The three-dimensional measurement of structured light is commonly used and has widespread applications in many industries. In this study, machine learning is used for structured light 3D measurement to recover the phase distribution of the measured object by employing two machine learning models. Without phase shift, the measurement operational complexity and computation time decline renders real-time measurement possible. Finally, a grating-based structured light measurement system is constructed, and machine learning is used to recover the phase. The calculated phase of distribution is wrapped in only one dimension and not in two dimensions, as in other methods. The measurement error is observed to be under 1%.

Optical traps formed in hollow-core fibers (HCFs) can overcome several limitations of conventional free-space optical tweezers. One of the key issues is to load particles from free space into the hollow core with high efficiency, in which process the capture dynamics of the particles in front of the HCF endface plays an important role. In this work, a comprehensive model of the trapping and capture process of the dielectric particles in front of HCF is established by taking into account the features of the fiber modes and the motional parameters of the particles. Stable capture positions are predicted based on analytical calculations of optical forces, and the dependencies of the equilibrium axial trapping position on the beam numerical aperture, the fiber core and particle diameters are provided. In addition, the trajectories and the capture dynamics of the particles are studied by solving the equation of motion for the particles under the impact of optical forces, predicting feasible parameter ranges of the initial amplitude and direction of particle launch velocity for achieving successful particle capture in front of HCF. The results can provide guidance for further improving the particle-loading efficiencies of the HCF-based optical traps, which may find applications of flying particle sensors and long-range particle binding in HCFs.