PROCEEDINGS ARTICLE | July 18, 2014
Proc. SPIE. 9152, Software and Cyberinfrastructure for Astronomy III
KEYWORDS: Near infrared, Telescopes, Spectrographs, Stars, Sensors, Calibration, Control systems, Space telescopes, Data processing, Visibility
The main goal of the CARMENES instrument is to perform high-accuracy measurements of stellar radial velocities (1m/s) with long-term stability. CARMENES will be installed in 2015 at the 3.5 m telescope in the Calar Alto Observatory (Spain) and it will be equipped with two spectrographs covering from the visible to the near-infrared. It will make use of its near-IR capabilities to observe late-type stars, whose peak of the spectral energy distribution falls in the relevant wavelength interval. The technology needed to develop this instrument represents a challenge at all levels. We present two software packages that play a key role in the control layer for an efficient operation of the instrument: the Instrument Control System
(ICS) and the Operational Scheduler. The coordination and management of CARMENES is handled by the ICS, which is responsible for carrying out the operations of the different subsystems providing a tool to operate the instrument in an integrated manner from low to high user interaction level. The ICS interacts with the following subsystems: the near-IR and visible channels, composed by the detectors and exposure meters; the calibration units; the environment sensors; the front-end electronics; the acquisition and guiding module; the interfaces with telescope and dome; and, finally, the software subsystems for operational scheduling of tasks, data processing, and data archiving. We describe the ICS software design, which implements the CARMENES operational design and is planned to be integrated in the instrument by the end of 2014. The CARMENES operational scheduler is the second key element in the control layer described in this contribution. It is the main actor in the translation of the survey strategy into a detailed schedule for the achievement of the optimization goals. The scheduler is based on Artificial Intelligence techniques and computes the survey planning by combining the static constraints that are known a priori (i.e., target visibility, sky background, required time sampling coverage) and the dynamic change of the system conditions (i.e., weather, system conditions). Off-line and on-line strategies are integrated into a single tool for a suitable transfer of the target prioritization made by the science team to the real-time schedule that will be used by the instrument operators. A suitable solution will be expected to increase the efficiency of telescope operations, which will represent an important benefit in terms of scientific return and operational costs. We present the operational scheduling tool designed for CARMENES, which is based on two algorithms combining a global and a local search: Genetic Algorithms and Hill Climbing astronomy-based heuristics, respectively. The algorithm explores a large amount of potential solutions from the vast search space and is able to identify the most efficient ones. A planning solution is considered efficient when it optimizes the objectives defined, which, in our case, are related to the reduction of the time that the telescope is not in use and the maximization of the scientific return, measured in terms of the time coverage of each target in the survey. We present the results obtained using different test cases.
