Phase-only steerable photonic nanojets.

We demonstrate numerically the feasibility of axial and angular control of the position of a photonic nanojet (PNJ) by lossless phase-only modulation of a fixed Gaussian beam illuminating a fixed 2D circular homogeneous dielectric micro-lens. We furthermore demonstrate that our phase-only modality can be used to calibrate and improve the confinement of PNJ generation.

Steerable photonic jet for super-resolution microscopy.

A promising technique in optical super-resolution microscopy is the illumination of the sample by a highly localized beam, a photonic jet (also called photonic nanojet). We propose a method of computation of incident field amplitude and phase profiles that produce photonic jets at desired locations in the near field after interaction with a fixed micro-scale dielectric lens. We also describe a practical way of obtaining the incident field profiles using spatial light modulators. We expect our photonic jet design method to work for a wide range of lens shapes, and we demonstrate its application numerically using two-dimensional micro-lenses of circular and square cross-sections. We furthermore offer a theoretical analysis of the resolution of photonic jet design, predicting among other that a larger lens can produce a narrower photonic jet. Finally, we give both theoretical and numerical evidence that the waist width of the achieved designed jets is increasing linearly and slowly over a large interval of radial distances. With uniform plane wave illumination, the circular two-dimensional micro-lens produces a similar-sized jet at a fixed radial distance, while the square lens does not form a jet at all. We expect our steerable optical photonic jet probe to enable highly localized adaptive real-time measurements and drive advances in super-resolution optical microscopy and scatterometry, as well as fluorescence and Raman microscopy. Our relatively weak peak jet intensity allows application in biology and health sciences, which require high resolution imaging without damaging the sample bio-molecules.

Autoencoder-aided measurement of concentration from a single line of speckle.

We demonstrate that a single 6mm line sample of simulated near-field speckle intensity suffices for accurate estimation of the concentration of dielectric micro-particles over a range from 104 to 6⋅106 particles per ml. For this estimation, we analyze the speckle using both standard methods (linear principal component analysis, support vector machine (SVM)) and a neural network, in the form of a sparse stacked autoencoder (SSAE) with a softmax classifier or with an SVM. Using an SSAE with SVM, we classify line speckle samples according to particle concentration with an average accuracy of over 78%, with other methods close behind.

Numerical simulation of Electron Energy Loss Spectroscopy using a Generalized Multipole Technique.

We numerically simulate low-loss Electron Energy Loss Spectroscopy (EELS) of isolated spheroidal nanoparticles, using an electromagnetic model based on a Generalized Multipole Technique (GMT). The GMT is fast and accurate, and, in principle, flexible regarding nanoparticle shape and the incident electron beam. The implemented method is validated against reference analytical and numerical methods for plane-wave scattering by spherical and spheroidal nanoparticles. Also, simulated electron energy loss (EEL) spectra of spherical and spheroidal nanoparticles are compared to available analytical and numerical solutions. An EEL spectrum is predicted numerically for a prolate spheroidal aluminum nanoparticle. The presented method is the basis for a powerful tool for the computation, analysis and interpretation of EEL spectra of general geometric configurations.

Profile estimation for Pt submicron wire on rough Si substrate from experimental data.

An efficient forward scattering model is constructed for penetrable 2D submicron particles on rough substrates. The scattering and the particle-surface interaction are modeled using discrete sources with complex images. The substrate micro-roughness is described by a heuristic surface transfer function. The forward model is applied in the numerical estimation of the profile of a platinum (Pt) submicron wire on rough silicon (Si) substrate, based on experimental Bidirectional Reflectance Distribution Function (BRDF) data.

Comparison of numerical methods in near-field computation for metallic nanoparticles.

Four widely used electromagnetic field solvers are applied to the problem of scattering by a spherical or spheroidal silver nanoparticle in glass. The solvers are tested in a frequency range where the imaginary part of the scatterer refractive index is relatively large. The scattering efficiencies and near-field results obtained by the different methods are compared to each other, as well as to recent experiments on laser-induced shape transformation of silver nanoparticles in glass.