The Las Cumbres Observatory operates a fleet of robotically controlled telescopes currently two 2m, nine 1m, and ten 0.4m telescopes, distributed amongst six sites covering both hemispheres. Telescopes of an aperture class are equipped with an identical set of optical imagers, and those data are subsequently processed by a common pipeline (BANZAI). The telescopes operate without direct human supervision, and assessing the daily and long-term scientific productivity of the fleet of telescopes and instruments poses an operational challenge. One key operational metric of a telescope/instrument system is throughput. We present a method of long-term performance monitoring based on nightly science observations: For every image taken in matching filters and within the footprint of the <strong>PANSTARRS DR1 </strong>catalog we derive a photometric zeropoint, which is a good proxy for system throughput. This dataset of over 250000 data points enables us to answer questions about general throughput degradation trends, and how individual telescopes perform at the various sites. This particular metric is useful to plan the effort level for on-site support and to prioritize the cleaning and re-aluminizing schedule of telescope optics and mirrors respectively.
Work in time-domain astronomy necessitates robust, automated data processing pipelines that operate in real time. We present the BANZAI pipeline which processes the thousands of science images produced across the Las Cumbres Observatory Global Telescope (LCOGT) network of robotic telescopes each night. BANZAI is designed to perform near real-time preview and end-of-night final processing for four types of optical CCD imagers on the three LCOGT telescope classes. It performs instrumental signature removal (bad pixel masking, bias and dark removal, flat-field correction), astrometric fitting and source catalog extraction. We discuss the design considerations for BANZAI, including testing, performance, and extensibility. BANZAI is integrated into the observatory infrastructure and fulfills two critical functions: (1) real-time data processing that delivers data to users quickly and (2) derive metrics from those data products to monitor the health of the telescope network. In the era of time-domain astronomy, to get from these observations to scientific results, we must be able to automatically reduce data with minimal human interaction, but still have insight into the data stream for quality control.
With 18 telescopes distributed over 6 sites, and more telescopes being added in 2016, Las Cumbres Observatory Global Telescope Network is a unique resource for timedomain astronomy. The Network's continuous coverage of the night sky, and the optimization of the observing schedule over all sites simultaneously, have enabled LCOGTusers to produce significant science results. However, practical challenges to maximizing the Network's science output remain. The Network began providing observations for members of its Science Collaboration and other partners in May 2014. In the two years since then, LCOGT has made a number of improvements to increase the Network's science yield. We also now have two years' experience monitoring observatory performance; effective monitoring of an observatory that spans the globe is a complex enterprise. Here, we describe some of LCOGT's efforts to monitor the Network, assess the quality of science data, and improve communication with our users.