Abstract
Optical waveguides were fabricated at the surface of Eagle2000 glass substrates, using femtosecond laser direct writing and wet etching, and their potential as intensity-modulated refractometers was assessed. Through the analysis of their broadband spectral response to different refractive index oils, we observed that mode mismatch is present when the guided mode reaches the surface of the substrate and interacts with the external medium, thus enabling the use of such optical waveguides in refractive index sensing. Refractive indices equal to or greater than that of the substrate also induced a coupling mechanism that was shown not to be suitable in these devices. The device's wavelength of operation was found to be tunable by controlling the distance between the surface and the center of the optical waveguide. However, the sensitivity was seen to diminish by increasing the latter, being nonexistent for distances greater than 5.5 mu m. In this study, the maximum sensitivity values were found for a surface to core center distance between 1 and 2 mu m, in the biological range, and 2.5 to 3 mu m, for a refractive index nearing that of the substrate. Accordingly, maximum sensitivities of approximate to 25 dB/RIU and approximate to 1200 dB/RIU were found between 1.300 < n(D)(25)degrees(C) < 1.400 and 1.490 < n(D)(25)degrees(C) < 1.500, respectively.

Abstract
Low loss optical waveguides are the key component for the fabrication of more complex integrated optics devices. In most works related to femtosecond laser written waveguides, the values presented give results at a single wavelength or in a narrow wavelength band; but some applications in optical sensing, for example, would benefit from waveguides having good propagation properties in a larger wavelength range. This paper presents results that allow one to gain insight into the major loss mechanisms present in laser written waveguides in two different types of glasses (fused silica and Eagle 2000 glass) and the dependence of those on the fabrication parameters. Finally, an example of application of broadband operating waveguides is given.

Abstract
A monolithic lab-on-a-chip fabricated by femtosecond laser micromachining capable of label-free biosensing is reported. The device is entirely made of fused silica, and consists of a microdisk resonator integrated inside a microfluidic channel. Whispering gallery modes are excited by the evanescent field of a circular suspended waveguide, also incorporated within the channel. Thermal annealing is performed to decrease the surface roughness of the microstructures to a nanometric scale, thereby reducing intrinsic losses and maximizing the Q-factor. Further, thermally-induced morphing is used to position, with submicrometric precision, the suspended waveguide tangent to the microresonator to enhance the spatial overlap between the evanescent field of both optical modes. With this fabrication method and geometry, the alignment between the waveguide and the resonator is robust and guaranteed at all instances. A maximum sensitivity of 121.5 nm/RIU was obtained at a refractive index of 1.363, whereas near the refractive index range of water-based solutions the sensitivity is 40 nm/RIU. A high Q-factor of 10(5) is kept throughout the entire measurement range.

Abstract
In this work we use the concept of paraxial fluids of light to explore quantum turbulence, probing a turbulent regime induced on an optical beam propagating inside a defocusing nonlinear media. For that purpose, we establish a physical analogue of a two-component quantum fluid by making use of orthogonal polarizations and incoherent beam interaction, obtaining a system for which the perturbative excitations follow a modified Bogoliubov-like dispersion relation. This dispersion relation features regions of instability that define an effective range of energy injection and that are easily tuned by manipulating the relative angle of incidence between the two components. Our numerical results support the predictions and show evidence of direct and inverse turbulent cascades expected from weak wave turbulence theories, which may inspire new ways to explore to quantum turbulence with optical analogues.

Abstract
Reservoir computing is a promising framework that facilitates the approach to physical neuromorphic hardware by enabling a given nonlinear physical system to act as a computing platform. In this work, we exploit this paradigm to propose a versatile and robust soliton-based computing system using a discrete soliton chain as a reservoir. By taking advantage of its tunable governing dynamics, we show that sufficiently strong nonlinear dynamics allows our soliton-based solution to perform accurate regression and classification tasks of non-linear separable datasets. At a conceptual level, the results presented pave a way for the physical realization of novel hardware solutions and have the potential to inspire future research on soliton-based computing using various physical platforms, leveraging its ubiquity across multiple fields of science, from nonlinear optical media to quantum systems.

Abstract
In the last three decades, a lot of research has been devoted to the optical response of an atomic media in near-to-resonant conditions and to how nonlinear optical properties are enhanced in these systems. However, as current research turns its attention towards multi-level and multidimensional systems interacting with several electromagnetic fields, the ever-increasing complexity of these problems makes it difficult to treat the semiclassical model of the Maxwell-Bloch equations analytically without any strongly-limiting approximations. Thus, numerical methods and particularly robust and fast computational tools, capable of addressing such class of modern and future problems in photonics, are mandatory. In this paper, we describe the development and implementation of a Maxwell-Bloch numerical solver that exploits the massive parallelism of the GPUs to tackle efficiently problems in multidimensional settings or featuring Doppler broadening effects. This constitutes a simulation tool that is capable of addressing a vast class of problems with considerable reduction of simulation time, featuring speedups up to 15 compared with the same codes running on a CPU.