Wavefront sensing is essential for many applications related to imaging and remote sensing. Most of the existing methods of wavefront sensing are based on interferometry and rely on precise optical alignment, which are often hard or impossible to realize in a real-life setting. On the other hand, nonlinear optical conversion, such as second harmonic generation, is sensitive to the spatial phase information of the beam profile, and, as we have shown lately, can be optimized through external beam shaper. More recently, we have demonstrated that the inverse problem can be successfully solved by acquiring second harmonic images of the beam and retrieving through a computer algorithm, enhanced by machine learning, the incident beam's wavefront. In this report, I will outline our recent results in this field, discuss the sensitivity and acquisition speed of the newly proposed method and outline potential applications related to remote sensing and biological imaging.
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