Computer Science – Artificial Intelligence
Scientific paper
Dec 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994aas...185.6903h&link_type=abstract
American Astronomical Society, 185th AAS Meeting, #69.03; Bulletin of the American Astronomical Society, Vol. 26, p.1423
Computer Science
Artificial Intelligence
Scientific paper
Tennessee State University conducts remote, automatic observing with four robotic telescopes located at the Fairborn Observatory site on Mt. Hopkins, 30 miles south of Tucson. These telescopes run completely unattended; a site control computer monitors the time of day and weather conditions, opens the roof at the beginning of the night, informs each telescope's control computer when observations can begin, and shuts down the site when morning twilight or bad weather intervenes. The Automatic Telescope Instruction Set (ATIS) allows us to program the telescopes and to retrieve data via ASCII file transfers over the Internet. ATIS also includes a set of target selection rules that allow the telescopes to operate autonomously for many weeks or months without our intervention. Over the past several years, Tennessee State University has collaborated with Fairborn to develop precision photometers, software, observing techniques and quality control procedures that have culminated in the automatic acquisition and reduction of high volumes of data with millimagnitude precision. The telescopes are being used for a variety long-term monitoring programs that would be difficult or impossible (and prohibitively expensive) to conduct by traditional manual methods. A 10-inch telescope is dedicated to observations of semi-regular variable stars to uncover their multiple periods. A 16-inch telescope is dedicated to long-term observations of chromospherically active (single and binary) stars to search for activity cycles. Solar-type stars are being monitored by 30-inch and 32-inch telescopes to measure the subtle luminosity variations of these stars associated with their long-term magnetic variations as measured by the HK Project at Mt. Wilson Observatory. An additional project in collaboration with the NASA Ames Research Center seeks to apply artificial intelligence techniques to improve the scheduling of the observations on these telescopes and to develop a software package to simplify access to robotic telescopes via the World Wide Web. This research is supported by NASA grant NAG8-1014 and NSF grant HRD-9104484.
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