Validation Through Simulations of a Cn2 Profiler for the ESO/VLT Adaptive Optics Facility

TL;DR

This paper validates a Cn2 turbulence profiler for the ESO/VLT Adaptive Optics Facility through end-to-end simulations, demonstrating reliable turbulence profile identification for various AO modes.

Contribution

It presents a simulation-based validation of a turbulence profiler tailored for the ESO/VLT AOF, including correction methods and response analysis.

Findings

Profiler accurately identifies turbulence features in simulated data.

Uncertainties in input parameters have limited impact on normalized profiles.

Correction for unseen turbulence improves profiling accuracy.

Abstract

The Adaptive Optics Facility (AOF) project envisages transforming one of the VLT units into an adaptive telescope and providing its ESO (European Southern Observatory) second generation instruments with turbulence corrected wavefronts. For MUSE and HAWK-I this correction will be achieved through the GALACSI and GRAAL AO modules working in conjunction with a 1170 actuators Deformable Secondary Mirror (DSM) and the new Laser Guide Star Facility (4LGSF). Multiple wavefront sensors will enable GLAO and LTAO capabilities, whose performance can greatly benefit from a knowledge about the stratification of the turbulence in the atmosphere. This work, totally based on end-to-end simulations, describes the validation tests conducted on a Cn2 profiler adapted for the AOF specifications. Because an absolute profile calibration is strongly dependent on a reliable knowledge of turbulence parameters r0 and L0, the tests presented here refer only to normalized output profiles. Uncertainties in the input parameters inherent to the code are tested as well as the profiler response to different turbulence distributions. It adopts a correction for the unseen turbulence, critical for the GRAAL mode, and highlights the effects of masking out parts of the corrected wavefront on the results. Simulations of data with typical turbulence profiles from Paranal were input to the profiler, showing that it is possible to identify reliably the input features for all the AOF modes.