Abstract
We report initial performance results emerging from 600 h of observations with the Automated Planet Finder (APF) telescope and Levy spectrometer located at UCO/Lick Observatory. We have obtained multiple spectra of 80 G, K, and M-type stars, which comprise 4954 individual Doppler radial velocity (RV) measurements with a median internal uncertainty of 1.35 ms−1. We find a strong, expected correlation between the number of photons accumulated in the 5000 to 6200 Å iodine region of the spectrum and the resulting internal uncertainty estimates. Additionally, we find an offset between the population of G and K stars and the M stars within the dataset when comparing these parameters. As a consequence of their increased spectral line densities, M-type stars permit the same level of internal uncertainty with 2× fewer photons than G-type and K-type stars. When observing M stars, we show that the APF/Levy has essentially the same speed-on-sky as Keck/high resolution echelle spectrometer (HIRES) for precision RVs. In the interest of using the APF for long-duration RV surveys, we have designed and implemented a dynamic scheduling algorithm. We discuss the operation of the scheduler, which monitors ambient conditions and combines on-sky information with a database of survey targets to make intelligent, real-time targeting decisions.
Highlights
The Doppler velocity technique has two decades of success in enabling extrasolar planetary detections
The scheduler’s target selection is driven by balancing scientific goals and engineering constraints
The internal uncertainty does not include potential systematic errors associated with the instrument, nor does it account for astrophysical noise associated with the star and, represents only a lower limit to the accuracy of the data for finding companions
Summary
The Doppler velocity technique has two decades of success in enabling extrasolar planetary detections. The scheduler’s target selection is driven by balancing scientific goals (what we want to observe based on scientific interest, required data quality, and desired cadences) and engineering constraints (what we can observe based on current atmospheric conditions and physical limitations of the telescope). To address these criteria, we need to know how the velocity precision extracted from a given stellar spectrum depends on inputs that can be monitored before and during each observation.
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