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15 October 2012Parameter optimization of Dome A site testing DIMM by data mining
The extreme environment of Antarctic is valuable for astronomical observations. Dome C is proved has excellent seeing
and transmission by site testing works. While the higher, colder inland plateau Dome A is widely predicted as even better
astronomical site than Dome C. Preliminary site testing developed since the beginning of 2008 shows that Dome A has
lower boundary layer and lower precipitable water vapour. Now the automated seeing monitor is urgently needed to
quantify the site's optical character which is necessary for the telescope design and deployment. In addition, it has the
requirement that DIMM must realize automatic measurement for nearly one year under the case of unmanned
intervention during which a great quantity of data will be generated because of the limitation of Dome A. This paper
aims at researching how to use the method of mining association rules to automatically analyze observation data, what
the relationship between various parameters effecting on optical quality is, and improving the efficiency of telescope
observation by parameter optimization. We have modified a commercial telescope with diameter of 35cm to function as
site testing DIMM which has been installed at XingLong observation station of National Astronomical Observatories,
Chinese Academy of Sciences, acquired long term observation data, and identified that this method is suitable for
optimizing the parameters of DIMM system.
Lingzhe Xu andChong Pei
"Parameter optimization of Dome A site testing DIMM by data mining", Proc. SPIE 8420, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing, 84200M (15 October 2012); https://doi.org/10.1117/12.974362
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Lingzhe Xu, Chong Pei, "Parameter optimization of Dome A site testing DIMM by data mining," Proc. SPIE 8420, 6th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical System Technologies for Manufacturing and Testing, 84200M (15 October 2012); https://doi.org/10.1117/12.974362