In the present work, we propose an improved wavefront reconstruction algorithm for zonal wavefront estimation using Shack–Hartmann type wavefront sensors. We start with the well known W H Southwell reconstruction algorithm, where phase at a central point is described in terms of horizontal and vertical slope values. We develop the mathematical expressions to show that by incorporating the diagonal slope values in addition to the horizontal and vertical slope values, accuracy in phase estimation can be increased. We present here experimental results that demonstrate significant improvement in the wavefronts, estimated using the proposed algorithm, in comparison to the Southwell algorithm.
Estimation of the wavefront from measured slope values is an essential step in a Shack-Hartmann-type wavefront sensor. Using an appropriate estimation algorithm, these measured slopes are converted into wavefront phase values. Hence, accuracy in wavefront estimation lies in proper interpretation of these measured slope values using the chosen estimation algorithm. There are two important sources of errors associated with the wavefront estimation process, namely, the slope measurement error and the algorithm discretization error. The former type is due to the noise in the slope measurements or to the detector centroiding error, and the latter is a consequence of solving equations of a basic estimation algorithm adopted onto a discrete geometry. These errors deserve particular attention, because they decide the preference of a specific estimation algorithm for wavefront estimation. In this paper, we investigate these two important sources of errors associated with the wavefront estimation algorithms of Shack-Hartmann-type wavefront sensors. We consider the widely used Southwell algorithm and the recently proposed Pathak-Boruah algorithm [J. Opt.16, 055403 (2014)JOOPDB0150-536X10.1088/2040-8978/16/5/055403] and perform a comparative study between the two. We find that the latter algorithm is inherently superior to the Southwell algorithm in terms of the error propagation performance. We also conduct experiments that further establish the correctness of the comparative study between the said two estimation algorithms.
Here we introduce an in situ and non-intrusive surface and thickness profile monitoring scheme of thin-film growth during deposition. The scheme is implemented using a programmable grating array based zonal wavefront sensor integrated with a thin-film deposition unit. It provides both 2D surface and thickness profiles of any reflecting thin film during deposition without requiring the properties of the thin-film material. The proposed scheme comprises a mechanism to nullify the effect of vibrations which is normally built in with the vacuum pumps of thin-film deposition systems and is largely immune to the fluctuations in the probe beam intensity. The final thickness profile obtained is compared with independent off-line measurement and the two results are observed to be in agreement.
In this Letter, we introduce a scheme to enhance the spatial resolution of a zonal wavefront sensor. The zonal wavefront sensor comprises an array of binary gratings implemented by a ferroelectric spatial light modulator (FLCSLM) followed by a lens, in lieu of the array of lenses in the Shack-Hartmann wavefront sensor. We show that the fast response of the FLCSLM device facilitates quick display of several laterally shifted binary grating patterns, and the programmability of the device enables simultaneous capturing of each focal spot array. This eventually leads to a wavefront estimation with an enhanced spatial resolution without much sacrifice on the sensor frame rate, thus making the scheme suitable for high spatial resolution measurement of transient wavefronts. We present experimental and numerical simulation results to demonstrate the importance of the proposed wavefront sensing scheme.
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