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| Paper: |
Scheduling the New Robotic Telescope in the Big Data Era |
| Volume: |
538, ADASS XXXII |
| Page: |
146 |
| Authors: |
David Law; Helen Jermak; Christopher M. Copperwheat; Carl Chalmers; Joao Bento; Robert J. Smith |
| DOI: |
10.26624/CPSV1446 |
| Abstract: |
The Liverpool Telescope (LT) provides robotic, autonomous observations
for the time-domain community, with fully reduced data available to users minutes after
observations are taken. An intelligent dispatch scheduler, developed in the early 2000s,
ranks observations according to various factors such as observational constraints, position on the sky, weather and scientific priority. However, there is an opportunity to
exploit Artificial Intelligence (AI) advancements to optimise robotic follow-up strategy
and meet the demands of the ever-growing survey telescope domain with an intelligent
scheduling solution.
The New Robotic Telescope (NRT) is a future 4-metre facility designed to classify
transients rapidly. It combines mechanical engineering, machine learning and hardware
advances to create an extremely rapid response facility, slewing across the sky and acquiring data within 30 seconds of trigger receipt. The scheduler is crucial in stream-lining the follow-up process. We are exploiting the vast LT database of observations to
develop optimal scheduling algorithms before the NRT’s first light in 2026. |
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