2021/12/02 by Rehan Hafeez, Finn Archinuk, Hafeez, Rehan +7
Physics and Astronomy · #Adaptive optics and wavefront sensing #Astronomy and Astrophysical Research #FOS: Physical sciences #Instrumentation and Methods for Astrophysics (astro-ph.IM) #Stellar, planetary, and galactic studies
paper · pdf · doi:10.48550/arxiv.2112.01437
openalex publication_date 2021/12/02 · openalex created_date 2022/05/05 · openalex updated_date 2026/07/28
We use telemetry data from the Gemini North ALTAIR adaptive optics system to investigate how well the commands for wavefront correction (both Tip/Tilt and high-order turbulence) can be forecasted in order to reduce lag error (due to wavefront sensor averaging and computational delays) and improve delivered image quality. We show that a high level of reduction (∼ 5 for Tip-Tilt and ∼ 2 for high-order modes) in RMS wavefront error can be achieved by using a "forecasting filter" based on a linear auto-regressive model with only a few coefficients (∼ 30 for Tip-Tilt and ∼ 5 for high-order modes) to complement the existing integral servo-controller. Updating this filter to adapt to evolving observing conditions is computationally inexpensive and requires less than 10 seconds worth of telemetry data. We also use several machine learning models (Long-Short Term Memory and dilated convolutional models) to evaluate whether further improvements could be achieved with a more sophisticated non-linear model. Our attempts showed no perceptible improvements over linear auto-regressive predictions, even for large lags where residuals from the linear models are high, suggesting that non-linear wavefront distortions for ALTAIR at the Gemini North telescope may not be forecasted with the current setup