Radial shearing dynamic wavefront sensor based on a geometric phase lens pair.

A radial shearing dynamic wavefront sensor is theorized and experimentally verified. The proposed sensor is based on a geometric phase lens pair that generates two radially sheared wavefronts. A polarization pixelated camera instantaneously obtains polarization-multiplexed phase maps from a single acquired image using a spatial phase-shifting technique. Experimental tests applied several wavefront shapes with a deformable mirror. The results were compared with a Shack-Hartmann wavefront sensor to evaluate the performance.

Pyramid and Shack-Hartmann hybrid wave-front sensor.

An ideal wave-front sensor (WFS) for an adaptive optics system prioritizes three properties: high sensitivity, wide dynamic range, and a linear relationship between the actual and estimated wave fronts. WFSs currently in operation can claim superiority in only two of these properties. For example, the Shack-Hartmann WFS (SHWFS) has a linear response and remains effective under large aberrations, but its sensitivity to low spatial frequencies is limited [Proc. SPIE5490, 1177 (2004)PSISDG0277-786X10.1117/12.550786]. The pyramid WFS (PyWFS) [J. Mod. Opt.43, 289 (1996)JMOPEW0950-034010.1080/09500349608232742] can also be operated in a linear control system [Opt. Express14, 11925 (2006)OPEXFF1094-408710.1364/OE.14.011925] and offers excellent sensitivity when used with an unresolved beacon but saturates quickly in the presence of large aberrations. The dynamic range can be extended by modulating the beacon about the pyramid prism tip, but at the expense of its sensitivity. This Letter describes a hybrid WFS (HyWFS) that combines the SHWFS and PyWFS, capturing the desirable features of both. The optical design of the HyWFS mimics the appearance of an unmodulated PyWFS with a lenslet array in the reimaged pupil planes. Spot patterns in the style of a SHWFS are formed in all pupil images. Wave-front estimates are calculated from the HyWFS's output using both conventional PyWFS and SHWFS reconstruction methods. A cross-over algorithm chooses between the two estimates to retain high sensitivity to low aberration and a robust capture range.