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Luke H. Nicholls

Publications and source records attributed to Luke H. Nicholls.

2 recordsLinked to original sources

Longitudinal field controls vector vortex beams in anisotropic epsilon-near-zero metamaterials

Structured light plays an important role in metrology, optical trapping and manipulation, communications, quantum technologies, nonlinear optics and provides a rich playground for addressing new optical phenomena. Here we demonstrate a novel approach for manipulating vector vortex beams carrying longitudinal field components using metamaterials with extreme anisotropy. Implementing vectorial spectroscopy, we show that the propagation of complex beams with inhomogeneous polarisation is strongly affected by the interplay of the metamaterial anisotropy with the transverse and longitudinal field structure of the beam. This phenomenon is especially pronounced in the epsilon-near-zero regime, exclusively realised for light polarised along the metamaterial optical axis, strongly influencing the interaction of longitudinal fields with the metamaterial. The requirements on the balance between the transverse and longitudinal fields to maintain a polarisation singularity at the beam axis allow control of the beam modal content, filtering diffraction effects and tailoring spatial polarisation distribution. The proposed approach offers important capabilities for wavefront shaping as well as local spatial polarisation engineering. The understanding of the interaction of vector beams with metamaterials opens new opportunities for applications in microscopy, information encoding, biochemical sensing and quantum technologies.

physics.optics

Machine learning -- based diffractive imaging with subwavelength resolution

Far-field characterization of small objects is severely constrained by the diffraction limit. Existing tools achieving sub-diffraction resolution often utilize point-by-point image reconstruction via scanning or labelling. Here, we present a new imaging technique capable of fast and accurate characterization of two-dimensional structures with at least wavelength/25 resolution, based on a single far-field intensity measurement. Experimentally, we realized this technique resolving the smallest-available to us 180-nm-scale features with 532-nm laser light. A comprehensive analysis of machine learning algorithms was performed to gain insight into the learning process and to understand the flow of subwavelength information through the system. Image parameterization, suitable for diffractive configurations and highly tolerant to random noise was developed. The proposed technique can be applied to new characterization tools with high spatial resolution, fast data acquisition, and artificial intelligence, such as high-speed nanoscale metrology and quality control, and can be further developed to high-resolution spectroscopy

physics.optics