Affiliation:
1. Xi’an Institute of Applied Optics
Abstract
It is known that the cumbersome
2
π
correction is needed in the traditional module-
2
π
method (i.e., the phase wrapping method) due to the
2
π
deviation of the phase modulation depth of spatial light modulators (SLMs). To avoid the cumbersome
2
π
correction in the module-
2
π
method, this paper proposes a module-
n
π
method, and it can directly utilize any full-field phase modulation depth. First, for a Gaussian phase with a phase depth of 30 rad, wrapped by the module-
3.6
π
, it is reconstructed with the root-mean-square (RMS) values of its phase response are
0.1006
λ
(for the Twyman–Green interferometer) and
0.1101
λ
(for the Shack–Hartmann wavefront sensor method), respectively, which proves that the monitoring accuracy is relatively consistent. Subsequently, some comparative experiments based on the traditional module-
2
π
are performed. The experimental results show that the RMS values of its phase response are
0.8886
λ
(for a modulation depth of 11.3 rad) and
0.2261
λ
(for a modulation depth of 6.28 rad), respectively. All the results have proved that the SLM with a phase modulation depth exceeding
2
π
(e.g., 11.3 rad) has more prominent advantages. More specifically, increasing the SLM’s phase modulation depth can effectively reduce the fringe orders of the wrapped patterns generated by the module-
n
π
method. With the further reduction of the fringe orders, the influence of the fly-back zone error on the wavefront phase modulation is reduced, that is, the modulation accuracy is improved (the RMS values are reduced from
0.2261
λ
to
0.1006
λ
). Different from the traditional module-
2
π
method, there is no need to consider the problems of the SLMs’ over modulation or the insufficient modulation in the module-
n
π
method. Furthermore, it avoids the cumbersome
2
π
correction process, which will make the use of the SLM more convenient.
Funder
National Natural Science Foundation of China
Technology Program of Shaanxi Province of China
Jiangxi Provincial Natural Science Foundation
Subject
Computer Vision and Pattern Recognition,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials