A FDTD solution of scattering of laser beam with orbital angular momentum by dielectric particles: Far-field characteristics

Electromagnetic (EM) beams with orbital angular momentum (OAM) may have great potential applications in communication technology and in remote sensing of the Earth atmosphere system and outer planets. Study of their interaction with optical lenses and dielectric or metallic objects, or scattering of them by particles in the Earth-atmosphere system, is a necessary step to explore the advantage of the OAM EM beams. In this study, the 3-dimensional (3D) scattered-field (SF) finite-difference time domain (FDTD) technique with the convolutional perfectly matched layer (CPML) absorbing boundary conditions (ABC) is applied to calculate the scattering of the purely azimuthal (the radial mode number is assumed to be zero) Laguerre-Gaussian (IC) beams with the OAM by dielectric particles. We found that for OAM beam's interaction with dielectric particles, the forward-scattering peak in the conventional phase function (P11) disappears, and light scattering peak occurs at a scattering angle of similar to 15 degrees to 45 degrees. The disappearance of forward-scattering peak means that, in laser communications most of the particle-scattered noise cannot enter the receiver, thus the received light is optimally the original OAM-encoded signal. This feature of the OAM beam also implies that in lidar remote sensing of the atmospheric particulates, most of the multiple-scattering energy will be off lidar sensors, and this may result in an accurate profiling of particle layers in the atmosphere or in the oceans by lidar, or even in the ground when a ground penetration radar (GPR) with the OAM is applied. This far-field characteristics of the scattered OAM light also imply that the optical theorem, which is derived from plane parallel wave scattering case and relates the forward scattering amplitude to the total cross section of the scatterer, is invalid for the scattering of OAM beams by dielectric particles. (C) 2016 Elsevier Ltd. All rights reserved.