image quality

Mid-IR

Point spread functions

Gemini Observatory

Stars

Humidity

Image filtering

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