Advancing the Technology Readiness of the Nonlinear Curvature Wavefront Sensor through Modeling and Laboratory Investigation

Adaptive optics (AO) systems provide a means for astronomers to overcome the distorting effects of the Earth's tubulent atmosphere on incoming light from celestial objects. A vital component of any AO system is the wavefront sensor (WFS). The most commonly used WFS, the Shack-Hartmann wavefront sensor (SHWFS), is more than an order of magnitude less sensitive than a theoretically ideal sensor. Further exacerbating this problem, the effects of scintillation locally reduce the signal in the SHWFS through interference effects, causing a reduction in performance. These impediments limit the science that can be pursued using ground-based telescopes, particularly at visible wavelengths and high airmass. In this PhD dissertation, a systematic exploration of an alternative to the SHWFS, the nonlinear curvature wavefront sensor (nlCWFS), is performed. This work focuses on both theoretical and laboratory research that aims to mature the nlCWFS architecture as a candidate replacement for the SHWFS. First, a comprehensive, simulation-based sensitivity analysis is presented on the optimal values of both the number and location of nlCWFS measurement planes. Next, the effects of scintillation on the nlCWFS compared to the SHWFS are studied in a laboratory testbed with increasing values of turbulence strength. Finally, the laboratory testbed is used to assess and validate the performance of the nlCWFS in the presence of detector readout noise. The results of both numerical simulations and laboratory experiments demonstrate that the nlCWFS consistently delivers improved sensitivity and robustness to scintillation compared to an equivalent SHWFS. Therefore, AO systems that employ a nlCWFS will be capable of accessing fainter natural guide star and lower-power laser guide star targets, while simultaneously enabling correction across a broad range of turbulence strengths and airmass. The results of this work help to inform the practicality of using a nlCWFS as a platform technology across multiple scientific and engineering disciplines.