Modelling of a novel point diffraction interferometer design for laser guide star wavefront sensing

Most of the current wavefront sensors used in adaptive optics systems estimate the phase of the wavefront indirectly by measuring the local gradients. In strong turbulence the AO correction decreases dramatically, meaning poor wavefront reconstruction. This is due to insufficient wavefront spatial sampling and large signal amplitude variations induced by scintillation, which reduce the accuracy of centroiding algorithms. Direct wavefront measurements, instead of its derivatives, with adequate spatial sampling are ideally suited. Interferometric techniques may be used in alternative to slope-based, or curvature-based wavefront sensors. In this work, a novel design of a point diffraction interferometer (PDI) wavefront sensor is presented which aims to optimise the light throughput and dynamic range while keeping its high sensitivity. This design is an optimised PDI wavefront sensor with a central pinhole. The modelling of this sensor using numerical propagation with Fourier optics is presented. A framework has been established to retrieve the phase reversing the interferometric process, which differs from traditional methods which typically use an off-axis pinhole or phase-stepping. These results look promising showing accurate phase retrieval in a variety of conditions. Ultimately, to overcome the non-linearity of the PDI, machine learning will be used to retrieve the phase and perform prediction. Our preliminary results on the use of machine learning for phase retrieval are also presented.