Direct orientation contrast imaging of zinc-blende III-V materials is studied using scanning electron microscopy. A quantitative approach is taken using a 3 μm thick orientation-patterned GaP grown on GaAs sample, studying the anti-phase domain contrast with respect to the electron beam energy and the tilt angle. A qualitative approach is taken for III-V grown on non-polar materials with and without chemical mechanical polishing. Finally, a processing of the acquired image for GaP on Si reveals in plane preferential anti-phase boundaries.

We present the first realization of Transverse orientation-patterned gallium phosphide (TOP-GaP) waveguides by direct bonding and their first linear and nonlinear characterization. These structures use vertical susceptibility control to achieve modal phase matching with large mode overlap, achieving high efficiency second harmonic generation.

Achieving high conversion efficiencies in second-order nonlinear optical processes is a key challenge in integrated photonics for both classical and quantum applications. This paper presents what we believe is the first demonstration of transverse orientation-patterned gallium phosphide (TOP-GaP) waveguides showing high-efficiency second harmonic generation. In such devices, first-order modal phase matching is unlocked and optimized through the inversion of the nonlinear susceptibility along the vertical direction. We discuss here the theory behind modal phase matching in TOP structures, describe the fabrication process, and present linear and nonlinear characterizations of the TOP-GaP waveguides.

Multimode lasers have a very complex dynamics. Order emerges when the modes lock together, leading to a periodic train of pulses or a nearly constant power output with a linearly chirped frequency. The first is promoted by a saturable absorber, while the latter is connected to more subtle conditions, such as the fast dynamics of the gain. When none of these conditions is satisfied, we show that locking is still possible inside a photonic band-gap laser. We show, first in theory, that modes lock together to generate a variety of waveforms which are not trains of pulses nor chirped continuous power waves. Mode-locking (ML) is observed in experiments on a III-V/Silicon hybrid laser with the cavity made of a suitably tapered grating. The mode-locking beatnote is strongly dependent on the injected current and can be changed dynamically by more than 1 GHz in microseconds. The behaviour of the laser is critically determined by the dispersion, which can be controlled by the photonic crystal structure. By scaling up the number of interacting modes, this laser source may offer an effective and flexible way for the generation of custom waveforms. The typical platforms to generate multimode lasers rely on mode locking, achieved via a saturable absorber and fast dynamics of the gain. The authors demonstrate that mode locking in semiconductor photonic bandgap lasers is possible in the absence of a fast nonlinear mechanism, proposing an effective way of generating waveforms à la carte.

We present a new design of semiconductor mode-locked laser. It is based on a non-uniform DFB cavity engineered to support multiple equi-spaced optical modes. Moreover, we observe that the mode-locked frequency is broadly tunable, unlike traditional mode-locked lasers.

We present a new concept of integrated semiconductor laser providing broad, continuous and potentially fast tunable mode-locked frequency.

Orientation-patterned gallium phosphide (OP-GaP) is studied for frequency combs conversion from C-band to visible. Simulations of periodic and chirped OP-GaP waveguides nonlinear response are presented. Design rules for future developments are established using this study.

La forte interaction optomécanique au sein d’une nanostructure intégrée sur un circuit photonique permet la génération d’oscillation directement aux fréquences GHz sur une porteuse optique. L’ajout d’une boucle de rétroaction opto-électro-mécanique renforce la stabilité court terme de l’oscillateur.

We present the modeling of an on-chip planar electron gun using COMSOL Multiphysics. The beam coming from this electron gun goes through a trench crossing a photonic crystal. The interaction between the electrons and the photonic crystal generates photon emission by Cherenkov effect [1],[2]. An objective is to realize an electron gun working from 30V to 1000V voltage. To obtain enough photons conversion and reach the laser threshold, we aim to reach 100 nA of current in 1 mrad. The electron gun will be fabricated using several steps of e-beam lithography. Modeling of the electron gun and electron trajectories will allow to reach optimal performances while preventing from device failures.

Four tunable optomechanical crystals are coupled through a common optical path, offering a scalable pathway to complex and controllable nonlinear dynamical systems. Individual tuning of their resonances dictates their interaction. This system undergoes mechanical lasing, frequency mixing, chaos and synchronization involving two to four oscillators.

We improve the long term stability of an optomechanical crystal in self-sustained oscillations through an on-chip tuning device that compensates for long-term drift of the optomechanical oscillator. On-chip control of the mechanical resonance frequency paves the way to low noise and integrated optical frequency references.

Generation of photon pairs in time bins at telecom wavelengths is demonstrated in Photonic Crystal cavity with footprint about 70 mu m(2). With a pump peak power below 100 mu W a pair generation rate of 1 MHz is reached with pulse repetition up to 100 MHz.

Nonlinear optical resonators allow the coherent conversion of photons, yet fabrication tolerances limit their wavelength accuracy. Introducing periodic modulation in ring resonators is shown to allow robust and predictable selection of the converted photons.

Mainstream Machine learning (ML) leverages on a simplified model of the neuron, the Perceptron, which is efficiently implemented in software running on digital computers. Still, biological neurons process information by exchanging time-depending signals, e.g. spikes. Understanding how to harness "neurons" closer in behaviour to their biological model, is fascinating but challenging. One of the challenges is related to scaling up the number of interconnected neurons. Photonics is regarded as a promising approach [1]. Particularly, the large bandwidth available in optical communication channels suggests applications in specialized computing tasks, where latency is critical. Aiming at an all-optical implementation, computing-related functions such as reconfigurable matrix multiplication [2] and nonlinear activation functions [3] are available in Silicon photonics. Semiconductor lasers have shown a neuron-like response such as excitability [4], i.e. the emission of a well-defined pulse as the excitation goes above a threshold, while microring-based "neurons", exploiting the thermo-optical nonlinearity, have been demonstrated in a silicon photonic circuit [5]. Here we consider a photonic crystal based semiconductor laser, heterogeneously integrated on top of a Silicon on Insulator (SOI) waveguide. The nanolaser is composed by two sections for the gain and saturable absorber: a metal screen ensure selective pumping of the gain section with a CW laser beam. By a suitable choice of the parameters (Q-factor, gain vs absorption ratio and pumping rate), the laser operates in different regimes: excitable, pulsing with variable rate (i.e. implements the Leak Integrate and Fire model of the neuron), bistable and CW. Excitability is shown in the figure: panels (c) to (e) relate to the response to a pulsed excitation as a function of its energy (here estimated before the input coupler to the silicon chip) when the pump is set just below the threshold of self-pulsing. Panel (f) shows the spiking probability, estimated as the fraction of traces where spikes are emitted (the event is detected when signal goes above -40 arb.u.). The spiking probability follows the expected trend with the excitation, already observed in VCSELs [6] and agrees very well with our stochastic implementation of the Yamada model of self-pulsing lasers. This result paves the way to electrically pumped, interconnected spiking nanolasers, operating with manageable (0.1 mA) current levels and sub-nanosecond time scales. References [1] B. J. Shastri et al., "Photonics for artificial intelligence and neuromorphic computing," Nat. Photon. 15, 102 (2021). [2] Y. Shen et al., "Deep learning with coherent nanophotonic circuits," Nat. Photon. 11, 441 (2017). [3] A. Jha et al., "Reconfigurable all-optical nonlinear activation functions for neuromorphic photonics," Opt. Lett. 45, 4819 (2020). [4] H.J. W¨unsche et al., "Excitability of a semiconductor laser by a two-mode homoclinic bifurcation" , Phys. Rev. Lett. 88, 023901 (2001). [5] T. Van Vaerenbergh et al., "Cascadable excitability in microrings," Opt. Express 20, 20292 (2012). [6] F. Selmi et al., "Relative Refractory Period in an Excitable Semiconductor Laser," Phys. Rev. Lett. 112 183902 (2014).

This paper presents the first realization, linear and nonlinear characterization of a vertically oriented gallium phosphide (VOP-GaP) waveguide dedicated to second harmonic generation. The design, fabrication steps and characterization method are discussed.

MHz-rate generation of time-energy entangled photon pairs is demonstrated on Silicon and InGaP bichromatic Photonic Crystal cavities with µ W-level pump power. High visibility up to 94% is measured with 1 second integration.

Gallium phosphide has long held promise for integrated nonlinear photonics, owing to its high non-linear figure of merit, broad transparency and compatibility with silicon. The recent development of orientation patterning in gallium phosphide has now brought this promise within grasp. Current research efforts are focused on demonstrating and evaluating a variety of second and third-order non-linear processes on the platform, reducing optical losses, and investigating integration with Si.

Although machine learning (ML) algorithms are already applied in many fields (e.g. language recognition, temporal series prediction) using software computed on “Von Neumann” architectures, numerous technological advances (e.g. robotics, autonomous driving) require dedicated hardware. Integrated optics constitute a highly promising platform that could be harnessed for achieving portable ML chips with unprecedented power-efficiency and bandwidth [1]. Despite recent observations of ML key functionalities using integrated Silicon photonics, such as reconfigurable matrix multiplication [2] and nonlinear activation functions [3], excitability observation, the spiking mechanism of our biological neurons, remains incomplete in all-integrated systems; they are based on opto-thermal (slow) effects [4] that drastically limits its applicability in ML systems with high bandwidth requirements. Here, we use InP-based photonic crystal nanocavities heterogeneously integrated on top of a Silicon on Insulator (SOI) waveguide to demonstrate the first all-integrated (fast) excitable nanolaser.