Statistics of Turbulence Parameters at Maunakea using multiple wave-front sensor data of RAVEN

TL;DR

This paper analyzes atmospheric turbulence at Maunakea using multiple wave-front sensors from RAVEN, providing detailed vertical profiles of $C_N^2$ and outer scale, which are crucial for adaptive optics system optimization.

Contribution

It introduces a novel SLODAR-based method with a Levenberg-Marquardt Algorithm for estimating turbulence profiles from on-sky telemetry data.

Findings

Median total seeing of 0.460 arcseconds

Ground layer $C_N^2$ fraction of 54.3%

Outer scale median value of 25.5m, increasing with altitude

Abstract

Prior statistical knowledge of the atmospheric turbulence is essential for designing, optimizing and evaluating tomographic adaptive optics systems. We present the statistics of the vertical profiles of $C_N^2$ and the outer scale at Maunakea estimated using a Slope Detection And Ranging (SLODAR) method from on-sky telemetry taken by RAVEN, which is a MOAO demonstrator in the Subaru telescope. In our SLODAR method, the profiles are estimated by a fit of the theoretical auto- and cross-correlation of measurements from multiple Shack-Haltmann wavefront sensors to the observed correlations via the non-linear Levenberg-Marquardt Algorithm (LMA), and the analytic derivatives of the spatial phase structure function with respect to its parameters for the LMA are also developed. The estimated profile has the median total seeing of 0.460$^{\prime\prime}$ and large $C_N^2$ fraction of the ground layer of 54.3%. The $C_N^2$ profile has a good agreement with the result from literatures, except for the ground layer. The median value of the outer scale is 25.5m and the outer scale is larger at higher altitudes, and these trends of the outer scale are consistent with findings in literatures.