Reference Optical Turbulence and Wind Profiles for Single Conjugate and Extreme Adaptive Optics

Abstract

We present a simple method of extracting a small number of reference optical turbulence and wind profiles from a large dataset for single conjugate and extreme adaptive optics simulations. These reference profiles can be used in slow end-to-end adaptive optics simulations to represent the variability of the atmosphere. The method is based on the assumption that performance for these systems is correlated with integrated atmospheric parameters $r_0$, ${\theta }_0$ and ${\tau }_0$. Profiles are selected from a large dataset that conform concurrently to the distributions of these parameters, and hence represent the variability of the atmosphere as seen by the AO system. We also extend the equivalent layers method of profile compression to include wind profiles. The method is applied to stereo-SCIDAR data from ESO Paranal to extract five turbulence and wind profiles that cover a broad range in atmospheric variability, and we show using analytical AO simulation that this correlates to the equivalent range of AO-corrected Strehl ratios.

References in corpus (10)

• Astropy: A Community Python Package for Astronomy
• The NumPy array: a structure for efficient numerical computation
• Adaptive Optics for Astronomy
• Optical turbulence profiling with Stereo-SCIDAR for VLT and ELT
• MOSE: optical turbulence and atmospherical parameters operational forecast at ESO ground-based sites. I: Overview and atmospherical parameters vertical stratification on [0-20] km
• AOtools -- a Python package for adaptive optics modelling and analysis
• Atmospheric turbulence forecasting with a General Circulation Model for Cerro Paranal
• Thirty Meter Telescope Site Testing VI: Turbulence Profiles
• Representative optical turbulence profiles for ESO Paranal by hierarchical clustering
• Identifying optical turbulence profiles for realistic tomographic error in adaptive optics

Cited by in corpus (2)

• Modeling Optical Key Distribution over a Satellite-to-Ground Link Under Weak Atmospheric Turbulence
• Optical downlink modeling for low-earth-orbit and medium-earth-orbit satellites under atmospheric turbulence with a quantum-state-tomography use case