Ariel Guerreiro

Abstract
Subwavelength cells of metallic nanorods arrayed in a dielectric background, termed “metamaterials”, present bulk properties that are useful to control and manipulate surface plasmon resonances. Such feature finds tremendous potential in providing a broad manifold of applications for plasmonic optical sensors. In this paper, we propose a surface-plasmon-resonance-based sensor with spectral response tunable by the volume fraction of silver present in a metamaterial layer deposited on a D-shaped photonic crystal fiber. Using computational simulations, we show that sensitivity and resolution can be hugely altered by changing the amount of constituents in the metamaterial, with no further modifications in the structure of the sensor. Moreover, the designed sensor can also be applied to label the average volume fraction of silver in the metamaterial layer and then to estimate its effective constitutive parameters.

Abstract
Light propagating in nonlinear optical materials opens the possibility to emulate quantum fluids of light with accessible tabletop experiments by taking advantage of the hydrodynamical interpretation. In this context, various optical materials have been studied in recent years, with nematic liquid crystals appearing as one of the most promising ones due to their controllable properties. Indeed, the application of an external electric field can tune their nonlocal response, and this mechanism may be useful for producing fluids of light and developing optical analogues. In this work, we extend the applicability of nematic liquid crystal to support optical analogues and study the possibility of emulating turbulent phenomena by using two fluids of light. These fluids interact with each other through the nonlinearity of the medium and generate instabilities that will lead to turbulent regimes. We also explore the possibility of exciting turbulent regimes through the decay of dark soliton stripes. The preliminary results are presented.

Abstract
In this paper, we study the implementation of a secure key distribution system based on an ultra-long fiber laser with a bi-directional erbium-doped fiber amplifier. The resilience of the system was tested against passive attacks from an eavesdropper. A similarity was observed in the spectra for both secure configurations of the system and no signature that would allow an eavesdropper to obtain the secure state of the system was observed during the state transitions.

Abstract
Abstract The propagation of light in nonlinear optical media has been widely used as a tabletop platform for emulating quantum-like phenomena due to their similar theoretical description to quantum fluids. These fluids of light are often used to study 2-dimensional phenomena involving superfluid-like flows, yet turbulent regimes still remain underexplored. In this work, we study the possibility of creating 2-dimensional turbulent phenomena and probing their signatures in the kinetic energy spectrum. To that end, we emulate and disturb a fluid of light with an all-optical defect using the propagation of two beams in a photorefractive crystal. Our experimental results show that the superfluid regime of the fluid of light breaks down at a critical velocity at which the defect starts to exert a drag force on the fluid, in accordance with the theoretical and numerical predictions. Furthermore, in this dissipative regime, nonlinear perturbations are excited on the fluid that can decay into vortex structures and thus precede a turbulent state. Using the off-axis digital holographic method, we reconstructed the complex description of the output fluids and calculated the incompressible component of the kinetic energy. With these states, we observed the expected power law that characterizes the generated turbulent vortex dipole structures. The findings enclosed in this manuscript align with the theoretical predictions for the vortex structures of 2-dimensional quantum fluids and thus may pave the way to the observation of other distinct hallmarks of turbulent phenomena, such as distinct turbulent regimes and their associated power laws and energy cascades.

Abstract
Optical tweezers use light to trap and manipulate mesoscopic scaled particles with high precision making them a useful tool in a plethora of natural sciences, with emphasis on biological applications. In principle, the Brownian-like dynamics reflect trapped particle properties making it a robust source of information. In this work, we exploit this information by plotting histogram based images of 250ms of position or displacement used as input to a Convolution Neural Network. Results of 2-fold stratified cross-validation show satisfying classifications between sizes or types of particles: Polystyrene and Polymethilmethacrylate thus highlighting the potential of CNN approaches in faster and non-invasive applications in intelligent opto and microfluidic devices using optical trapping tools.