Wavefront aberration detection of a structured laser beam using artificial intelligence and its use for alignment

Abstract

The Structured Laser Beam (SLB) is a pseudo-non-diffracting laser beam that shares many characteristics with a Bessel beam. However, it can theoretically propagate over an unlimited distance while maintaining an extremely low inner core divergence of only 0.01 mrad. This makes it a promising candidate for precise longdistance alignment applications such as the alignment of particle accelerator components at CERN. In this work, a novel method to detect low-order wavefront aberrations induced by an SLB generator, that can affect the referential straightness of the beam, is presented. Our approach is based on the analysis of a single intensity distribution of an SLB. The coefficients of the Zernike polynomials are estimated using artificial intelligence before least-squares fitting is used to refine the result. This approach ensures that the fitting avoids local minima. This method provides a novel way to analyze the optical aberrations induced by the SLB generator and estimate the quality of the beam. Furthermore, it has the potential to be used for the alignment of complex lens systems, where an SLB can serve as a reference optical axis to which the other optical elements can be aligned.